Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigation into fatigue life of interface bond between asphalt concrete layers

ABSTRACT A proper interface bond between adjacent asphalt concrete layers ensures the layers to act monolithically to withstand traffic and thermal loading. The presence of a weak interface results in delamination, slippage and fatigue cracks thereby affects the pavement performance; hence, requires careful evaluation. The objectives of this investigation are three-fold. The first objective is to develop a test protocol to investigate the damage characteristics of the interface bond. The proposed test applies a 5 Hz cyclic shear load on a double-layered asphalt concrete specimen using a Modified Advanced Shear Tester at 23°C. The second objective is to determine the effect of interlayer shear modulus on the pavement response of typical pavement sections using numerical simulations. The interface material model property used in this study is a set of arbitrary values that lies within the typical range of interlayer shear modulus values observed during cyclic shear tests. The third objective is to propose a failure criterion for shear fatigue testing that is based on the critical tensile strain obtained during pavement response analysis. The test outcomes show that specimens with a tack coat at the interface exhibit a significant increase in shear fatigue life resistance compared to specimens with no tack coat.
Operation State Identification Method for Converter Transformers Based on Vibration Detection Technology and Deep Belief Network Optimization Algorithm

The converter transformer is a special power transformer that connects the converter bridge to the AC system in the HVDC transmission system. Due to the special structure of the converter transformer, it is necessary to test its operation state during its manufacture and processing to ensure the safety of its future connection to the grid. Numerous studies have shown that vibration signals in transformers can reflect their operating state. Therefore, in order to achieve an effective identification of the operation state of the converter transformer, this paper proposes a method for identifying the operation state of the converter transformer based on vibration detection technology and a deep belief network optimization algorithm. This paper firstly describes the background, principle and application of vibration detection technology, using vibration measurement systems with piezoelectric acceleration sensors, piezoelectric actuators and data acquisition instruments to collect vibration signals at different measurement points on the converter transformer in states of no-load and on-load. By analyzing the time-frequency characteristics of the vibration signals, fast Fourier transform (FFT), wavelet packet decomposition (WPD) and time domain indexes (TDI) are combined into a fused feature extraction method to extract the eigenvalues of the vibration signals, so that the fused eigenvectors of the signals can be constructed. Considering the excellent performance of deep learning in classification, the deep belief network is used to classify the signals’ eigenvectors. To effectively improve the network classification efficiency, the sparrow search algorithm was introduced to build a mathematical model based on the behavioral characteristics of sparrow populations and combine the model with a deep belief network, so as to achieve adaptive parameter optimization of the network and accurate classification of the signals’ eigenvectors. The proposed method is applied to a 500 kV converter transformer for experimental verification. The experimental results show that the fused feature extraction method was able to fully extract the features of the vibration signal, and the deep belief network optimization algorithm had higher classification accuracy and better operational efficiency, and was able to effectively achieve accurate identification of the operation state of the converter transformer. In addition, the method achieved a precision response to the detection results of the vibration sensors, contributing to future improvements in converter transformer manufacturing technology.
Phenotypic reactions of 53 soybean genotypes to infection with each of 16 isolates of Phakopsora pachyrhizi

ABSTRACT Soybean rust, caused by the fungal pathogen Phakopsora pachyrhizi, is an economically significant disease for soybean (Glycine max (L.) Merr. ) production throughout the world. Genes for resistance to P. pachyrhizi (Rpp) have been identified at multiple loci in the soybean genome, but each conditions resistance to specific P. pachyrhizi isolates rather than providing broad resistance to the species. Identifying soybean cultivars with previously unidentified Rpp genes, combined with efforts to breed soybean containing multiple Rpp genes, is a key part of the ongoing strategy to manage the disease and minimize its economic impact. Fifty-three soybean genotypes, possessing known and unknown Rpp genes, were challenged with 16 P. pachyrhizi isolates from a global collection. The observed phenotypic reaction patterns provided insight into the presence of Rpp genes. This study tentatively confirms the presence of Rpp1b, or an allele, in eight soybean lines, of previously unknown resistance gene, and in another three lines produced by targeted breeding. Examples of resistance gene pyramiding were identified in lines 4014–242-341 and 4018-4-1-1-212, which may contain both Rpp2 and Rpp4 genes and line RN6-313-362, which may contain both Rpp1b and Rpp4. Three possible sources of new resistance genes may exist within GC00138-29, PI 567145 C, and PI 605833. This study provides preliminary information on potential new sources of soybean-rust-resistance that may be used to focus specific future research and inform breeding programs.
Detecting Outlier Machine Instances Through Gaussian Mixture Variational Autoencoder With One Dimensional CNN

