Miracle-dz/UniFAR-FTUs huggingface dataset:
From cardiorenal syndromes to cardionephrology: a reflection by nephrologists on renocardiac syndromes

ABSTRACT Cardiorenal syndromes (CRS) are broadly defined as disorders of the heart and kidneys whereby acute or chronic dysfunction in one organ may induce acute or chronic dysfunction of the other. CRS are currently classified into five categories, mostly based on disease-initiating events and their acuity or chronicity. CRS types 3 and 4 (also called renocardiac syndromes) refer to acute and chronic kidney dysfunction resulting in acute and chronic heart dysfunction, respectively. The notion of renocardiac syndromes has broadened interest in kidney–heart interactions but uncertainty remains in the nephrological community's understanding of the clinical diversity, pathophysiological mechanisms and optimal management approaches of these syndromes. This triple challenge that renocardiac syndromes (and likely other cardiorenal syndromes) pose to the nephrologist can only be faced through a specific and demanding training plan to enhance his/her cardiological scientific knowledge and through an appropriate clinical environment to develop his/her cardiological clinical skills. The first must be the objective of the subspecialty of cardionephrology (or nephrocardiology) and the second must be the result of collaboration with cardiologists (and other specialists) in cardiorenal care units. This review will first consider various aspects of the challenges that renocardiac syndromes pose to nephrologists and, then, will discuss those aspects of cardionephrology and cardiorenal units that can facilitate an effective response to the challenges.
Capacity Analysis of Channel Inversion Using Space-Time Block Coding with Transmit Power Control

In this paper, we analyze channel inversion with transmit diversity in terms of capacity and bit error rates in correlated fading. We obtain the Shannon capacity of Rayleigh fading channel under channel inversion using spatially correlated dual branch orthogonal space-time block coding, in comparison with the optimal power and rate adaptation policy, and provide a simple fixed-rate power adaptation policy to invert the Rayleigh fading into additive white Gaussian noise channel, and obtain the bit error rates using binary phase-shift keying modulation with/without channel inversion. It is found that the correlation generally causes a loss in capacity, which becomes more distinct with channel inversion relative to the optimal power and rate adaptation policy, especially when power correlation is greater than 0.5, and hinders otherwise possible full inversion. Transmit power truncation introduces power gain over full inversion, which manifests itself as an increase in capacity and a decrease in bit error probability. This gain increases with decreasing truncation level of the allowed peak transmit power. Inverting with truncation, a gain of about 19 dB in signal-to-noise ratio is obtained over classical single-antenna transmission without inversion. This gain may be further increased by a combination of truncation and correlation levels, as the correlation surprisingly turns to advantage when the normalized permitted peak-power is below 2 dB. However, the gain is normally accompanied by lower throughput or bandwidth expansion for a fixed data rate due to outage.
Forecasting Shanghai Container Freight Index: A Deep-Learning-Based Model Experiment

With the increasing availability of large datasets and improvements in prediction algorithms, machine-learning-based techniques, particularly deep learning algorithms, are becoming increasingly popular. However, deep-learning algorithms have not been widely applied to predict container freight rates. In this paper, we compare a long short-term memory (LSTM) method and a seasonal autoregressive integrated moving average (SARIMA) method for forecasting the comprehensive and route-based Shanghai Containerized Freight Index (SCFI). The research findings indicate that the LSTM deep learning models outperformed SARIMA models in most of the datasets. For South America and the east coast of the U.S. routes, LSTM could reduce forecasting errors by as much as 85% compared to SARIMA. The SARIMA models performed better than LSTM in predicting freight movements on the west and east Japan routes. The study contributes to the literature in four ways. First, it presents insights for improving forecasting accuracy. Second, it helps relevant parties understand the trends of container freight markets for wiser decision-making. Third, it helps relevant stakeholders understand overall container shipping market trends. Lastly, it can help hedge against the volatility of freight rates.
Additive manufacturing of concrete in construction: potentials and challenges of 3D concrete printing

