Miracle-dz/UniFAR-FTUs huggingface dataset:
Computational Modelling of Concrete Time-Dependent Mechanics and Its Application to Large-Scale Structure Analysis

The goal of the proposed work is to systematically study the time-dependent mechanics of concrete with a focus on concrete creep and its effect on prestressed concrete bridges, which are creep-sensitive. With increasing demands for sustainable construction, a longer lifespan, i.e., over 100 years, is now generally expected for critical bridges in structural design. To ensure the safety and serviceability of prestressed concrete bridges throughout this prolonged lifespan, there is a call for deeper understanding of the concrete time-dependent mechanics and its effects on the structural performance of prestressed concrete bridges. The primary aim of this study is to build a numerical framework to estimate the time-dependent performance of prestressed concrete bridges based on the development of concrete creep and its coupling with other physical and chemical processes. The established framework will be used to capture the correlation between the long-term asymptotes of deformation curves, early age measurements, and distinctive concrete creep models. Based on the identified correlation and in-situ measurements, a suitable creep model can be identified and calibrated for the bridge under investigation. Then the framework is extended to take into account the effect of scatter in concrete creep on the deformation asymptote. Statistical analyses based on the Latin hypercube sampling scheme are employed to investigate the effectiveness and robustness of the established correlation. For bridges carrying heavy traffic flows, the intertwined effects of concrete static creep, cyclic creep, softening and cracking are recommended to be incorporated to enhance the predictive capacity of the proposed framework. To meet this need, a unified concrete constitutive model is formulated and then is integrated in the 3D rate-type formulation for full-scale creep structural analysis. Finally, to remedy the inadequacy resulting from the phenomenological formulas in concrete creep modeling, a multi-scale methodology residing at the meso-scale of concrete is developed. A representative volume element (RVE) of concrete is numerically generated for the multi-scale analysis and the macros-scale time-dependent behavior of concrete is approximated by a proper computational homogenization scheme.
Development of nociceptive synaptic inputs to the neonatal rat dorsal horn: glutamate release by capsaicin and menthol

To study the postnatal development of nociceptive synaptic inputs in the superficial dorsal horn of the neonatal rat spinal cord, we examined the effect of capsaicin and menthol on glutamatergic mEPSCs in postnatal day (P) 0–1, P5–6 and P9–11 slices of spinal cord. Capsaicin (100 nm to 2 μm) increased the mEPSC frequency in a concentration‐dependent manner at all ages tested, with a significant enhancement of the effect between P5 and P10. This effect was sensitive to vanilloid receptor (VR) antagonists. The elevation in mEPSC frequency occurred at concentrations of capsaicin (100 nm) that did not alter the distribution of mEPSC amplitudes and was abolished by a dorsal rhizotomy, demonstrating that capsaicin acts via presynaptic VR1 receptors localized on primary afferents. Menthol significantly increased the mEPSC frequency with a similar developmental pattern to capsaicin without consistently affecting mEPSC amplitude. The increase in mEPSC frequency following capsaicin did not depend on transmembrane calcium influx since it persisted in zero [Ca2+]o. The facilitation of spontaneous glutamate release by capsaicin was sufficient to evoke action potentials in neonatal dorsal horn neurons but was accompanied by a block of EPSCs evoked by electrical stimulation of the dorsal root. These results indicate that VR1‐expressing nociceptive primary afferents form functional synaptic connections in the superficial dorsal horn from birth and that activation of the VR1 receptor increases spontaneous glutamate release via an undetermined mechanism. In addition, the data suggest that immature primary afferents express functional menthol receptors that are capable of modulating transmitter release. These results have important functional implications for infant pain processing.
Thermal degradation of InGaN/GaN quantum wells in blue laser diode structure during the epitaxial growth

