Miracle-dz/UniFAR-FTUs huggingface dataset:
Modelling disc-brake squeal in a multi-body-dynamicsenvironment

Brake squeal is known to be an issue at disc brakes since their introduction, but a complete understanding of the problem is still missing. Experiments show that transversal vibrations of the brake disc are responsible for squeal. In literature, different sources of the instabilities that lead to squeal are discussed. In this thesis self-excited vibrations due to the follower-force characteristic of the friction forces are investigated. Different analytical minimal models for disc-brake squeal are introduced, and two are discussed in detail. One model uses a rigid disc with friction contact, the second one uses a flexible disc with two eigenmodes of the disc. Current numerical simulations are based on full finite-element models of the brake system. This approach has the disadvantage of a high computational effort and only gives limited information about the squeal process itself. In this thesis a rigidand a flexible-discmodel aremodelled and analysed in themulti-body-system program SIMPACK.The advantage of this approach is the computational efficiency and the chance to expand the model easily in order to represent more complex systems. Finally, the potential of the combination of multi-body-system dynamics and acoustic finite-element analysis is demonstrated. In order to model the flexible disk in SIMPACK, a finite-element model of the has been preprocessed for the multi-body-system dynamics analysis. The needed mechanical mathematical foundations are explained.
The Association Between Admission Heart Failure and In-Hospital Outcomes in ST-Elevation Myocardial Infarction Patients Undergoing Primary Percutaneous Coronary Intervention

Background The Global Registry of Acute Coronary Events (GRACE) study showed that admission HF is associated with longer hospital stay and higher mortality in ST-elevation myocardial infarction (STEMI) patients. No data are available on the effect of heart failure (HF) on the length of cardiac care unit (CCU) stay and in-hospital major adverse cardiac events (MACEs). The link between the severity of HF and the in-hospital prognosis is not established. Therefore, we aimed to investigate the unstudied outcomes in HF patients as well as to compare the outcomes across the spectrum of HF presentations. Methods We studied 210 STEMI patients presenting to a single primary percutaneous coronary intervention (PPCI) center in a retrospective cohort pattern. We excluded those who received fibrinolysis, those who had chest pain for more than 24 h and those with previous stents and presenting with stent thrombosis. All the procedures followed the ethical standards of Alexandria University and the Helsinki Declaration. Results STEMI patients with HF had significantly longer CCU stay (mean value of 3.6 vs. 2.87 days, P = 0.009), higher in-hospital MACE (55% vs. 4.7%, P < 0.001) and higher mortality (15% vs. 0.53%, P < 0.001). Multivariate logistic regression analysis revealed that HF is an independent predictor of in-hospital mortality (odds ratio (OR) = 9.11, 95% confidence interval (CI): 1.66 - 49.9, P = 0.01). The patients with severe HF on admission (Killip III and IV) tended to stay longer in the CCU (4.13 ± 1.89 days vs. 3.25 ± 1.54 days, P = 0.069) and the hospital (5.88 ± 3.09 vs. 4.42 ± 2.47 days, P = 0.077), compared to those with mild HF (Killip II). There was a tendency for a higher incidence of in-hospital MACE (75% vs. 33%, P = 0.068) and mortality (16.7% vs. 12.5%, P = 0.798) in the former group compared to the latter. The differences among HF subgroups did not reach the point of statistical significance though. Conclusions The presence of HF on the admission of STEMI patients undergoing PPCI is associated with longer CCU stay, higher in-hospital MACE and mortality.
Learning-Based Resource Allocation for Ultra-Reliable V2X Networks With Partial CSI

