Cardiovascular magnetic resonance and right ventricular angiography in assessment of right ventricular volumes, function and wall motion abnormalities in arrhythmogenic right ventricular cardiomyopathy: a comparative study

Background: Arrhythmogenic right ventricular cardiomyopathy (ARVC) is an inherited cardiomyopathy characterised by structural changes to mostly the right ventricle (RV) that predisposes to ventricular arrhythmias heart failure and sudden cardiac death. ARVC is diagnosed using the 2010 Task Force Criteria which include RV angiography (RVA) and cardiovascular magnetic resonance (CMR). There has been a dearth of studies to document the comparison of the performance of CMR and RVA, and none undertaken in Africa. The aim of this study was to compare CMR and RVA in the assessment of ARVC in the South African ARVC registry. Methods: The study is a retrospective analysis of definite, possible and borderline ARVC cases from the South African ARVC registry and the African Cardiomyopathy and Myocarditis Registry Program (IMHOTEP) that have both CMR and RVA data. RV end-systolic and diastolic volumes, RV ejection fractions and the presence of absence of structural abnormalities derived from RVA and CMR are compared. Sensitivity of CMR and RVA for the diagnosis of definite, possible and borderline ARVC was also calculated. Results: A total of 11 patients out of 62 from the registry met the inclusion criteria. The Spearman’s coefficient for RV end-systolic volume was 0.48 (p=0.12). The Spearman’s coefficient for RV enddiastolic volume was 0.28 (p=0.4). The Spearman’s coefficient for RV ejection fraction was 0.06 (p=0.85). CMR detected regional wall abnormalities in 4 out of 11 patients while RVA did not detect any regional wall abnormalities. Sensitivity of CMR and RVA for the diagnosis of definite, possible and borderline ARVC was 48% and 55%, respectively. Conclusions: We show that South African ARVC patients had poor correlation between CMR and RVA parameters, and CMR was also more likely to reveal RV free wall regional wall motion abnormalities

The production of textile fibers from soy proteins

The use of soy protein presently is limited mostly to animal feeds, but the markets for soy protein could be expanded by industrial applications. In these studies, soy fibers were produced from soy protein isolate using both wet spinning and extrusion methods. The wet spinning process consisted of forcing an aged alkaline protein solution through a spinnerette having 368-[mu] openings into an acid coagulating bath. The extrusion process employed a twin screw extruder to force a protein-water mixture with dough-like consistency through a die also with 368-[mu] openings. The physical properties of the fibers were measured at 11% and 65% relative humidity and wet conditions using an Instron Universal Testing Machine. The fibers produced by both methods initially were brittle and very weak. The addition of glycerol reduced brittleness in extruded fibers and the inorganic ions zinc and calcium decreased the brittleness of wet-spun fibers. Modification of soy proteins by acylation with acetic anhydride or esterification with low molecular weight alcohols prior to extrusion to block the polar groups of soy proteins decreased the tenacity of the fibers. The tenacity of soy fibers was significantly improved by finishing treatments after extrusion using reagents such as acetic anhydride, glyoxal, glutaraldehyde or a combination of glutaraldehyde and acetic anhydride. The fibers finished with acetic anhydride or glutaraldehyde after extrusion became less polar by blocking the polar groups or cross-linking protein molecules. The conditions of finishing fibers and stretching fibers were studied to improve fiber properties. Scanning electron micrographs of the fibers revealed that strong fibers were smooth and continuous while weak fibers often contained cracks and voids

Life Tables of Bactrocera cucurbitae (Coquillett) (Diptera: Tephritidae): with a Mathematical Invalidation for Applying the Jackknife Technique to the Net Reproductive Rate

Life table data for the melon fly, Bactrocera cucurbitae (Coquillett), reared on cucumber (Cucumis sativus L.) were collected under laboratory and simulated field conditions. Means and standard errors of life table parameters were estimated for two replicates using the jackknife technique. At 25ºC, the intrinsic rates of increase (_r_) found for the two replicates were 0.1354 and 0.1002 day-1, and the net reproductive rates (_R_~0~) were 206.3 and 66.0 offspring, respectively. When the cucumbers kept under simulated field conditions were covered with leaves, the _r_ and _R_~0~ for the two replicates were 0.0935 and 0.0909 day-1, 17.5 and 11.4 offspring, respectively. However, when similar cucumbers were left uncovered, the _r_ and _R_~0~ for the two replicates were 0.1043 and 0.0904 day-1, and 27.7 and 10.1 offspring, respectively. Our results revealed that considerable variability between replicates in both laboratory and field conditions is possible; this variability should be taken into consideration in data collection and application of life tables. Mathematical analysis has demonstrated that applying the jackknife technique results in unrealistic pseudo-_R_~0~ and overestimation of its variance. We suggest that the jackknife technique should not be used for the estimation of variability of _R_~0~