Today's large datacenters house a massive number of machines, each of which is being closely monitored with multivariate time series (e.g., CPU idle, memory utilization) to ensure service quality. Detecting outlier machine instances with multivariate time series is crucial for service management. However, it is a challenging task due to the multiple classes and various shapes, high dimensionality, and lack of labels of multivariate time series. In this article, we propose DOMI, a novel unsupervised model that combines Gaussian mixture VAE with 1D-CNN, to detect outlier machine instances. Its core idea is to capture the normal patterns of machine instances by learning their latent representations that consider the shape characteristics, reconstruct input data by the learned representations, and apply reconstruction probabilities to determine outliers. Moreover, DOMI interprets the detected outlier instance based on the reconstruction probability changes of univariate time series. Extensive experiments have been conducted on the dataset collected from 1821 machines with a 1.5-month-period, which are deployed in ByteDance, a top global content service provider. DOMI achieves the best F1-Score of 0.94 and AUC score of 0.99, significantly outperforming the best performing baseline method by 0.08 and 0.03, respectively. Moreover, its interpretation accuracy is up to 0.93.
A 0.061-mm² 1–11-GHz Noise-Canceling Low-Noise Amplifier Employing Active Feedforward With Simultaneous Current and Noise Reduction

This article proposes a novel wideband common-gate (CG) common-source (CS) low-noise amplifier (LNA) with active feedforward for simultaneous current and noise reduction. By employing an active feedforward stage in the main path, the current dissipation and the thermal noise are effectively suppressed, while the noise and distortion cancelation properties of CG-CS topology are preserved. Moreover, no extra noise is introduced since the additional <inline-formula> <tex-math notation="LaTeX">$g_{m}$ </tex-math></inline-formula>-boost amplifier follows the same noise-canceling (NC) principle as the CG amplifier, and its noise can be fully canceled at the output theoretically. Thus, the proposed LNA benefits from the <inline-formula> <tex-math notation="LaTeX">$g_{m}$ </tex-math></inline-formula>-boosting and NC technique simultaneously to obtain a good tradeoff between gain, noise figure (NF), and power consumption. Fabricated in standard 40-nm CMOS technology, the measured results show the proposed LNA exhibits a peak gain of 17 dB, NF of 3.5–5.5 dB from 1 to 11 GHz and an IIP3 of −2.8 dBm at 6 GHz. It consumes 9 mW from a 1.2-V supply and occupies a very compact die area of 0.061 mm<sup>2</sup>.
Increased Glenoid Index as a Risk Factor for Pediatric and Adolescent Anterior Glenohumeral Dislocation: An MRI-Based, Case-Control Study

