Miracle-dz/UniFAR-FTUs huggingface dataset:
Reduction of Layer Mixing in Stratified Forming through Hydrodynamic Control

STFI-Packforsk has recently patented the “Aq-vanes”, a new technology for stratified forming headboxes. In this new solution, a thin passive liquid layer (a liquid vane or “Aq-vane”) is injected in the headbox between neighbouring pulp streams through a narrow hollow channel, thereby preventing mixing between the layers. One of the most interesting features of the Aq-vane technology is that layer purity and separation can be controlled externally by tuning a set of process parameters. This opens the field for a widespread industrial application of stratified forming, a paper maker’s quantum leap that may reduce energy and raw material consumption, lead to improved product properties and possibly even to the development of new grades. In fact, although the basic concept of producing an engineered layered structure is not new in papermaking; its application has been extremely limited to a few selected grades, such as high grammage paperboard or multi-layer tissue. The Aq-vanes have been implemented on EuroFEX, STFI-Packforsk’s research paper machine, for extensive pilot scale trials. Thereby a number of technical solutions for the injection of the liquid layer has been tested and evaluated. In a parallel project, a method for measurement of layer purity in stratified forming has been developed. It is based on sheet splitting using a heat-seal pouch lamination technique. An image analysis method is then used to identify the colour of the fibres and thus the layer mixing.
A JUMP START FOR NMF WITH N-FINDR AND NNLS

Nonnegative Matrix Factorization is a popular tool for the analysis of audio spectrograms. It is usually initialized with random data, after which it iteratively converges to a local optimum. In this paper we show that N-FINDR and NNLS, popular techniques for dictionary and activation matrix learning in remote sensing, prove useful to create a better starting point for NMF. This reduces the number of iterations necessary to come to a decomposition of similar quality. Adapting algorithms from the hyperspectral image un-mixing and remote sensing communities, provides an interesting direction for future research in audio spectrogram factorization
Experiment and numerical simulation for high pressure combustible gas jet expansion process in a bulk-loaded liquid

In order to investigate the expansion characteristics of the high pressure combustible gas jet in a bulk-loaded liquid and to explore the control methods for improveing the jet stability,a cylindrical four-stage stepped-wall chamber was designed.Using a high-speed kinescope system,the expansion and mixing process of the gas jet in the liquid was observed.A series of photos describing jet expansion form were obtained,the expansion velocity of the Taylor cavity was measured and the effects of the chamber wall shape on the jet expansion were compared.A 2-D axisymmetric gas-liquid two-phase turbulent flow model was developed to simulate the jet expansion process.The calculated jet expansion shape and expansion velocity of the Taylor cavity were consistent with experimental results.Obtained results show that vortex emerges at the chamber steps,which induces the jet to expand radially then restrains Kelvin-Helmholtz instability.The stepped-wall chamber boundary can improve the jet stability.
Concentration Fluctuations and Crossover Effects of Critical Binary Liquids Near Their Consolute Point

Various scaling functions for the critical acoustic absorption of demixing binary liquids have been predicted theoretically. In this article measurements are reported to experimentally determine the scaling function without adjustable parameter, taking into account the effects of the crossover from critical to mean-field behaviour. It is found that the empirical Bhattacharjee-Ferrell scaling function nicely fits to the experimental findings, particularly if a possible temperature dependence in the sound velocity and in the amplitude of the critical absorption term is considered accordingly.
Association of G894T Polymorphism of Endothelial Nitric Oxide Synthase Gene and Essential Hypertension

