Miracle-dz/UniFAR-FTUs huggingface dataset:
Metropolitan bicycle-sharing system in the Polish context of various needs of cities, towns, and villages

Abstract Bicycle-sharing systems (BSSs) have started to play an important role in the transport systems of cities worldwide as a sustainable alternative to the dominant motorised mobility culture. BSSs have also expanded over time to include regions and metropolitan areas as well as small towns and rural areas. The purpose of this paper is to identify and compare the goals of connecting individual communes in a metropolitan area to a metropolitan bicycle system. The authors applied a case study of the MEVO metropolitan bicycle system consisting of electrically assisted bicycles, introduced in 2019 in 14 communes of the Gdańsk-Gdynia-Sopot Metropolitan Area (GGSMA) in Poland. The study used GGSMA-designated metropolitan zoning to group the goals pursued by the participants when joining the project. This paper is the first to identify the goals that inclined small towns and rural areas to accede to the BSS. The results show that the largest cities in the metropolis that make up its core count on bike sharing to solve the problems of congested city centres, while small towns and rural areas see the BSS as an opportunity to improve the quality of life of the inhabitants, as the first mode of public transport, as an opportunity to be closer and more identified with the metropolitan core, and as a chance to develop tourism and recreation.
Discrete Optimal Tracking Control for a Two-Wheel Mobile Robot Driven by DC Motors

In this paper, an optimal control is designed and developed to track time-varying desired paths. A discrete-time linear model for the mobile robot is first developed from the robot dynamics. Then, an optimal controller is formulated by solving a Riccati equation to track the robot desired orientation rate that causes the robot to track a desired position in a short time with less effort. The proposed discrete optimal controller is designed to track desired velocities of robot wheels, that causes a desired robot orientation rate, that are computed from the robot kinematics. Numerical simulations are introduced to demonstrate the effectiveness of the proposed discrete optimal controller.
Extraction of the intrinsic base region sheet resistance in bipolar transistors

A new method for extracting the intrinsic base sheet resistance in bipolar transistors is presented. In contrast to existing methods, which give the sheet resistance at a given forward bias, the method proposed here allows the determination of the zero-bias sheet resistance of the intrinsic base which is an important parameter in both process characterization and circuit design. Furthermore, the new method is not restricted to a narrow range of biases and emitter widths as in existing methods, since the effects of current crowding, base conductivity modulation and base width modulation are accurately taken into account in the extraction procedure.
Improved Intelligibility Prediction in the Modulation Domain

sEPSMcorr is a recently proposed intelligibility measure that combines a modulation domain auditory model with a correlation similarity metric inspired by the STOI measure. In this paper, we aim at improving the overall performance of sEPSMcorr, particularly in modulated noise conditions. We propose to improve its auditory model and use a segmentation scheme and similarity metric adapted from the extended STOI measure that works better than STOI with modulated noise. Performance evaluation against subjective data shows the modified measure is able to predict intelligibility much better than the original version in conditions involving modulated noise, nonlinear processing, and reverberation. The modified sEPSMcorr also has better overall performance than several baseline intelligibility measures, especially in modulated noise conditions. Additionally, we study the contribution of the proposed modifications to performance by evaluating variants of the modified measure where subsets of the modifications are in effect.
Reliable Force Predictions for a Flapping-Wing Micro Air Vehicle: A “Vortex-Lift” Approach

Vertical and horizontal force of a flapping-wing micro air vehicle (MAV) has been measured in slow-speed forward flight using a force balance. Detailed information on kinematics was used to estimate forces using a blade-element analysis. Input variables for this analysis are lift and drag coefficients. These coefficients are usually derived from steady-state measurements of a wing in translational flow. Previous studies on insect flight have shown that this method underestimates forces in flapping flight, mainly because it cannot account for additional lift created by unsteady phenomena. We therefore derived lift and drag coefficients using a concept for delta-wings with stably attached leading-edge vortices. Resulting lift coefficients appeared to be a factor of 2.5 higher than steady-flow coefficients, and match the results from previous (numerical) studies on instantaneous lift coefficients in flapping flight. The present study confirms that a blade-element analysis using force coefficients derived from steady-state wind tunnel measurements underestimates vertical force by a factor of approximately two. The equivalent analysis, using “vortex-lift” enhanced coefficients from a delta-wing analogue, yields very good agreement with force balance measurements, and hence seems to be a good approximation for lift-enhancing flow phenomena when modelling flapping flight.
Surrogate/spent fuel sabotage : aerosol ratio test program and Phase 2 test results.