True blue nitride laser diodes (LDs) are one of the key challenges for epitaxy of nitrides due to the variety of its potential applications. The growth of high temperature p-type layers may cause thermal degradation of the InGaN-based multiple quantum wells (MQWs) active region because of the annealing effect, since thick p-AlGaN layers were introduced as upper optical cladding layer in the LDs. The degradation was found in blue LDs grown on both Si and sapphire substrate. In the degraded LD wafer samples, “Dark” non-radiative MQWs regions were observed by microscopic photoluminescence. Formation of metallic indium precipitates and voids in these regions were confirmed by transmission electron microscope. The thermal degradation is attributed to the decomposition of indium-rich InGaN materials in the MQWs. The indium-rich InGaN materials were supposed to be accumulated at dislocation related V-shaped pits according to the surface morphology by atomic force microscope. To obtain high quality InGaN-based MQWs, one of the four methods can be introduced to eliminate the degradation. A lower thermal budget can suppress the decomposition of indium-rich InGaN clusters by a lower p-cladding layer growth temperature. The use of low threading dislocation density substrates results in low density indium-rich InGaN clusters. The introducing of H2 carrier gas during the quantum barriers growth or a 2-step growth scheme with a higher quantum barrier growth temperature etches off the indium-rich InGaN clusters. The suppression of the thermal degradation in the MQWs makes it possible for lasing of blue laser diode directly grown on Si.
Vascular endothelial growth factor level as a prognostic determinant of small cell lung cancer in Japanese patients.

OBJECTIVE To clarify the clinical significance of vascular endothelial growth factor (VEGF) in Japanese patients with small cell lung cancer (SCLC). MATERIALS AND METHODS We measured serum VEGF levels using an enzyme-linked immunosorbent assay in 45 patients with SCLC before treatment and in 38 patients with benign pulmonary disease and in 32 healthy subjects (71 non-malignant subjects). VEGF immunostaining was performed in tissue biopsies obtained from 23 SCLC patients during bronchoscopic examination. RESULTS Median serum VEGF level was 332 pg/ml in patients with SCLC and 160 pg/ml in non-malignant subjects, respectively. The 95% cut-off level to exclude non-malignant subjects was 500 pg/ml. An elevated VEGF level (>500 pg/ml) was found more frequently in patients with extensive disease of SCLC than in those with the limited disease (p<0.01). A significant positive correlation was found between the serum VEGF level and platelet count in SCLC patients (r=0.389; p=0.0083). Serum VEGF level also correlated with serum lactate dehydrogenase in SCLC patients (r=0.381; p=0.0098). However, it did not correlate with serum neuron-specific enolase and pro-gastrin-releasing peptide level. Patients with the elevated VEGF levels had significantly shorter progression-free time than those with the normal VEGF levels (p<0.05). Patients with the elevated VEGF levels had a significantly shorter overall survival time than those with the normal VEGF levels in univariate survival analysis (p<0.05). Further, the elevated VEGF level remained as a significant determinant of poor survival in multivariate analysis (p<0.01). Serum VEGF level was significantly higher in patients with positive VEGF protein immunoreactivity in tumor tissue in SCLC. CONCLUSION Elevated serum VEGF levels were associated with poor outcome in SCLC.
Transition from pre-diabetes to diabetes and predictors of risk in Mexican-Americans