Objective To investigate the association of the G894T polymorphism of endothelial nitric oxide synthase (eNOS) gene with essential hypertension (EH) in Chinese population. Methods Polymerase chain reaction combined with restriction enzyme digestion was used to detect the polymorphism of G protein of β-3 subunit gene in 151 normotensive controls and 310 hypertensive patients (2) Fasting serum nitric oxide metabolite(NOx) and endothelin (ET) were measured by nitrate reductase and radioimmunoassay respectively. Results (1)The frequencies of T allele and GTTT genotype in EH were significantly higher than in control group; (2) SBP, DBP, MBP in patients with T allele of eNOS gene G894T polymorphism (150.5±13.6, 100.0±8.5,116.8±7.8) mmHg respectively, higher than that of GG genotype[(145.0±12.2) mmHg, (97.4±8.0) mmHg, (114.0±7.5) mmHg)]. (3)The level of NOx and the rate of NOx/ET were lower in GTTT genotype[(69.7±27.0) μmol/L, (1.0±0.6)] than in GG genotype[(78.5±32.5) μmol/L, (1.5±1.5)] of EH. The level of ET were higher in GTTT genotype[(83.3±39.7) pg/mL] than in GG genotype[(72.86±33.80) pg/mL] of EH. Conclusion The G894T plolymorphism of eNOS gene is associated with EH in Chinese population. T allele may be involved in the etiology of EH by reducing NO release of endothelium.
Digital Signal Processing for Frequency-Modulated Continuous Wave RADARs

Advanced driver-assistance systems (ADAS) and autonomous driving (AD) systems typically combine several types of sensors, such as cameras, RADARs, and LiDARs. Different types of sensors have their strengths, and effectively complement each other. Cameras and the appropriate machine vision algorithms can “see” lane marking and recognize traffic signals and signs. LiDAR can offer high (cm-level) resolution and high density of collected data points. RADAR technology is indispensable in ADAS applications because of its robustness to a variety of environmental conditions, like rain, fog, snow, and its ability to directly and precisely measure range and velocity. Basic use cases can rely on RADAR sensors only, enabling cost-effective solutions. RADAR can be used to augment, cross-check or ‘fuse’ situational models derived using advanced computer vision algorithms.
MPF-MLBS: A Multi-path Load Balancing Strategy for SDN Networks Based on Multiple Performance Factors

Aiming at the common load balancing problems in the network, a multi-path load balancing strategy (MPF-MLBS) based on multi-performance factor (MPF) for Software Defined Network (SDN) networks is proposed, which can be divided into two stages: algorithm design and strategy implementation. In the algorithm design stage, the advantages and disadvantages of the existing load balancing algorithms are analyzed, combined with the characteristics of the SDN network architecture, and the bandwidth, delay and link rate of the network link are comprehensively considered. Based on this, multiple performance factors are defined, and a load balancing algorithm based on multiple performance factors (MPF-CMP) is designed and implemented. In the strategy implementation stage, build a multi-path network topology based on the SDN architecture, and use the depth-first traversal algorithm to traverse the global network to obtain the required link information; Subsequently, the MPF-CMP algorithm and OpenFlow group table technology are combined to complete the proportional distribution of network traffic to each available path, thereby achieving multi-path load balancing of the SDN network. The simulation experiment results show that the strategy effectively exerts the SDN controller's overall network monitoring and scheduling functions, can obtain link information in real time and distribute and transmit network traffic according to the situation. The overload of a single path is avoided, the data packet transmission volume of all available paths is effectively increased, the flow transmission efficiency of the entire network is improved, and the multi-path load balancing of the SDN network is realized.
CAELI WATER VAPOUR RAMAN LIDAR CALIBRATION AT THE CABAUW EXPERIMENTAL SITE FOR ATMOSPHERIC RESEARCH

Water vapour is a crucial parameter in atmospheric physics. Concentrations are low at upper tropospheric altitudes, but radiation effects are sensitive to water vapour abundance at these levels. Obtaining reliable data of low water vapour concentrations in the upper troposphere is challenging. The Raman lidar technique for water vapour can meet this challenge, however, the Raman lidar water vapour data rely on an external source for calibration. For the Raman lidar Caeli in Cabauw, operational radiosondes launched in De Bilt, about 22 km North-East of the lidar location are routinely used for this. Differences in space and time between the observations influence the consistency and quality of the calibration. Various in-situ and remote observations of humidity are available at Cabauw that are better collocated and synchronised with the lidar measurements. These collocated observations could also be used for the lidar calibration as an alternative to the radio soundings. Among the possibilities are GNSS and microwave radiometer and tower based in-situ humidity measurements. In this paper we explore the possibilities for applying those for the Raman lidar calibration in Cabauw.
Assessment of VMS-LES and hybrid RANS VMS-LES models