In this paper, we study the resource allocation in high mobility vehicle-to-everything (V2X) networks with only slowly varying large-scale channel parameters. For satisfying the diversity requirements of different types of links, i.e., low delay for vehicle-to-infrastructure (V2I) connections and ultra-reliability for vehicle-to-vehicle (V2V) connections, we formulate a joint power, spectrum and vehicle local computing ratio allocation problem to minimize the delay of V2I links whilst satisfying the V2V reliability constraint. For solving the formulated problem, a Feasible Region Transformation Method is firstly developed to convert the probabilistic V2V reliability requirement into a computable constraint. In addition, a Robust Signal to Interference Plus Noise Ratio (SINR) Modified Method is proposed to give the computable expression for the V2I throughput. Then, a parallel Deep Neural Network (DNN) framework is designed for the resource allocation in V2X networks, where one is the transmit power control unit and the other is the local computing ratio allocation unit. After that, a Feedback-oriented Learning Method is proposed to train the parallel DNN-based resource allocation framework, in which the output of DNN is used as feedback to dynamically revise the training loss function along with the training process. Afterwards, the Hungarian method is employed to obtain the optimal spectrum matching. Finally, we conduct the simulations to show that the proposed learning-based algorithm has better performance compared with other general algorithms.
Global Identification of White Lupin lncRNAs Reveals Their Role in Cluster Roots under Phosphorus Deficiency

Phosphorus (P) deficiency heterogeneously affected plant nutritional status and physiological performance, ultimately leading to a severe yield reduction. A few putative long non-coding RNAs (lncRNAs) responding to P-starvation in the model crops Arabidopsis thaliana and Oryza sativa have been characterized. White lupin (Lupinus albus) is of prime importance, and is a legume with increasing agronomic value as a protein crop as it exhibits extreme tolerance to nutrient deficiency, particularly P deficiency. Despite its adapted nature to P deficiency, nothing is known about low P-induced lncRNAs in white lupin roots. To address this issue, we identified 39,840 mRNA and 2028 lncRNAs in the eight developmental stages of white lupin root (S0–S7 and lateral root, LR) grown under P deficiency. From these 2028 lncRNAs, 1564 were intergenic and 464 natural antisense intergenic transcript (NAT) lncRNAs. We further predicted six potential targets of miRNAs with twelve lncRNAs, which may regulate P-deficiency-related processes. Moreover, the weighted gene co-expression network analysis (WGCNA) revealed seven modules that were correlated with the expression pattern of lncRNAs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed 606 GO terms and 27 different pathways including signal transduction, energy synthesis, detoxification, and Pi transport. In addition, we screened 13 putative lncRNAs that showed a distinct expression pattern in each root, indicating their role in the P deficiency regulatory network. Therefore, white lupin may be a reference legume to characterize P-deficiency-responsive novel lncRNAs, which would highlight the role of lncRNAs in the regulation of plant responses to P deficiency.
A High-Throughput Full-Dataflow MobileNetv2 Accelerator on Edge FPGA

FPGA accelerators for lightweight neural networks, such as MobileNetv2, are of great need in edge computing applications with high throughput requirements. Dataflow architecture has been considered a promising approach to optimize throughput since the intermediate feature map transfers can be significantly saved. However, previous MobileNetv2 accelerators only achieved a partial-dataflow architecture, and just one-third of the feature map transfers can be saved. To solve this issue, we propose a scheme to achieve a full-dataflow MobileNetv2 accelerator on FPGA. The scheme contains four techniques. First, we improve the full-integer quantization for easier deployment on hardware. Second, we propose tunable activation weight imbalance transfer for less quantization accuracy loss. Third, we present several highly optimized accelerator components whose parallelism can be flexibly adjusted and implement residual connection with deeper FIFO so that the requirements of the full-dataflow architecture can be fully met. Finally, we present a computing resource allocation strategy to balance the latency of each layer, and a memory resource allocation strategy to effectively use the on-chip memory. Compared to the state-of-the-art, experimental results show that the accelerator achieves 1910 FPS with $1.8\times $ speedup when implemented on the Xilinx ZCU102 FPGA. In addition, it reaches 72.98% Top-1 accuracy with 8-bit integer quantization that outperforms all the other MobileNetv2 accelerators.
Supporting after action review in simulator mission training: Co-creating visualization concepts for training of fast-jet fighter pilots