ABSTRACT Additive manufacturing is gaining ground in the construction industry. The potential to improve on current construction methods is significant. One of such methods being explored currently, both in academia and in construction practice, is the additive manufacturing of concrete (AMoC). Albeit a steadily growing number of researchers and private enterprises active in this field, AMoC is still in its infancy. Different variants in this family of manufacturing methods are being developed and improved continuously. Fundamental scientific understanding of the relations between design, material, process, and product is being explored. The collective body of work in that area is still very limited. After sketching the potential of AMoC for construction, this paper introduces the variants of AMoC under development around the globe and goes on to describe one of these in detail, the 3D Concrete Printing (3DCP) facility of the Eindhoven University of Technology. It is compared to other AMoC methods as well as to 3D printing in general. Subsequently, the paper will address the characteristics of 3DCP product geometry and structure, and discuss issues on parameter relations and experimental research. Finally, it will present the primary obstacles that stand between the potential of 3DCP and large-scale application in practice, and discuss the expected evolution of AMoC in general.
Single-Cell RNA Sequencing Analysis for Oncogenic Mechanisms Underlying Oral Squamous Cell Carcinoma Carcinogenesis with Candida albicans Infection

Oral squamous cell carcinoma (OSCC) carcinogenesis involves heterogeneous tumor cells, and the tumor microenvironment (TME) is highly complex with many different cell types. Cancer cell–TME interactions are crucial in OSCC progression. Candida albicans (C. albicans)—frequently pre-sent in the oral potentially malignant disorder (OPMD) lesions and OSCC tissues—promotes malignant transformation. The aim of the study is to verify the mechanisms underlying OSCC car-cinogenesis with C. albicans infection and identify the biomarker for the early detection of OSCC and as the treatment target. The single-cell RNA sequencing analysis (scRNA-seq) was performed to explore the cell subtypes in normal oral mucosa, OPMD, and OSCC tissues. The cell composi-tion changes and oncogenic mechanisms underlying OSCC carcinogenesis with C. albicans infec-tion were investigated. Gene Set Variation Analysis (GSVA) was used to survey the mechanisms underlying OSCC carcinogenesis with and without C. albicans infection. The results revealed spe-cific cell clusters contributing to OSCC carcinogenesis with and without C. albicans infection. The major mechanisms involved in OSCC carcinogenesis without C. albicans infection are the IL2/STAT5, TNFα/NFκB, and TGFβ signaling pathways, whereas those involved in OSCC carcinogenesis with C. albicans infection are the KRAS signaling pathway and E2F target down-stream genes. Finally, stratifin (SFN) was validated to be a specific biomarker of OSCC with C. albicans infection. Thus, the detailed mechanism underlying OSCC carcinogenesis with C. albicans infection was determined and identified the treatment biomarker with potential precision medicine applications.
Optimized Context-Adaptive Binary Arithmetic Coder in Video Compression Standard Without Probability Estimation

CABAC is a Context Adaptive Binary Arithmetic Coder utilized in novel AVC/H.264 of video standard. AC (arithmetic coding) permits important enhancement in the compression. However, the complexity of implementation is main drawback because of slowness and hardware cost. In this paper, we propose the implementation of MPEG4/H-264 AVC against M-decoder without PE (Probability Estimation). Furthermore, in order to estimate an algorithm, we have compared many existing methods, and the comparison takes place based on power dissipation and device utilization.
Combined Treatment with Ultrasound and Immune Checkpoint Inhibitors for Prostate Cancer