Turbulent flows around bluff bodies at suband supercritical Reynolds numbers are simulated through a Variational Multiscale (VMS) Large Eddy Simulation (LES) model and a hybrid RANS/VMS-LES model. In VMS-LES, the separation between the largest and the smallest resolved scales is obtained through a variational projection operator and finite-volume cell agglomeration. Eddy-viscosity models are used to account for the effects of the unresolved scales. In the VMS approach, they are only added to the smallest resolved ones. We use a hybrid RANS/LES approach with a wall law for the simulation of supercritical turbulent flows. A smooth blending function allows a progressive switch from LES to RANS to be obtained, depending on the values of a blending parameter. The assessment proposed relies on the simulation of a series of flows for which experiments are available. They involve subcritical flows around a circular cylinder at Reynolds numbers (Re) 3900, 10000, 20000, and around a sphere at Reynolds numbers 10000, 50000, and supercritical flows around a circular cylinder (Re=140000, 500000, 1 million, 2 million) and a sphere (Re=400000).
VIBRATION OF POROUS PLATES IN STRUCTURAL/ACOUSTIC COUPLING APPLICATIONS

The transverse vibration of thin poroelastic plates can be described with the help of the standard theory of plates, the fluid-solid relative displacement in the pores and fluid-solid coupling terms. Two coupled equations of dynamic equilibrium were obtained that can be solved by a variational method. The method can be used for any boundary condition at the edges. The influence of the plate parameters is studied and a condition of maximum damping is given. The calculated plate deflection is compared to experimental results for clamped porous plates. Studies currently in progress and possible applications involving structural/acoustic interactions are outlined.
Is Deep Reinforcement Learning Ready for Practical Applications in Healthcare? A Sensitivity Analysis of Duel-DDQN for Hemodynamic Management in Sepsis Patients

The potential of Reinforcement Learning (RL) has been demonstrated through successful applications to games such as Go and Atari. However, while it is straightforward to evaluate the performance of an RL algorithm in a game setting by simply using it to play the game, evaluation is a major challenge in clinical settings where it could be unsafe to follow RL policies in practice. Thus, understanding sensitivity of RL policies to the host of decisions made during implementation is an important step toward building the type of trust in RL required for eventual clinical uptake. In this work, we perform a sensitivity analysis on a state-of-the-art RL algorithm (Dueling Double Deep Q-Networks) applied to hemodynamic stabilization treatment strategies for septic patients in the ICU. We consider sensitivity of learned policies to input features, embedding model architecture, time discretization, reward function, and random seeds. We find that varying these settings can significantly impact learned policies, which suggests a need for caution when interpreting RL agent output.
Pareto-Efficient Quantum Circuit Simulation Using Tensor Contraction Deferral

With the current rate of progress in quantum computing technologies, systems with more than 50 qubits will soon become reality. Computing ideal quantum state amplitudes for circuits of such and larger sizes is a fundamental step to assess both the correctness, performance, and scaling behavior of quantum algorithms and the fidelities of quantum devices. However, resource requirements for such calculations on classical computers grow exponentially. We show that deferring tensor contractions can extend the boundaries of what can be computed on classical systems. To demonstrate this technique, we present results obtained from a calculation of the complete set of output amplitudes of a universal random circuit with depth 27 in a 2D lattice of $7 \times 7$ qubits, and an arbitrarily selected slice of $2^{37}$ amplitudes of a universal random circuit with depth 23 in a 2D lattice of $8 \times 7$ qubits. Combining our methodology with other decomposition approaches found in the literature, we show that we can simulate $7 \times 7$-qubit random circuits to arbitrary depth by leveraging secondary storage. These calculations were thought to be impossible due to resource requirements.
High Resolution Computed Tomography (HRCT) Assessment of Suspected COVID-19 Patients -----A Study of 51 Patients