Background: In adults, anterior glenohumeral instability has been associated with a tall and narrow glenoid morphology, assessed using the glenoid index (GI; glenoid height-to-width ratio) on magnetic resonance imaging (MRI). This morphological association has not been assessed in children and adolescents. Purpose/Hypothesis: To examine the association of GI and other MRI measurements of interest supported in studies on adults with anterior glenohumeral dislocation in patients aged ≤19 years. We hypothesized that these patients would have a significantly greater GI (relatively taller and narrower glenoid morphology) compared with healthy controls. Study Design: Case-control study; Level of evidence, 3. Methods: An institutional radiology database was queried over a 10-year period to identify patients aged ≤19 years who had been diagnosed with radiographically confirmed anterior shoulder dislocation and who underwent glenohumeral magnetic resonance arthrography as well as those without dislocation with normal shoulder arthrogram studies (controls). Patients with bony Bankart lesions were excluded. The following glenohumeral dimensions were measured on shoulder arthrogram: GI, glenoid version, coracohumeral interval, and rotator interval width/depth. Comparative analysis between the 2 groups was performed using the Student t test for each variable, followed by receiver operating characteristic (ROC) analysis to determine discriminative ability when statistically significant. Results: Overall, 55 participants (33 male and 22 female patients; mean age, 15.4 ± 2.1 years) were enrolled; 22 patients were in included in the dislocator group and 33 patients comprised the control group. The mean GI in the dislocator group was significantly greater than the control group (1.55 ± 0.14 vs. 1.38 ± 0.08; P < .001). ROC analysis revealed adequate discrimination of GI in predicting glenohumeral dislocation (area under the curve = 0.88). A GI ≥1.45 was 83% sensitive and 79% specific for predicting dislocation in the study cohort. Conclusion: Patients with anterior glenohumeral dislocation had increased GI (taller and narrower glenoid morphology) than controls. This useful MRI measurement may help identify patients at risk for primary or recurrent anterior glenohumeral instability events and may therefore help with guiding treatment and prevention.
Experimental investigation and thermodynamic evaluation of the C–O–Zr ternary system

The ZrCxOy oxycarbides are well-known relevant ceramic materials for ultra-high temperature applications. The intrinsic macroscopic properties of ZrCxOy being closely related to the C/O ratio, a detailed analysis of the C–O–Zr system has been undertaken experimentally in order to accurately determine the extent of the solid solution of oxygen within the oxycarbide phase at different synthesis temperatures. The obtained results were then used as diagrammatic data to extrapolate the ternary C–O–Zr phase equilibria diagram by the CALPHAD method, providing a predictive tool for the oxycarbide synthesis. The model proposed in the temperature range 1650–2000 °C is in fair agreement with results obtained in the literature. The chemical determination of the relative ratio between light elements (oxygen (O) and carbon (C)) being a difficult issue for most of the general applications, an accurate determination of the cell parameters of the different oxycarbide compositions has been performed to propose an abacus reporting the evolution of the cell parameter against the C/O amount. The chemical composition of the oxycarbide is shown to be determined with an accuracy better that a few percent. It is also shown that the evolution of the cell parameter is not linear, indicative of a possible change of the ionocovalent character of the chemical bonds with the composition of ZrCxOy.
Effects of Using High Resolution Satellite‐Based Inundation Time Series to Estimate Methane Fluxes From Forested Wetlands

A major source of uncertainty in the global methane budget arises from quantifying the area of wetlands and other inland waters. This study addresses how the dynamics of surface water extent in forested wetlands affect the calculation of methane emissions. We used fine resolution satellite imagery acquired at sub‐weekly intervals together with a semiempirical methane emissions model to estimate daily surface water extent and diffusive methane fluxes for a low‐relief wetland‐rich watershed. Comparisons of surface water model predictions to field measurements showed agreement with the magnitude of changes in water extent, including for wetlands with surface area less than 1,000 m2. Results of methane emission models showed that wetlands smaller than 1 hectare (10,000 m2) were responsible for a majority of emissions, and that considering dynamic inundation of forested wetlands resulted in 49%–62% lower emission totals compared to models using a single estimate for each wetland’s size.
Newly approved IV acetaminophen in Canada: Switching from oral to IV acetaminophen. Is IV worth the price difference? A systematic review.