A multinational test program is in progress to quantify the aerosol particulates produced when a high energy density device, HEDD, impacts surrogate material and actual spent fuel test rodlets. This program provides needed data that are relevant to some sabotage scenarios in relation to spent fuel transport and storage casks, and associated risk assessments; the program also provides significant political benefits in international cooperation. We are quantifying the spent fuel ratio, SFR, the ratio of the aerosol particles released from HEDD-impacted actual spent fuel to the aerosol particles produced from surrogate materials, measured under closely matched test conditions. In addition, we are measuring the amounts, nuclide content, size distribution of the released aerosol materials, and enhanced sorption of volatile fission product nuclides onto specific aerosol particle size fractions. These data are crucial for predicting radiological impacts. This document includes a thorough description of the test program, including the current, detailed test plan, concept and design, plus a description of all test components, and requirements for future components and related nuclear facility needs. It also serves as a program status report as of the end of FY 2003. All available test results, observations, and analyses - primarily for surrogate material Phasemore » 2 tests using cerium oxide sintered ceramic pellets are included. This spent fuel sabotage - aerosol test program is coordinated with the international Working Group for Sabotage Concerns of Transport and Storage Casks, WGSTSC, and supported by both the U.S. Department of Energy and Nuclear Regulatory Commission. « less
Optimal Charging of Lithium-ion Batteries Based on Model Predictive Control Considering Lithium Plating and Cell Temperature

Fast charging is crucial for applications of lithium-ion batteries in energy power systems. In this paper, a novel optimal charging strategy based on the model predictive control considering lithium plating and cell temperature is proposed. This method maximizes the charging speed while maintaining battery performance. It addresses constraints on the input current, the inner anode potential, and the temperature to prevent lithium plating and thermal safety issues. A thermal-coupled electrode equivalent circuit model is developed to observe the battery internal states with limited computation. A state observer based on the extended Kalman filter and a particle swarm optimizer is adopted in the MPC framework. The capability of this charging strategy is demonstrated via simulation and the result reveals that the battery can be charged to 86.6% of the full capacity in 17 minutes with accurate control of the anode potential and temperature. Compared with other charging protocols, the proposed method presents significant superiority. Besides, the optimal charging strategy is practical for onboard applications.
Flexural performance of functionally graded RC cross-section with steel and PP fibres

Many studies have been conducted on the behaviour of reinforced concrete (RC) to determine the effects of different fibre types on the mechanical properties of concrete. Tests such as flexural and shear tests are used to evaluate the behaviour of RC. Most previous studies have focused on reinforcement of the entire cross-section with one fibre type, but the use of double-type reinforcement is growing and the lower cost of polypropylene (PP) fibres can be a significant factor in the use of double-type reinforcement. Therefore, in this work, experimental tests and numerical simulations were carried out to study reinforcement of the cross-section with steel fibres, PP fibres or both, in two separate layers. Beams were reinforced using 0·5%, 1% and 2% fibre volume fractions of steel and PP fibres. The beams with a reinforced cross-section with one or two fibre types were evaluated under flexural loading. The results showed that reinforcement of the entire cross-section with steel fibres led to a higher load-c.
Deep Quantile Regression for QoT Inference and Confident Decision Making

This work examines deep quantile regression for quality-of-transmission (QoT) estimation and accurate decision making in optical networks. Quantile regression is applied to approximate QoT models capable of inferring QoT bounds for any future lightpath, according to a predefined level of certainty, for confident decision making, without the need to consider traditional margins at decision time. It is shown, that quantile regression automatically accounts for such margins, in a discriminative fashion, leading to a significant margin reduction and subsequently to more accurate inference of the QoT of unestablished lightpaths, when compared to the traditional margin-based decision approaches. Specifically, deep quantile regression for QoT estimation ensures that lightpaths with insufficient QoT will be accurately identified and rejected, while also identifying correctly lightpaths with sufficient QoT, making it a confident decision making tool for the planning of optical networks.
Spatial Meta-transcriptomes of human and murine intestines

We developed an analysis pipeline that can extract microbial sequences from Spatial Transcriptomic data and assign taxonomic labels to them, generating a spatial microbial abundance matrix in addition to the default host expression one, enabling simultaneous analysis of host expression and microbial distribution. We applied it on both human and murine intestinal datasets and validated the spatial microbial abundance information with alternative assays. Finally, we present a few biological insights that can be gained from this novel data. In summary, this proof of concept work demonstrated the feasibility of Spatial Meta-transcriptomic analysis, and pave the way for future experimental optimization.
Extend Mixed Models to Multi-layer Neural Networks for Genomic Prediction Including Intermediate Omics Data