Background: Ultrasound (US) is mostly used for diagnostic purpose but could be used for cancer treatments with a US intensity or frequency fitted to such a purpose. Prostate cancer (PC) has the highest prevalence in the urological field, but indications for immune checkpoint inhibitors (ICIs) for PC are limited to very few cases. In this study, we compared the antitumor effect of US irradiation alone with the combined use of US and ICIs in vitro and in vivo. Methods: PC cell line TRAMP-C2 cells were used in our experiments. TRAMP-C2 cells were irradiated with US with pulse repeated frequencies (PRF) of 1, 10, and 100 Hz. Cell proliferation was evaluated by MTS assay and apoptotic cells were analyzed using flow cytometry. To verify the antitumor effect of US irradiation on PC in vivo, we conducted animal experiments using mice. TRAMP-C2-bearing mice were irradiated with US with PRF of 10 and 100 Hz. Three weeks after the start of US irradiation, anti-PD-1 antibody was administered to the mice. Finally, mice were sacrificed and tumors were collected. Immunohistochemical (IHC) analyses were assessed for cleaved caspase-3 and CD3 in tumor cell extracts. Results: Cell proliferation assays showed that 1 and 10 Hz US significantly inhibited cell survival (p < 0.0001). In addition, US irradiation induced apoptosis at 1, 10, and 100 Hz (p = 0.0129, p = 0.0150, and p = 0.0017, respectively). In animal experiments, a significant tumor growth inhibitory effect was observed at 10 and 100 Hz, and 100 Hz + ICIs (p < 0.05, respectively). Hematoxylin–eosin (H–E) staining showed a significant increase in the necrotic area of the tumor at 100 Hz and 100 Hz + ICIs (p < 0.05, respectively). In addition, under IHC staining the expression level of cleaved caspase-3 and the number of CD3-positive cells increased at 100 Hz (p < 0.05, respectively). Conclusion: US irradiation induced apoptosis in cells and reduced cell viability. In vivo tumor growth was suppressed by combined treatment with US irradiation and ICIs. Further research on immune system activation will lead to less invasive and more efficient treatments for PC.
The Policy of Land Reclamation Use of Coastal Dike Development in Jakarta Bay

This paper discusses the social problems of the use of land (old and new) in tidal flood disaster management that often occur in Jakarta Bay and its alternative solution policy. One of the mitigation efforts is to build a coastal dike that serves to hold off the runoff of the sea to the mainland. However, the construction of coastal dike is not easy because the residents have used the land along the coastline for various purposes that are not following it is designation. By using the qualitative-descriptive method, the results of this study show that the land around the coast has been used by the community not following the rules to make settlements and make marine processing business. Whereas for a new land reclamation it has been used to make temporary docks and potentially be used improperly. The policy alternative offered is on new land have been planned to build flats, marine products processing facilities, fish markets, docks, and green open space.
Line termination net for load overvoltage cancellation in medium to high power three-phase PWM VSI induction motor drives

A line termination net (LTN) suitable for overvoltage cancellation in PWM VSI induction motor (IM) drives is investigated, deriving reliable LTN sizing design criteria in the medium-to-high power range. Such an LTN concept has been successfully tested for small power IM drives, by defining analytical criteria which are of general validity. These ones here are applied to medium-to-high power drives accounting for the LTN power loss terms which are negligible in small power drives. The effectiveness of the proposed power loss terms model is experimentally tested on a reference 55 kW IM.
CCD PHOTOMETRY, PERIOD ANALYSIS AND EVOLUTIONARY STATUS OF THE PULSATING VARIABLE TYC 3292-1328-1

Multi-color (BVIc) CCD-derived photometric data were acquired from TYC 3292-1328-1, a pulsating variable classified as a high amplitude δ Scuti-type (HADS) system. Analysis of precise time-series lightcurve (LC) data was accomplished using discrete Fourier transformation which revealed a mean fundamental mode (f0) of oscillation at 10.20831±0.00027 d-1 along with five other partial harmonics (2f0 and 6f0). No other statistically significant frequency shared by all bandpasses was resolved following successive pre-whitening of each residual signal. While no other times-of-maximum were found in the literature, 26 new ToMx values are reported herein. The evolutionary status, age and physical nature of TYC 3292-1328-1 were modeled using the PAdova & TRieste Stellar Evolution Code (PARSEC) for generating stellar tracks and isochrones. At this time, all available results for TYC 3292-1328-1 are consistent with its classification as a HADS variable.
Giant Late Triassic ichthyosaurs from the Kössen Formation of the Swiss Alps and their paleobiological implications