Context The use of intravenous acetaminophen leads to meaningful health cost increases for paediatric institutions. Therefore, strict criteria for intravenous acetaminophen administration are needed. Objective To undertake a systematic review of available evidence comparing oral versus intravenous acetaminophen use in children. Method A systematic literature search was conducted on five databases. All prospective interventional studies comparing intravenous to oral acetaminophen in patients <18 years old were included. Data collection and analysis were done according to PRISMA guidelines. Results Among 6,417 retrieved abstracts, 29 full-text articles were assessed of which 3 were retained. (1) Pharmacokinetic: Oral bioavailability (72% with a high inter-individual variability) was reported in 47 stable patients in a paediatric intensive care unit. (2) Analgesia: In a double-blind randomized controlled trial of 45 children, no difference in analgesia was found between oral and intravenous administration after cleft palate repair. (3) Fever: In an open-label prospective observational study of 200 children, temperature decreased faster after intravenous than oral administration but was similar 4 hours later. Conclusions Available data are insufficient to guide clinicians with a rational choice of route of administration. Oral bioavailability should be studied in paediatric populations outside the intensive care unit. Despite the widespread use of intravenous acetaminophen, there is little evidence to suggest that it improves analgesia compared to the oral formulation. Similarly, fever weans faster but whether this translates into any meaningful clinical outcome is unknown. The lack of data plus the significantly higher costs of intravenous acetaminophen should motivate further research.
Characterization of Extracellular Vesicles Secreted in Lentiviral Producing HEK293SF Cell Cultures

Lentiviral vectors (LVs) are a powerful tool for gene and cell therapy and human embryonic kidney cells (HEK293) have been extensively used as a platform for production of these vectors. Like most cells and cellular tissues, HEK293 cells release extracellular vesicles (EVs). EVs released by cells share similar size, biophysical characteristics and even a biogenesis pathway with cell-produced enveloped viruses, making it a challenge to efficiently separate EVs from LVs. Thus, EVs co-purified with LVs during downstream processing, are considered “impurities” in the context of gene and cell therapy. A greater understanding of EVs co-purifying with LVs is needed to enable improved downstream processing. To that end, EVs from an inducible lentivirus producing cell line were studied under two conditions: non-induced and induced. EVs were identified in both conditions, with their presence confirmed by transmission electron microscopy and Western blot. EV cargos from each condition were then further characterized by a multi-omic approach. Nineteen proteins were identified by mass spectrometry as potential EV markers to differentiate EVs in LV preparations. Lipid composition of EV preparations before and after LV induction showed similar enrichment in phosphatidylserine. RNA cargos in EVs showed enrichment in transcripts involved in viral processes and binding functions. These findings provide insights on the product profile of lentiviral preparations and could support the development of improved separation strategies aimed at removing co-produced EVs.
Microstructure and Mechanical Properties of Novel Quasibinary Al-Cu-Yb and Al-Cu-Gd Alloys

Microstructure of Al-Cu-Yb and Al-Cu-Gd alloys at casting, hot-rolled -cold-rolled and annealed state were observed; the effect of annealing on the microstructure was studied, as were the mechanical properties and forming properties of the alloys, and the mechanism of action was explored. Analysis of the solidification process showed that the primary Al solidification is followed by the eutectic reaction. The second Al8Cu4Yb and Al8Cu4Gd phases play an important role as recrystallization inhibitor. The Al3Yb or (Al, Cu)17Yb2 phase inclusions are present in the Al-Cu-Yb alloy at the boundary between the eutectic and aluminum dendrites. The recrystallization starting temperature of the alloys is in the range of 250–350 °C after rolling with previous quenching at 590 and 605 °C for Al-Cu-Yb and Al-Cu-Gd, respectively. The hardness and tensile properties of Al-Cu-Yb and Al-Cu-Gd as-rolled alloys are reduced by increasing the annealing temperature and time. The as-rolled alloys have high mechanical properties: YS = 303 MPa, UTS = 327 MPa and El. = 3.2% for Al-Cu-Yb alloy, while YS = 290 MPa, UTS = 315 MPa and El. = 2.1% for Al-Cu-Gd alloy.
A comprehensive quality improvement model: integrating internal and external information