With the growing amount and diversity of intermediate omics data complementary to genomics (e.g., DNA methylation, gene expression, and protein abundance), there is a need to develop methods to incorporate intermediate omics data into conventional genomic evaluation. The omics data helps decode the multiple layers of regulation from genotypes to phenotypes, thus forms a connected multi-layer network naturally. We developed a new method named NN-LMM to model the multiple layers of regulation from genotypes to intermediate omics features, then to phenotypes, by extending conventional linear mixed models (“LMM”) to multi-layer artificial neural networks (“NN”). NN-LMM incorporates intermediate omics features by adding middle layers between genotypes and phenotypes. Linear mixed models (e.g., pedigree-based BLUP, GBLUP, Bayesian Alphabet, single-step GBLUP, or single-step Bayesian Alphabet) can be used to sample marker effects or genetic values on intermediate omics features, and activation functions in neural networks are used to capture the nonlinear relationships between intermediate omics features and phenotypes. NN-LMM had significantly better prediction performance than the recently proposed single-step approach for genomic prediction with intermediate omics data. Compared to the single-step approach, NN-LMM can handle various patterns of missing omics measures, and allows nonlinear relationships between intermediate omics features and phenotypes. NN-LMM has been implemented in an open-source package called “JWAS”.
Age dependent changes in circulating Tfh cells influence the development of functional antibodies to malaria in children

T-follicular helper (Tfh) cells are key drivers of antibodies that protect from malaria. However, little is known regarding the host and parasite factors that influence Tfh and functional antibody development. Here, we use samples from a large cross-sectional study of children residing in an area of high malaria transmission in Uganda to characterize Tfh cells and functional antibodies to multiple parasites stages. We identify a dramatic re-distribution of the Tfh cell compartment with age that is independent of malaria exposure, with Th2-Tfh cells predominating in early childhood, while Th1-Tfh cell gradually increase to adult levels over the first decade of life. Functional antibody acquisition is age-dependent and hierarchical acquired based on parasite stage, with merozoite responses followed by sporozoite and gametocyte antibodies. Antibodies were boosted in children with current infection, and were higher in females. The children with the very highest antibody levels had increased Tfh cell activation and proliferation, consistent with a key role of Tfh cells in antibody development. Together, these data reveal a complex relationship between the circulating Tfh compartment, antibody development and protection from malaria.
Test-retest reproducibility of in vivo magnetization transfer ratio and saturation index in mice at 9.4 Tesla

Background Magnetization transfer saturation (MTsat) imaging was developed to reduce T1 dependence and improve specificity to myelin compared to the widely used MT ratio (MTR), while maintaining a feasible scan time. Knowledge of MTsat reproducibility is necessary to apply MTsat in preclinical neuroimaging. Purpose To assess the test-retest reproducibility of MTR and MTsat in the mouse brain at 9.4 T and calculate sample sizes required to detect various effect sizes. Study Type Prospective Animal Model C57Bl/6 Mouse Model (6 females and 6 males, aged 12 – 14 weeks) Field Strength/Sequence Magnetization Transfer Imaging at 9.4 T Assessment All mice were scanned at two timepoints (5 days apart). MTR and MTsat maps were analyzed using mean region-of-interest (ROI), and whole brain voxel-wise analysis. Statistical Tests Bland-Altman plots assessed biases between test and retest measurements. Test-retest reproducibility was evaluated via between and within-subject coefficients of variation (CV). Sample sizes required were calculated (at a 95 % significance level and power of 80 %), given various minimum detectable effect sizes, using both between and within-subject approaches. Results Bland-Altman plots showed negligible biases between test and retest sessions. ROI-based and voxel-wise CVs revealed high reproducibility for both MTR (ROI: CVs < 8 %) and MTsat (ROI: CVs < 10 %). With a sample size of 6, changes on the order of 15% can be detected in MTR and MTsat, both between and within subjects, while smaller changes (6 – 8 %) require sample sizes of 10 – 15 for MTR, and 15 – 20 for MTsat. Data Conclusion MTsat exhibits comparable reproducibility to MTR, while providing sensitivity to myelin with less T1 dependence than MTR. Our findings suggest both MTR and MTsat can detect moderate changes, common in pathologies, with feasible preclinical sample sizes.
Microbial Associations With Microscopic Colitis