Original Research Article Objective: To investigate High resolution computed tomography (HRCT) features of patients with suspected COVID 19 in Moulvibazar district, Bangladesh and to evaluate the diagnostic value of HRCT and reverse transcriptase polymerase chain reaction (RT PCR) for COVID 19 pneumonia. Methods: This retrospective study included all patients with COVID 19 pneumonia suspicion, who were examined by both HRCT and RT PCR at initial presentation. The sensitivities of both tests were then compared. For patients with a final confirmed diagnosis, clinical and laboratory data, in addition to HRCT imaging findings were evaluated. Results: Total of 21 cases was finally diagnosed with COVID-19 pneumonia among 51 suspected patients. Twenty patients had abnormal HRCT findings at presentation, and only one patient had a normal thoracic HRCT. Using RT-PCR, 19 cases showed positivity, with 2 cases initially missed. Amongst the missed cases, patients had a positive result in the second RT-PCR test (after 2 and 4 days) Therefore, sensitivity of HRCT examinations was 95.45 % at presentation, whereas first round RT-PCR sensitivity was 86.36 %. Conclusion: COVID 19 manifest with chest HRCT imaging abnormalities even in asymptomatic patients. RT PCR may produce initial false negative results. We suggest that patients with typical HRCT findings with negative RT PCR results should be isolated, and RT PCR should be repeated to avoid misdiagnosis.
Optimized Heat Treatment Enhances the Anti-Inflammatory Capacity of Ginger

This study aims to investigate the relationship between constituent contents and anti-inflammatory activities of heat processed gingers, and to optimize heat process to enhance ginger’s anti-inflammatory capacity. After 3 h of heat treatment at 75, 100, and 125°C, the gingerols content was reduced by 6.8, 12.6, and 42.7%, respectively, and the shogaols content was increased by 2.95, 4.85, and 9.34 fold, respectively. After 3 h of heat treatment at 150°C, the gingerols content was dramatically reduced by 89.5% and the increased shogaols content was even lower than treatment at 125°C. The tumor necrosis factor-α-, prostaglandin E2, and nitric oxide-inhibitory capacities of ginger could be increased by heat treatment. However, at high temperature, the enhanced ability would be decreased. The enhanced tumor necrosis factor-α-, prostaglandin E2-, and nitric oxide-inhibitory capacities of ginger was attenuated after 40, 60, and 180 min of heat treatment at 150°C, respectively. The results indicated that the TNF-α-inhibitory capacity of ginger was the most susceptible to heat. Only the prostaglandin E2-inhibitory capacity correlated with the shogaols content, which implies that heat derived shogaols contributed primarily to the prostaglandin E2-inhibitory capacity enhancement. We suggest that the optimal heat process condition is 125°C for 40–60 min for ginger to reach the maximum tumor necrosis factor-α-, prostaglandin E2-, and nitric oxide-inhibitory capacities.
Granger Causal Inference from Spiking Observations via Latent Variable Modeling

Extracting directional connectivity in a neuronal ensemble from spiking observations is a key challenge in understanding the circuit mechanisms of brain function. Existing methods proceed in two stages, by first estimating the latent processes that govern spiking, followed by characterizing connectivity using said estimates. As such, the extracted networks in the second stage are highly sensitive to the accuracy of the estimates in the first stage. In this work, we introduce a framework to directly extract Granger causal links from spiking observations, without requiring intermediate time-domain estimation, by explicitly modeling the endogenous and exogenous latent processes that underlie spiking activity. Our proposed method integrates several techniques such as point processes, state-space modeling and Pólya-Gamma augmentation. We demonstrate the utility of our proposed approach using simulated data and application to real data from the rat brain during sleep.
Walkability and Fitness Center Prices, Opening Hours, and Extra Services: The Case of Madrid, Spain

Walkability has been associated with urban development and political plans, contributing to more connected cities with improvements in communication, shopping, and pedestrian base. Among these services, fitness centers are becoming important elements for communities due to their impact on the health and welfare of citizens. The present study aims to examine how an area’s Walk Score® affects fitness center services, specifically membership costs, opening hours, and aquatic services. Data from 193 fitness centers were retrieved, representing all the areas of the municipality of Madrid, Spain, including fitness centers in the 21 city districts. A nonlinear relationship between an area’s Walk Score® and fitness centers’ monthly fees is observed. Only in premium fitness centers, a weak curvilinear model is observed, following a quadratic equation, showing that fitness centers with higher prices are in less walkable areas. Additionally, the association between Walk Score® and a fitness center’s opening hours reveals that fitness centers with wider hours of operation tend to be in moderately to highly walkable locations. Lastly, the existence of a swimming pool is related to a lower Walk Score®. Thus, fitness centers in less walkable areas try to offer additional services as differentiation from competitors, whereas centers in walkable locations use this advantage as a strength.
Profiling Virulence and Antimicrobial Resistance Markers of Enterovirulent Escherichia Coli from Fecal Isolates of Adult Patients with Enteric Infections in West Cameroon