In a highly competitive market, service quality gap, competitor performance and objective assessment of service quality are the key considerations for identifying the critical deficiencies of service quality. This study aims to develop a Competitive Importance-Performance and Gap Analysis (CIPGA) through function conversion, which is based on the relative importance, relative performance and competitive quality gap of each service attribute. The CIPGA model has six strategic patterns, including Competitive advantage, Head-to-Head Competition, Potential Disadvantage, Potential Opportunity, Negative Head-to-Head Competition, and Fatal Crisis. This study takes two major wedding banquet halls in Taiwan as a case study to verify the model. It explores the service quality of the benchmark company compared to the major competitor by setting Wedding Banquet Hall A as the benchmark company and Wedding Banquet Hall B as the major competitor. The results show, for Wedding Banquet Hall A, nine service attributes belong to Potential Opportunity, three service attributes belong to Negative Head-to-Head Competition and three service attributes belong to Fatal Crisis. Their management implications are discussed in detail in the text. This study expects that service quality can be evaluated more specifically and effectively by the CIPGA model, to improve service quality in a highly competitive market.
Jazz Bass Transcription Using a U-Net Architecture

In this paper, we adapt a recently proposed U-net deep neural network architecture from melody to bass transcription. We investigate pitch shifting and random equalization as data augmentation techniques. In a parameter importance study, we study the influence of the skip connection strategy between the encoder and decoder layers, the data augmentation strategy, as well as of the overall model capacity on the system’s performance. Using a training set that covers various music genres and a validation set that includes jazz ensemble recordings, we obtain the best transcription performance for a downscaled version of the reference algorithm combined with skip connections that transfer intermediate activations between the encoder and decoder. The U-net based method outperforms previous knowledge-driven and data-driven bass transcription algorithms by around five percentage points in overall accuracy. In addition to a pitch estimation improvement, the voicing estimation performance is clearly enhanced.
A distributionally robust optimization approach for coordinating clinical and surgical appointments

Abstract In this article, we address a two-stage scheduling problem that requires coordination between clinical and surgical appointments for specialized surgeries. First, patients have a clinical appointment with a surgeon to determine whether they are an appropriate candidate for the surgical procedure. Subsequently, if the decision to pursue the surgery is made the patient undergoes the procedure on a later date. However, the scheduling process aims to book both the clinical and surgical appointments for a patient at the time of the initial appointment request. Two sources of uncertainty make this scheduling process challenging: (i) the patient may or may not need surgery after the clinical appointment and (ii) the surgery duration for each patient and procedure is unknown. We present a Distributionally Robust Optimization (DRO) approach for coordinating clinical and surgical appointments under these uncertainties. A case study of the Transcatheter Aortic Valve Replacement procedure at Mayo Clinic, Rochester, MN is presented. Numerical results include comparisons with the current practice and four heuristic scheduling policies from the literature. Results show that the DRO-based scheduling policies lead to lower total surgeon idle-time and overtime per day. The proposed policies also restrict the under and over utilization of clinical capacity.
Cognitive Reserve and language processing demand in healthy older adults

ABSTRACT Cognitive Reserve (CR) refers to cognitive resources acquired through experiences along the lifespan that allow for flexibility in coping with neurocognitive changes. Investigating the role of CR measures across well-established psycholinguistic features can provide new insight into how CR interplays with cognition. Sixty-five Italian older adults performed a Lexical Decision, a Semantic Matching and a Sentence Reading task. We observed the effects of CR on reaction times and accuracy while varying lexical frequency (high vs low) and lexical semantics (concrete vs abstract) and on reading times of sentences with either syntactic or semantic violations. In the Lexical Decision and Semantic Matching tasks, CR played a role in processing low frequency and abstract words. In the Sentence Reading Task, CR influenced reading times, particularly in the presence of syntactic violations. CR predicts cognitive performance in tasks that require language demands at different levels.