Numeral Understanding in Financial Tweets for Fine-grained Crowd-based Forecasting

Numerals that contain much information in financial documents are crucial for financial decision making. They play different roles in financial analysis processes. This paper is aimed at understanding the meanings of numerals in financial tweets for fine-grained crowd-based forecasting. We propose a taxonomy that classifies the numerals in financial tweets into 7 categories, and further extend some of these categories into several subcategories. Neural network-based models with word and character-level encoders are proposed for 7-way classification and 17-way classification. We perform backtest to confirm the effectiveness of the numeric opinions made by the crowd. This work is the first attempt to understand numerals in financial social media data, and we provide the first comparison of fine-grained opinion of individual investors and analysts based on their forecast price. The numeral corpus used in our experiments, called FinNum 1.0 , is available for research purposes.Comment: Accepted by the 2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2018), Santiago, Chil

NumHG: A Dataset for Number-Focused Headline Generation

Headline generation, a key task in abstractive summarization, strives to condense a full-length article into a succinct, single line of text. Notably, while contemporary encoder-decoder models excel based on the ROUGE metric, they often falter when it comes to the precise generation of numerals in headlines. We identify the lack of datasets providing fine-grained annotations for accurate numeral generation as a major roadblock. To address this, we introduce a new dataset, the NumHG, and provide over 27,000 annotated numeral-rich news articles for detailed investigation. Further, we evaluate five well-performing models from previous headline generation tasks using human evaluation in terms of numerical accuracy, reasonableness, and readability. Our study reveals a need for improvement in numerical accuracy, demonstrating the potential of the NumHG dataset to drive progress in number-focused headline generation and stimulate further discussions in numeral-focused text generation.Comment: NumEval@SemEval-2024 Datase

Local minima in quantum systems

Finding ground states of quantum many-body systems is known to be hard for both classical and quantum computers. As a result, when Nature cools a quantum system in a low-temperature thermal bath, the ground state cannot always be found efficiently. Instead, Nature finds a local minimum of the energy. In this work, we study the problem of finding local minima in quantum systems under thermal perturbations. While local minima are much easier to find than ground states, we show that finding a local minimum is computationally hard for classical computers, even when the task is to output a single-qubit observable at any local minimum. In contrast, we prove that a quantum computer can always find a local minimum efficiently using a thermal gradient descent algorithm that mimics the cooling process in Nature. To establish the classical hardness of finding local minima, we consider a family of two-dimensional Hamiltonians such that any problem solvable by polynomial-time quantum algorithms can be reduced to finding ground states of these Hamiltonians. We prove that for such Hamiltonians, all local minima are global minima. Therefore, assuming quantum computation is more powerful than classical computation, finding local minima is classically hard and quantumly easy.Comment: 9+80 pages, 4 figure

Effects of epidural compression on stellate neurons and thalamocortical afferent fibers in the rat primary somatosensory cortex

A number of neurological disorders such as epidural hematoma can cause compression of cerebral cortex. We here tested the hypothesis that sustained compression of primary somatosensory cortex may affect stellate neurons and thalamocortical afferent (TCA) fibers. A rat model with barrel cortex subjected to bead epidural compression was used. Golgi‑Cox staining analyses showed the shrinkage of dendritic arbors and the stripping of dendritic spines of stellate neurons for at least 3 months post‑lesion. Anterograde tracing analyses exhibited a progressive decline of TCA fiber density in barrel field for 6 months post‑lesion. Due to the abrupt decrease of TCA fiber density at 3 days after compression, we further used electron microscopy to investigate the ultrastructure of TCA fibers at this time. Some TCA fiber terminal profiles with dissolved or darkened mitochondria and fewer synaptic vesicles were distorted and broken. Furthermore, the disruption of mitochondria and myelin sheath was observed in some myelinated TCA fibers. In addition, expressions of oxidative markers 3‑nitrotyrosine and 4‑hydroxynonenal were elevated in barrel field post‑lesion. Treatment of antioxidant ascorbic acid or apocynin was able to reverse the increase of oxidative stress and the decline of TCA fiber density, rather than the shrinkage of dendrites and the stripping of dendritic spines of stellate neurons post‑lesion. Together, these results indicate that sustained epidural compression of primary somatosensory cortex affects the TCA fibers and the dendrites of stellate neurons for a prolonged period. In addition, oxidative stress is responsible for the reduction of TCA fiber density in barrels rather than the shrinkage of dendrites and the stripping of dendritic spines of stellate neurons