This article presents the design and evaluation of visualization concepts supporting After Action Review (AAR) in simulator mission training of fast-jet fighter pilots. The visualization concepts were designed based on three key characteristics of representations: re-representation, graphical constraining, and computational offloading. The visualization concepts represent combined parameters of missile launch and threat range, the former meant to elicit discussions about the prerequisites for launching missiles, and the latter to present details of what threats a certain aircraft is facing at a specific moment. The visualization concepts were designed to: 1) perceptually and cognitively offload mental workload from participants in support of determining relevant situations to discuss; 2) re-represent parameters in a format that facilitates reading-off of crucial information; and 3) graphically constrain plausible interpretations. Through a series of workshop iterations, two visualization concepts were developed and evaluated with 11 pilots and instructors. All pilots were unanimous in their opinion that the visualization concepts should be implemented as part of the AAR. Offloading, in terms of finding interesting events in the dynamic and unique training sessions, was the most important guiding concept, while re-representation and graphical constraining enabled a more structured and grounded collaboration during the AAR.
Small-Signal Angle Stability-Oriented False Data Injection Cyber-Attacks on Power Systems

The small-signal angle stability (SSAS) of a power system is determined by the property of operation points. The widely applied false data injection (FDI) cyber-attack, however, is able to stealthily mislead the optimal power flow (OPF) and thus compromise operation points, leading to damages to the SSAS margin. To provide insights for cyber defenders, this paper proposes and investigates a stealthy SSAS-oriented FDI cyber-attack focusing on two attacking purposes, i.e., the SSAS margin and operation cost, with higher priority on the former one. First, this paper establishes a novel bi-level model with an implicit SSAS constraint based on a structure preserving model to compromise operation points. Then, for the SSAS interarea mode in a typical two-area system, this paper formulates closed-form expressions of how the SSAS margin and operation cost behave with respect to stealthy injections. By comparison, for the SSAS local mode in general power systems, this paper proposes a moving target cyber-attack-based hierarchical solution algorithm. Simulation results on a two-area system, a Kundur 11 bus system, and a modified IEEE 14 bus system demonstrate the significant damaging effects of the proposed SSAS-oriented FDI cyber-attack and the conflict between the two attacking purposes.
The Field Experiments on the HTO Washout from the Atmosphere

Abstract The results of the field experiments of HTO washout with rainfall in the vicinity of the HT and HTO emission source are presented. The objective of the current study was to obtain the direct experimental data on the impact of raindrops characteristics (rate and spectrum of the drops) on HTO washout from the atmosphere. The results can be applied in for the development and validation of various models of washout.
Liposomal Mineral Absorption: A Randomized Crossover Trial

Multivitamin/mineral (MVM) supplements are one of the most popular dietary supplement categories. The purpose of this analysis was to determine if a novel liposomal delivery mechanism improves mineral absorption from an MVM product. In a randomized crossover trial, 25 healthy participants (12 females, 13 males) completed two testing sessions in which blood samples were collected at baseline and 2, 4, and 6 h following the ingestion of either a liposomal MVM or a nutrient-matched standard MVM. Analysis of MVM products indicated an elemental iron content of 9.4 and 10.1 mg (~50% U.S. FDA Daily Value) and an elemental magnesium content of 22.0 and 23.3 mg (~5% U.S. FDA Daily Value) in the liposomal and standard MVM products, respectively. Blood samples were analyzed for concentrations of iron and magnesium using colorimetric assays. Changes in mineral concentrations were analyzed using linear mixed models, and pharmacokinetic parameters were compared between conditions. For iron, statistically significant condition × time interactions were observed for percent change from baseline (p = 0.002), rank of percent change from baseline (p = 0.01), and raw concentrations (p = 0.02). Follow-up testing indicated that the liposomal condition exhibited larger changes from baseline than the standard MVM condition at 4 (p = 0.0001; +14.3 ± 18.5% vs. −6.0 ± 13.1%) and 6 h (p = 0.0002; +1.0 ± 20.9% vs. −21.0 ± 15.3%) following MVM ingestion. These changes were further supported by a 50% greater mean incremental area under the curve in the liposomal condition (33.2 ± 30.9 vs. 19.8 ± 19.8 mcg/dL × 6 h; p = 0.02, Cohen’s d effect size = 0.52). In contrast, no differential effects for magnesium absorption were observed. In conclusion, iron absorption from an MVM product is enhanced by a liposomal delivery mechanism.
Applying Multiple Functional Connectivity Features in GCN for EEG-Based Human Identification