Background No studies have examined risk factors for the transition from pre-diabetes to diabetes in populations with widespread obesity and diabetes. We determined proximal changes and factors affecting the transition among Mexican-Americans with pre-diabetes. Methods Participants with pre-diabetes (n=285) were recruited from our randomly sampled population-based Cameron County Hispanic Cohort. These participants were followed for an average of 27 months with repeat examination every 3 to 4 months. Metabolic health was defined as having less than 2 metabolic abnormalities (e.g., hypertension, elevated low-density lipoprotein, etc). Diabetes was identified as fasting blood glucose ≥126 mg/dL, glycated hemoglobin ≥6.5% and/or on hypoglycemic medication. Results Ninety-six of 285 (33.7%) participants transitioned to overt diabetes. The increased risk of diabetes in the metabolically unhealthy varying with follow-up time was 81% (adjusted odds ratio [OR]: 1.81; 95% CI: 1.09–3.02). The risk of diabetes increased 8% for each kg/m2 of increase in body mass index (BMI, OR: 1.08; 95% CI: 1.05–1.11) independent of covariates. Transition to diabetes was accompanied by a mean increase in BMI of 0.28 kg/m2, and deterioration in metabolic health of 9% (OR: 1.09; 95% CI: 1.003–1.18) compared with those who did not transition. Conclusions Deteriorating metabolic health and/or increasing BMI significantly raises the risk of transitioning from pre-diabetes to diabetes. Transition itself was accompanied by further increase in BMI and deterioration in metabolic health. These data underline the importance of improving metabolic health and avoiding weight gain in pre-diabetes as simple but clear diabetes prevention targets, and emphasize the importance of lifestyle management.
The Association of Polymorphisms in Leptin/Leptin Receptor Genes and Ghrelin/Ghrelin Receptor Genes With Overweight/Obesity and the Related Metabolic Disturbances: A Review

Context: Leptin and ghrelin are two important appetite and energy balance-regulating peptides. Common polymorphisms in the genes coding these peptides and their related receptors are shown to be associated with body weight, different markers of obesity and metabolic abnormalities. This review article aims to investigate the association of common polymorphisms of these genes with overweight/obesity and the metabolic disturbances related to it. Evidence Acquisition: The keywords leptin, ghrelin, polymorphism, single-nucleotide polymorphism (SNP), obesity, overweight, Body Mass Index, metabolic syndrome, and type 2 diabetes mellitus (T2DM) (MeSH headings) were used to search in the following databases: Pubmed, Sciencedirect (Elsevier), and Google scholar. Overall, 24 case-control studies, relevant to our topic, met the criteria and were included in the review. Results: The most prevalent leptin/leptin receptor genes (LEP/LEPR) and ghrelin/ghrelin receptor genes (GHRL/GHSR) single nucleotide polymorphisms studied were LEP G-2548A, LEPR Q223R, and Leu72Met, respectively. Nine studies of the 17 studies on LEP/LEPR, and three studies of the seven studies on GHRL/GHSR showed significant relationships. Conclusions: In general, our study suggests that the association between LEP/LEPR and GHRL/GHSR with overweight/obesity and the related metabolic disturbances is inconclusive. These results may be due to unidentified gene-environment interactions. More investigations are needed to further clarify this association.
Verbal memory in drug-naive, newly diagnosed Parkinson's disease. The retrieval deficit hypothesis revisited.

OBJECTIVE The retrieval deficit hypothesis on memory impairment in patients with Parkinson's disease (PD) implies a selective impairment in recall of learned material with normal encoding, retention, and recognition. This hypothesis has been challenged by new data. We have therefore investigated verbal memory and learning in a large sample of newly diagnosed, drug naïve, non-demented patients with PD. METHOD From a sample of patients with PD from the Norwegian ParkWest study, 133 PD patients and 133 controls matched on sex, age, and education were included. The California Verbal Learning Test-2 (CVLT-2) was used to assess verbal memory. RESULTS Patients performed significantly worse than controls on free and cued recall as well as on recognition memory. Patients used the semantic clustering learning strategy significantly less extensively than the controls and the learning slope of the PD patients was significantly less steep. There was no difference in retention when controlling for encoding. Patients did not perform better on the recognition measure or on cued recall (d-prime), as compared to free recall. Executive functions explained a substantial part of the memory deficits. CONCLUSIONS This study suggests that memory impairment in drug naïve early PD to a large degree is a deficit of learning/ encoding and not of retention or retrieval. An implication is that the retrieval deficit hypothesis should be moderated in its general form. Executive deficits and less extensive use of the efficient semantic clustering learning strategy had a strong impact on learning and memory.
Large deviation approach to the outage optical MIMO capacity