BACKGROUND AND OBJECTIVE Microscopic colitis is a relatively common cause of chronic diarrhea and may be linked to luminal factors. Given the essential role of the microbiome in human gut health, analysis of microbiome changes associated with microscopic colitis could provide insights into the development of the disease. METHODS We enrolled patients who underwent colonoscopy for diarrhea. An experienced pathologist classified patients as having microscopic colitis (n=52) or controls (n=153). Research biopsies were taken from the ascending and descending colon, and the microbiome was characterized with Illumina sequencing. We analyzed the associations between microscopic colitis and microbiome with a series of increasingly complex models adjusted for a range of demographic and health factors. RESULTS We found that alpha-diversity was significantly lower in microscopic colitis cases compared to controls in the descending colon microbiome. In the descending colon, a series of models that adjusted for an increasing number of co-variates found taxa significantly associated with microscopic colitis, including Proteobacteria that was enriched in cases and Collinsella enriched in controls. While the alpha-diversity and taxa were not significantly associated with microscopic colitis in the ascending colon microbiome, the inference p-values based on ascending and descending microbiomes were highly correlated. CONCLUSION Our study demonstrates an altered microbiome in microscopic colitis cases compared to controls. Because both the cases and controls had diarrhea, we have identified candidate taxa that could be mechanistically responsible for the development of microscopic colitis independent of changes to the microbial community caused by diarrhea. Significance of this study What is already known about this subject? Microscopic colitis is a common cause of chronic diarrhea. The exact etiology of microscopic colitis is unknown, but the gut microbiome is considered to play an important role. Prior studies have reported microbial changes associated with microscopic colitis, but the results are not consistent. Prior studies have generally involved small numbers of patients, fecal samples, and comparison to healthy controls. What are the new findings? The microbiome was altered in microscopic colitis patients. Microscopic colitis was associated with lower alpha-diversity, increase of inflammation related taxa and decrease of Collinsella in the descending colon microbiome independent of diarrhea status. The changes of microbial features were consistent between ascending and descending colon microbiomes, but with smaller changes in the ascending colon microbiome. How might it impact on clinical practice in the foreseeable future? The altered microbial communities in patients with microscopic colitis suggest that the patients might benefit from prevention or treatment with live biotherapeutic products.
Performance of optically preamplified receivers with Fabry-Perot optical filters

A technique is presented for evaluating the probability of error for an optically preamplified receiver with a fiber Fabry-Perot optical filter of arbitrary bandwidth between the preamplifier and photodiode. The technique permits simultaneous consideration of the distortion due to modulator chirp and fiber dispersion, the optical filter and the baseband electrical filter. The optical filter is characterized by a Lorentzian passband response, and the quadrature noise processes due to the amplified spontaneous emission are represented by Karhunen-Loeve expansions. For an arbitrary optical filter bandwidth, the evaluation of the probability of error depends explicitly on the details of the Karhunen-Loeve expansion. The solution procedure is general and consequently can, in principle, be applied to other filter passband responses. The influence of the bandwidths of the optical and electrical filters on the performance of a 10 Gb/s system is assessed.
Advanced Optimal Design of the IoT Based University Campus Microgrid Considering Environmental Concerns and Demand Response

Rising energy prices and depletion of fossil fuel seriously affect the comfort of energy consumers. The integration of renewable energy resources with the legacy system is a striking solution to mitigate such problems, especially for developing countries. For this purpose, an IoT based university campus is taken as a case study, which comprised of dispatchable and non-dispatchable energy sources along with a battery bank. Different case studies have been carried out to the analytic assessment of the proposed system. The conventional campus can consume energy from the utility grid, while the prosumer microgrid can exchange the power with the utility grid considering the price-based demand response and environmeatal concern. For the analysis, advanced linear programming is used as a solution technique in MATLAB software. The obtained results using the demand response scheme reduced the energy cost by 20.5 % that shows the efficiency of the proposed model. Furthermore, the comparison with the existing work also shows the significance of the proposed linear campus model.
A comparison of compartment models for solids transport in flighted rotary dryers

Flighted rotary dryers are used extensively in a number of industries to control moisture content and temperature of particulate materials. In order to predict and control the operations of these units, it is necessary to understand the complicated solids transport and heat and mass transfer operations that occur. Most previous attempts to model the solids transport fail to characterise the dispersion seen in experimental measurements. Recently, a model has been developed using combinations of perfectly mixed reactors to reproduce the solids residence time distribution for a dryer based all geometric and physical analysis. While this model has shown promise in accurately fitting the experimental data, a geometric study of the local residence time distribution for falling particles within the dryer differs significantly from the CSTR residence time distribution used to represent the airborne mass. This paper presents a discussion of these concerns and proposes an alternative model for a rotary dryer using a combination of perfectly mixed reactors and plug flow reactors to better represent these aspects of a dryer. The two models are compared Gild shown to produce similar steady-state results.