EEG-based human identification has gained a wide range of attention due to the further increase in demand for security. How to improve the accuracy of the human identification system is an issue worthy of attention. Using more features in the human identification system is a potential solution. However, too many features may cause overfitting, resulting in the decline of system accuracy. In this work, the graph convolutional neural network (GCN) was adopted for classification. Multiple features were combined and utilized as the structure matrix of the GCN. Because of the constant signal matrix, the training parameters would not increase as the structure matrix grows. We evaluated the classification accuracy on a classic public dataset. The results showed that utilizing multiple features of functional connectivity (FC) can improve the accuracy of the identity authentication system, the best results of which are at 98.56%. In addition, our methods showed less sensitivity to channel reduction. The method proposed in this paper combines different FCs and reaches high classification accuracy for unpreprocessed data, which inspires reducing the system cost in the actual human identification system.
Automatic Temperature Monitoring/Logging System with Computer USB Interface

Temperature is one of the most measure weather parameter. In most cases it is sufficient to measure and read out the instantaneous temperature of an environment. For useful analysis and weather prediction however, it is important to see the trend and variation of such measure temperature over a long period of time. This project will involve the design and fabrication of a microcontroller based temperature monitoring and logging system. The microcontroller will acquire digital temperature values from a precision temperature sensor, whose value is then processed and send to computer software through the USB port for logging and future analysis of the measure data. This system can be upgraded to form a full weather monitoring Equipment.
360°-VIDEO REFLECTION IN TEACHER EDUCATION: A CASE STUDY

360°(degree-)-videos inherit interesting potentials for teaching competence development. Reflecting on personal teaching performance from multiple perspectives potentially increases the depth in situated reflection and provides new learning insights for pre-service teachers. In this light, this paper describes a case study conducted at the University of St.Gallen where 360°-videos were used for reflection on personal performance of pre-service teachers in order to clarify, whether they add value to reflective observations compared to classical video recordings. Key findings are that (I): 360°-videos can add value to reflection processes in teacher education when combined with feedback and situated learning processes in a learning design and (II): 360°-videos offer advantages to follow teacher-student-interactions and to reflect upon personal teaching performance from multiple perspectives.
Benchmarking Flexible Electric Loads Scheduling Algorithms

: Due to increasing numbers of intermittent and distributed generators in power systems, there is an increasing need for demand responses to maintain the balance between electricity generation and use at all times. For example, the electriﬁcation of transportation signiﬁcantly adds to the amount of ﬂexible electricity demand. Several methods have been developed to schedule such ﬂexible energy consumption. However, an objective way of comparing these methods is lacking, especially when decisions are made based on incomplete information which is repeatedly updated. This paper presents a new benchmarking framework designed to bridge this gap. Surveys that classify ﬂexibility planning algorithms were an input to deﬁne this benchmarking standard. The benchmarking framework can be used for different objectives and under diverse conditions faced by electricity production stakeholders interested in ﬂexibility scheduling algorithms. Our contribution was implemented in a software toolbox providing a simulation environment that captures the evolu-tion of look-ahead information, which enables comparing online planning and scheduling algorithms. This toolbox includes seven planning algorithms. This paper includes two case studies measuring the performances of these algorithms under uncertain market conditions. These case studies illustrate the importance of online decision making, the inﬂuence of data quality on the performance of the algorithms, the beneﬁt of using robust and stochastic programming approaches, and the necessity of trustworthy benchmarking.
Consolidation centers in city logistics: A cooperative approach based on the location routing problem