Objectives This study aimed to identify virulent and antimicrobial resistant genes in fecal E. coli in Mbouda, Cameroon. Methods A total of 599 fecal samples were collected from patients with enteric infections who were ≥ 20 years old. E. coli was isolated on the MacConkey agar and virulent genes were detected by multiplex/simplex PCR. Isolates in which ≥ 1 virulent gene was detected were subjected to antibiotic susceptibility testing. The resulting resistant isolates were subjected to PCR, followed by sequencing for resistant genes detection. Results There were 119 enterovirulent E. coli identified, amongst which 47.05% were atypical enteropathogenic E. coli (EPEC), 36.97% enterotoxigenic E. coli, 10.08% Shiga toxin producing E. coli (STEC) and 5.88% were enteroinvasive E. coli (EIEC). The occurrence of the eae gene (47.06%) was higher compared with CVD432 (33.61%), aaic (13.45%), stx2 (10.08%) and stx1 (0.84%). High resistance rates were noted for ampicillin (94.64% EPEC, 91.67% STEC, 59.09% EAEC, and 57.14% EIEC) and sulfamethoxazole-trimethoprim (100% EPEC and 83.33% STEC, 81.82% EAEC and 71.43% EIEC). sul2 (71.43%), tetB (64.71%), tetA (59.94%) and blaTEM (52.10%) were detected. A double mutation (S83L; D87N) was seen in gyrA and a single mutation (S80I) was observed in parC. Conclusion These findings suggested that measures should be taken to reduce the harm of E. coli to public health.
Evaluation of Peruvian Government Interventions to Reduce Childhood Anemia

Background: In Peru, anemia has been a persistent health problem that is known to lead to irreversible cognitive and developmental deficits in children. The Peruvian government has recently made anemia a primary health concern by passing legislation in 2017 that makes anemia an intersectoral priority. This new legislation fortifies previous programs while creating new programs that target specific age groups. Objectives: Evaluate the effectiveness of government programs in Madre de Dios, Peru to reduce anemia prevalence and increase hemoglobin levels among children ages 2–11 years old. Methods: Propensity scores are used to match 688 children enrolled in 2018, after the legislation, and 2,140 children enrolled in previous studies our team conducted in the region between 2014 and 2017, based on sex, age (years), intervention status (prior/post), community income, presence of a health post in the community (yes/no), community type (indigenous, non-indigenous rural, non-indigenous urban) and road access (fraction of the number of months out of the year with road access). A pseudo matched case-control analysis to evaluate changes in anemia prevalence and hemoglobin was conducted using t-tests and multivariate models. Program effectiveness is evaluated overall, by age groups (2–4, 5–7 and 8–11 years old), and community type (indigenous vs. urban). Findings: The adjusted odds ratio indicated lower odds of anemia (OR = 0.31, 95%CI 0.17–0.54) for children exposed to the anemia prevention programs vs. those not exposed. The effect was not significantly different across age groups; however, the intervention effects significantly differed by community type among children 8–11 years old, with urban children less likely to benefit from anemia interventions (OR = 0.69, 95% CI 0.38–1.25) compared to indigenous children (OR = 0.21, 95% CI 0.08–0.56). Conclusion: Government programs to reduce anemia in Madre de Dios were found to be associated with reduced anemia prevalence in the study communities. However, the lack of program monitoring precludes the attribution of anemia decline to specific interventions or program components. In addition, regional anemia prevalence remains high according to the 2019 Demographic and Health Survey, suggesting impaired population impact. Program monitoring and evaluation is a key component of health interventions to improve program implementation effectiveness.