MIMO processing techniques in fiber optical communications have been proposed as a promising approach to meet increasing demand for information throughput. In this context, the multiple channels correspond to the multiple modes and/or multiple cores in the fiber. The lack of back-scattering necessitates the modeling of the transmission coefficients between modes as elements of a unitary matrix. Also, due to the scattering between modes the channel is modeled as a random Haar unitary matrix between Nt transmitting and Nr receiving modes. In this paper, we apply a large-deviations approach from random matrix theory to obtain the outage capacity for Haar matrices in the low outage limit, which is appropriate for fiber-optical communications. This methodology is based on the Coulomb gas method for the eigenvalues of a matrix developed in statistical physics. By comparing our analytic results to simulations, we see that, despite the fact that this method is nominally valid for large number of modes, our method is quite accurate even for small to modest number of channels.
Simulation of Thermal Signature of Tires and Tracks

Abstract : Rubber is the main element of tires and the outside layer of tracks. Tire and track heating is caused by hysteresis effects due to the deformation of the rubber during operation. Tire temperatures can depend on many factors, including tire geometry, inflation pressure, vehicle load and speed, road type and temperature and environmental conditions. The focus of this study is to develop a finite element approach to computationally evaluate the temperature field of a steady-state rolling tire and track. The 3D thermal analysis software Radtherm was applied to calculate the average temperature of tread and sidewall, and the results of Radtherm agreed with ABAQUS results very well. The distributions of stress and strain energy density of the rolling tracks were investigated by ABAQUS as well. The future works were finally presented.
Fire retardant properties of intumescent polypropylene composites filled with calcium carbonate

This study was aimed to investigate the influence of calcium carbonate (CaCO3), a widely used filler, on the fire retardancy of intumescent polypropylene composites. Two intumescent systems based on (1) mixture of ammonium polyphosphate (APP) and pentaerythritol and (2) surface-modified APP (m-APP) were examined. In terms of steady heat release rate, total heat evolved, and fire growth index determined by mass loss calorimetry, m-APP performed markedly superior to APP-pentaerythritol. The presence of CaCO3 in both intumescent formulations caused significant losses in fire retardant performance assessed by mass loss calorimetry, limiting oxygen index and UL-94 tests. Peak rates of heat release and mass loss during combustion, and total heat evolved on combustion were increased, whereas time to ignition was decreased. Characterization of fire residues ascribed the mechanism of deterioration in fire retardancy to the formation of porous and nonexpanded crystalline calcium phosphate/CaCO3 residues during combustion rather than the amorphous protective intumescent chars formed in the absence of CaCO3. POLYM. ENG. SCI., 2011. © 2011 Society of Plastics Engineers
Automatic Description Generation from Images: A Survey of Models, Datasets, and Evaluation Measures

Automatic description generation from natural images is a challenging problem that has recently received a large amount of interest from the computer vision and natural language processing communities. In this survey, we classify the existing approaches based on how they conceptualize this problem, viz., models that cast description as either generation problem or as a retrieval problem over a visual or multimodal representational space. We provide a detailed review of existing models, highlighting their advantages and disadvantages. Moreover, we give an overview of the benchmark image datasets and the evaluation measures that have been developed to assess the quality of machine-generated image descriptions. Finally we extrapolate future directions in the area of automatic image description generation.
Use of Mirror Elements in the Active Device Synthesis by Admittance Matrix Expansion

This paper proposes a modification for the symbolic synthesis method of analog circuits using admittance matrix expansion. The modification involves a generalization of the synthesis approach to employ mirror elements (voltage mirrors and current mirrors) in the admittance matrix expansion and ideal description of active elements, rather than using only nullor elements (nullators and norators). Accordingly, more alternative ideal representations, based on nullor-mirror elements, can be realized and a wide range of active elements can be used in the circuit synthesis. Systematic synthesis of the CCII-based generalized impedance converters (GICs) is presented as an application example to illustrate the potential of this generalized approach. Multiple equivalent nullor-mirror realizations for the GIC could be extracted easily, by virtue of using mirror elements in the admittance matrix expansion. Consequently, numerous circuit realizations, spanning various combinations of CCII types, have been generated in a simple and direct way.
Graph-Based Word Alignment for Clinical Language Evaluation