ABSTRACT The Late Triassic was populated by the largest ichthyosaurs known to date, reaching lengths of over 20 m. Recent discoveries include the remains of giant ichthyosaurs from the Austroalpine nappes of the eastern Swiss Alps. The finds come from the lower two members of the Kössen Formation (late Norian to Rhaetian). The material consists of a very large tooth lacking most of the crown from the Rhaetian Schesaplana Member, a postcranial bone association of one very large vertebra and ten rib fragments also from the Schesaplana Member, and an association of seven very large vertebral centra from the upper Norian to lower Rhaetian Alplihorn Member. These associations represent the only published partial skeletons of large to giant ichthyosaurs younger than middle Norian. We compare the material with the two largest ichthyosaurs known from partial skeletons, Shonisaurus popularis (15 m) and Shastasaurus sikkanniensis (21 m) from the late Carnian (ca. 230 Ma) of Nevada and the middle Norian (ca. 218 Ma) of British Columbia, respectively. The incomplete tooth confirms that at least some giant ichthyosaurs had teeth. Based on their proportional differences, the two bone associations may represent two different taxa of Shastasaurus-like ichthyosaurs. The larger and geologically younger specimen may have been nearly the size of S. sikkanniensis, and the smaller that of S. popularis. These giant ichthyosaurs from the eastern Swiss Alps indicate that such ichthyosaurs also colonized the western Tethys. The finds also unequivocally document that giant ichthyosaurs persisted to the latest Triassic.
Automatic detection, classification, and long‐term investigation of temporal–spatial changes of atmospheric rivers in the Middle East

Most water vapour in various subtropical regions is transported by atmospheric rivers (ARs). It is crucial to study this phenomenon, especially in regions more vulnerable to climate change due to population growth and aridity. The study's primary purpose was to detect ARs in the Middle East. According to expectations, ARs were classified based on strength and temporal–spatial distribution and their changes were examined to characterize the risks of the phenomenon. The results showed that ARs had significantly increased over the past 50 years (1971–2020). The most positive increase was related to weak ARs (Cat 1) in the last two decades and exceptional events (Cat 5) in the last decade. The results also indicated the role of terrain in limiting the path of the AR axis and multiple sources of moisture in their strongest form. The occurrence of hazardous events (Cat 4 and 5) was estimated at up to 22% of all ARs in the Middle East, with the highest frequency in the last three decades. It was also found that events with a maximum IVT of >1,000 kg·m−1·s−1 occurred 10 times during the last half of the last century. Also, an AR with a maximum IVT of 1,102 kg·m−1·s−1 occurred once in the region. The temporal distribution of these extreme events showed that they could occur at any time, depending on the conditions of AR formation. However, extreme events mainly occurred in March.
The ‘imaginary’ challenge of remaking subnational governance: regional identity and contested city-region-building in the UK

ABSTRACT With the structuring of subnational governance driven primarily by economic goals, an issue that has become increasingly overlooked is that of identity. Drawing on interviews with stakeholders from the Sheffield City Region, the paper builds on Jones and Woods’ framework of 2013 of ‘material’ and ‘imagined’ coherence, demonstrating the ‘imaginary’ challenge of remaking subnational governance in the context of rescaling from regions to city-regions. It shows that historical regional identities can persist even in the absence of associated material components of governance, and that rescaling can create asymmetries between material and imagined coherence, resulting in competing imaginaries that hinder the new subnational arrangements.
The TRIAX 6 Element for Axisymmetric Analysis by the Matrix Displacement Method

The investigation of axisymmetric states of stress by the matrix displacement method may, in principle, be carried out as an ordinary exercise of three-dimensional analysis, using TETRA 4, TETRA 10 or other suitable elements. However, this approach is clearly not the most efficient by not taking advantage ab initio of the inherent simplifications arising in an axisymmetric state; this leads to an unnecessary inflation of the number of unknowns and complexity of the mesh. A number of techniques to deal with this limiting condition of a three-dimensional state have been developed at the ISD. The theory for one specific element, TRIAX 6 which evolves most naturally from the tapered TRIM 6 element analysed in the preceding note 8 is presented.
Min–max version of single-machine scheduling with generalized due dates under scenario-based uncertainty