Article history: Received December 13 2018 Received in Revised Format January 6 2019 Accepted January 9 2019 Available online January 9 2019 In the context of city logistics, freight transportation is one of the prominent causes of traffic congestion, high levels of pollution, and safety concerns. To decrease the negative impact of these issues, different methods have been traditionally implemented. On the one hand, the location of urban consolidation Centers (UCCs) near a city can be used to consolidate freight delivery services. Therefore, the number of trucks moving in urban areas can be reduced. On the other hand, Horizontal Cooperation can also help to reduce environmental impact while increasing service level. This paper combines both strategies, that is, we deal with the location of UCCs and, simultaneously, we analyze different scenarios where the players of different supply chain processes exhibit various levels of cooperation. Thus, different levels of cooperations regarding routing and UCCs-location decisions are considered in the following scenarios: (a) non-cooperative case, in which all decisions are decentralized (i.e., each enterprise solves its own vehicle routing problem); (b) low-cooperative case, where depot capacities are shared but the customers are still being served by each company's fleet of vehicles; (c) semicooperative case, based on centralized route planning decisions (i.e. facilities and fleets are shared among participating enterprises); and (d) fully cooperative scenario, where the routing plans and facility-location decisions are taken by consensus amongst all the participants. In order to estimate the benefits of both strategies, we propose a flexible metaheuristic algorithm to deal with the combined location and routing problem under the different cooperative scenarios. Our results show impressive benefits of the proposed approach. © 2019 by the authors; licensee Growing Science, Canada
Are serum leptin correlations influenced by fat placement?

In their paper on serum lepOO concentrations in Jamaican men and women, Bennett et al (1) maintain that "hip circumference is a proxy measure of peripheral fat" and that "the larger hips of women may contribute to the sex difference in serum leptin concentration. " However, one may question whether hip fat is in fact being measured, whether it is actually peripheral, and whether outer fat at anyone site truly accounts for the sex difference in serum lepOO concentrations. First, and by their own description of the circumference in question, taken "at the point of maximum extension of the bUllocks," it is gluteal fat and trochanteric fat that the measuring tape encompasses. Hip fat, ie, fat over the iliac crests, is well above the body section described. Moreover, and despite the reference to the study by Krotkiewski et al (2), the gluteal and trochanteric regions are scarcely peripheral to the trunk. The arms and legs properly constitute the peripheries in anatomic usage. (peripheral bone mass is now measured in the calcaneus.) In general, and except for the top quintile of the socioeconomic continuum, women do have more outer fat at nearly every site that is accessible to radiography or pinch-caliper measurement (3). A major exception to this rule is scalp fat, which is systematically thicker in adult males (4). Thus, the sex difference in outer-fat thickness is not unique to the gluteal and trochanteric regions, but applies equally to the legs, arms, thighs, neck, and buccal fat-pads. Accordingly, one may question whether gluteal and trochanteric fat configurations uniquely determine serum lepOO concentrations, even in steatopygic women. Yes, I agree with Bennell et al that body fat mass and percentage fat are substantially correlated with serum leptin concentrations (r = 0.58-0.73). No, I do not find it remarkable that serum leptin correlations, corrected for fat mass, were the same for lean and obese individuals. And, I am not surprised that in individuals with a large body mass index or in those otherwise partitioned, fat mass no longer correlates well with serum leptin, given the skewness of some of the part distributions, and sample sizes (for males) as low as 20 or even 7.