Among the more recent applications for natural language processing algorithms has been the analysis of spoken language data for diagnostic and remedial purposes, fueled by the demand for simple, objective, and unobtrusive screening tools for neurological disorders such as dementia. The automated analysis of narrative retellings in particular shows potential as a component of such a screening tool since the ability to produce accurate and meaningful narratives is noticeably impaired in individuals with dementia and its frequent precursor, mild cognitive impairment, as well as other neurodegenerative and neurodevelopmental disorders. In this article, we present a method for extracting narrative recall scores automatically and highly accurately from a word-level alignment between a retelling and the source narrative. We propose improvements to existing machine translation–based systems for word alignment, including a novel method of word alignment relying on random walks on a graph that achieves alignment accuracy superior to that of standard expectation maximization–based techniques for word alignment in a fraction of the time required for expectation maximization. In addition, the narrative recall score features extracted from these high-quality word alignments yield diagnostic classification accuracy comparable to that achieved using manually assigned scores and significantly higher than that achieved with summary-level text similarity metrics used in other areas of NLP. These methods can be trivially adapted to spontaneous language samples elicited with non-linguistic stimuli, thereby demonstrating the flexibility and generalizability of these methods.
Selective Encoding for Abstractive Sentence Summarization

We propose a selective encoding model to extend the sequence-to-sequence framework for abstractive sentence summarization. It consists of a sentence encoder, a selective gate network, and an attention equipped decoder. The sentence encoder and decoder are built with recurrent neural networks. The selective gate network constructs a second level sentence representation by controlling the information flow from encoder to decoder. The second level representation is tailored for sentence summarization task, which leads to better performance. We evaluate our model on the English Gigaword, DUC 2004 and MSR abstractive sentence summarization datasets. The experimental results show that the proposed selective encoding model outperforms the state-of-the-art baseline models.
The controller placement problem

Network architectures such as Software-Defined Networks (SDNs) move the control logic off packet processing devices and onto external controllers. These network architectures with decoupled control planes open many unanswered questions regarding reliability, scalability, and performance when compared to more traditional purely distributed systems. This paper opens the investigation by focusing on two specific questions: given a topology, how many controllers are needed, and where should they go? To answer these questions, we examine fundamental limits to control plane propagation latency on an upcoming Internet2 production deployment, then expand our scope to over 100 publicly available WAN topologies. As expected, the answers depend on the topology. More surprisingly, one controller location is often sufficient to meet existing reaction-time requirements (though certainly not fault tolerance requirements).
Abnormal coupling of knee and hip moments during maximal exertions in persons with cerebral palsy

The motions of lower‐limb extension, adduction, and internal rotation are frequently coupled in persons with cerebral palsy (CP) and are commonly referred to as an extension synergy. However, the underlying joint moments that give rise to these coupled motions are not well understood. We hypothesized that maximal voluntary exertions in a direction of one component of a synergy (e.g., hip extension) would result in the concurrent presence of other components of the synergy in subjects with CP but not in control subjects. To test this hypothesis, we measured three‐dimensional moments about the hip and knee as nine subjects with spastic CP and six control subjects performed maximal isometric exertions of the hip and knee flexors and extensors. During maximal hip extension exertions, control subjects simultaneously generated a knee flexion moment, whereas CP subjects generated a knee extension moment (P < 0.05) and a larger hip internal rotation moment than did controls (P < 0.05). During maximal knee extension exertions, control subjects generated a hip flexion moment, whereas CP subjects generated a hip extension moment (P < 0.05). The patterns of joint moments generated by CP subjects are consistent with an extension synergy and may underlie the coupled motion patterns of the lower extremity in such persons. Muscle Nerve 27: 486–493, 2003