This article considers the min–max version of a single-machine scheduling problem with generalized due dates under processing time uncertainty. The objective is to minimize the maximum number of tardy jobs over all scenarios. For a problem with a common due date, denoted d, it is shown that the case with a fixed number of scenarios is weakly NP-hard and has no fully polynomial time approximation scheme, although it has a polynomial time approximation scheme. Furthermore, it is shown that the case with an arbitrary number of scenarios has no α-approximation algorithm for any constant . For a problem with identical due date intervals, it is shown that the case with two scenarios is strongly NP-hard and has no α-approximation algorithm for any constant . As a practical solution approach, a genetic algorithm is proposed and numerical experiments are conducted to verify its performance.
The Effect of Impact Compliance, Velocity, and Location in Predicting Brain Trauma for Falls in Sport

of Biomechanics in the School of Human Kinetics at University of Ottawa in Ottawa, Canada. Abstract Peak linear and angular acceleration are commonly used to measure concussion risk. In efforts to better understand the importance of loading factors affecting head dynamic response, the purpose of this study was to examine the effects of impact velocity, location, and compliance on head acceleration. A Hybrid III headform and modified neckform attached to a drop tower were subject to 4 impact velocities (1.5, 3.0, 4.5, 6.0 m/s) and 3 surfaces: steel, vinyl nitrile foam, and Rubatex R338 rubber foam to represent falls onto a hard surface, a helmeted fall (i.e. football helmet), and a gymnastics mat, respectively. Each combination of velocity and compliance were tested at front, front boss, side, and rear boss negative azimuth. Regression analysis were conducted for each impact location and revealed that compliance had a consistently stronger influence on head dynamic response than velocity.
A New Graph-Based Fractality Index to Characterize Complexity of Urban Form

Examining the complexity of urban form may help to understand human behavior in urban spaces, thereby improving the conditions for sustainable design of future cities. Metrics, such as fractal dimension, ht-index, and cumulative rate of growth (CRG) index have been proposed to measure this complexity. However, as these indicators are statistical rather than spatial, they result in an inability to characterize the spatial complexity of urban forms, such as building footprints. To overcome this problem, this paper proposes a graph-based fractality index (GFI), which is based on a hybrid of fractal theory and deep learning techniques. First, to quantify the spatial complexity, several fractal variants were synthesized to train a deep graph convolutional neural network. Next, building footprints in London were used to test the method, where the results showed that the proposed framework performed better than the traditional indices, i.e., the index is capable of differentiating complex patterns. Another advantage is that it seems to assure that the trained deep learning is objective and not affected by potential biases in empirically selected training datasets Furthermore, the possibility to connect fractal theory and deep learning techniques on complexity issues opens up new possibilities for data-driven GIS science.
Propositional and activity monitoring using qualitative spatial reasoning

Communication is the key to effective teamwork regardless of whether the team members are humans or machines. Much of the communication that makes human teams so effective is non-verbal; they are able to recognize the actions that the other team members are performing and take their own actions in order to assist. A robotic team member should be able to make the same inferences, observing the state of the environment and inferring what actions are being taken. In this thesis I introduce a novel approach to the combined problem of activity recognition and propositional monitoring. This approach breaks down the problem into smaller sub-tasks. First, the raw sensor input is parsed into simple, easy to understand primitive semantic relationships known as qualitative spatial relations (QSRs). These primitives are then combined to estimate the state of the world in the same language used by most planners, planning domain definition language (PDDL) propositions. Both the primitives and propositions are combined to infer the status of the actions that the human is taking. I describe an algorithm for solving each of these smaller problems and describe the modeling process for a variety of tasks from an abstracted electronic component assembly (ECA) scenario. I implemented this scenario on a robotic testbed and collected data of a human performing the example actions. Thesis Supervisor: Brian C. Williams Title: Professor of Aeronautics and Astronautics