Miracle-dz/UniFAR-FTUs huggingface dataset:
Unique and complementary information on shape coexistence in the neutron-deficient Pb region derived from Coulomb excitation

Neutron-deficient isotopes of Pt–Hg–Pb–Po–Rn are the classic region in the investigation of shape coexistence in atomic nuclei. A large programme of Coulomb-excitation experiments has been undertaken at the REX-ISOLDE facility in CERN with a number of even–even isotopes in this region. These experiments have been used to probe the electromagnetic properties of yrast and non-yrast states of even–even exotic nuclei, above and below Z = 82. Amongst a large amount of different complementary techniques used to study nuclear structure, Coulomb excitation brings substantial and unique information detailing shape coexistence. In this paper we review the Coulomb-excitation campaign at REX-ISOLDE in the light-lead region together with most recently obtained results. Furthermore, we present some new interpretations that arise from this data and show testing comparisons to state-of-the-art nuclear models.
Learning to Hallucinate Face in the Dark

Face hallucination in low-light environments is an extremely challenging task due to the significant loss of facial structure and facial texture information. Although cascading image relighting and face hallucination tasks is a feasible strategy, simply cascading these two tasks does not achieve satisfactory results because they do not fit into each other naturally. In this article, we propose a novel duplex fusing-embedding learning approach to tackle this challenge in low-light environments. The core of the proposed approach is the duplexity of feature fusion and embedding between relighting and hallucination tasks. In the feature fusion phase, the shallow features from two tasks are bidirectionally fused and activated into a consistent feature space. In the feature embedding phase, the fused features from the previous iteration are fed back and bidirectionally embedded into the deep features of two tasks in the current iteration so that they can learn feature representations that consistently represent both tasks, thereby boosting the performance of relighting and hallucination to generate photorealistic HR face images. Experimental results show that the proposed approach allows current face hallucination methods to learn to hallucinate face in the dark.
First reported Porrocaecum angusticolle infection in Griffon vulture (Gyps fulvus) in China

This present study is the first case of a Porrocaecum angusticolle (P. angusticolle) infection reported in Griffon vulture (Gyps fulvus) in China. This study aimed to identify the nematode species and explore the genetic evolution of worms infecting Gyps fulvus (G.fulvus). Clinical examination revealed several milky white parasites in the stomach and intestinal tract. Polymerase chain reaction and partial 18S gene sequencing analyses identified these worms to be P. angusticolle (SD isolates). Further phylogenetic analyses revealed that they shared the highest genetic identity (99.9%) with a P. angusticolle isolate (EU004820.1) from Germany. Our study is the first report on the identification and characterization of P. angusticolle infecting G.fulvus in China, based on clinical findings and molecular diagnosis. Therefore, our study provides novel insights for the diagnosis of P. angusticolle infections and the prevention of nematode transmission in wild and domestic animals.
Metric process models

Among the various formal models proposed to provide semantics for concurrency constructs in programming languages, partial orders have the advantages of conceptual simplicity, mathematical tractability, and economy of expression. We first observe that the theory of enriched categories supplies a natural abstraction of the notion of partial order, the D-schedule. Varying the choice of temporal domain D allows for other forms of temporal constraint beyond that available from simple ordering. For example, having the constraints of inter-event delays be numeric bounds produces a generalized metric-space structure suitable for the discussion of real-time computation. We then construct an algebra of processes parametrized by notion of time. Here a process is a structure based on schedules that also incorporates nondeterminism. Since the model is category-based, we can define operations on D-schedules and processes via universal constructions that depend little on the choice of D. Also, given a suitable choice of process structure and process morphism, the constructions used for process operations and schedule operations are remarkably similar.
Magnetohydrodynamic Free Convective Boundary Layer Flow of a Nanofluid past an Impulsively Started Flat Vertical Plate with Newtonian Heating Boundary Condition

Steady two dimensional MHD free convective boundary layer flow of an electrically conducting Newtonian nanofluid past an impulsively started infinite vertical plate is investigated numerically. Nanofluids are well-dispersed (metallic) nanoparticles at low-volume fractions in liquids. They may enhance the mixture's properties among them, thermal conductivity over the base fluid values. A magnetic field can be used to control the motion of an electrically conducting fluid in micro-scale systems used for the transportation of fluids. The momentum and energy equations along with the boundary conditions are first converted into dimensionless form by dimensional analysis. The transformed equations are solved numerically using the Implicit Finite Difference method of order two. MATLAB software is used to obtain the solutions of the tri-diagonal matrices. The effects of different controlling parameters, namely; Prandtl number, magnetic field number, Grashof number and Eckert number on temperature and velocity profiles are investigated. The numerical results for the velocity and temperature profiles are discussed and presented on tables and graphs. It is found that the fluid velocity increases with increase in the magnetic field and the Grashof number as temperature values also increase with increase of Prandtl number and Eckert number.
Nonparametric Inference for Multivariate Data: The R Package npmv

We introduce the R package npmv that performs nonparametric inference for the comparison of multivariate data samples and provides the results in easy-to-understand, but statistically correct, language. Unlike in classical multivariate analysis of variance, multivariate normality is not required for the data. In fact, the different response variables may even be measured on different scales (binary, ordinal, quantitative). p values are calculated for overall tests (permutation tests and F approximations), and, using multiple testing algorithms which control the familywise error rate, significant subsets of response variables and factor levels are identified. The package may be used for low- or highdimensional data with small or with large sample sizes and many or few factor levels.
Synthesis of 2-Izopropyl-5-methylphenylcarboxymethylen Tartrate

: The chemical reaction of O-chloroacetylthymol with the sodium salt of tartaric acid in the presence of dimethylformamide and hexamethylphosphoramide (HMPA) as solvents is described in this article, along with the ﬁndings of physico-chemical analysis to conﬁrm the structure of the resulting chemical compounds. Hexamethylphosphoramide was found to be present in the chemical reactions which were proven to have the greatest yields (HMPA).
Analysis of the Gross Domestic Product (GDP) time series and its interrelationship with the Civil Construction sector

The Gross Domestic Product (GDP) can be used to analyze the growth of some sectors in the country's economy. Furthermore, the GDP demonstrates how these sectors behave on the national stage. In this article, the aim is to study whether there is a relationship between the country's GDP and the growth of civil construction. For this, a time series was used with data from 1997. For the series fit, the selected model was ARIMA. Predictions for these data were tested, allowing to conclude that the model ARIMA is a viable alternative for the analyzed time series using as a criterion choice, the mean absolute percentage error (MAPE) values. To check whether GDP and civil construction growth are associated, we used the Pearson's Correlation coefficient and the results revealed a positive and moderate correlation between the variables (r = 0.741).
Collagen and Beyond: A Comprehensive Comparison of Human ECM Properties Derived from Various Tissue Sources for Regenerative Medicine Applications

Collagen, along with proteoglycans, glycosaminoglycans, glycoproteins, and various growth factors, forms the extracellular matrix (ECM) and contributes to the complexity and diversity of different tissues. Herein, we compared the physicochemical and biological properties of ECM hydrogels derived from four different human tissues: skin, bone, fat, and birth. Pure human collagen type I hydrogels were used as control. Physical characterization of ECM hydrogels and assessment of cell response of cord-tissue mesenchymal stem cells (CMSCs) were performed. Decellularization efficiency was found to be >90% for all ECM. Hydroxyproline quantification assay showed that collagen content in birth ECM was comparable to collagen control and significantly greater than other sources of ECM. Sodium dodecyl-sulfate polyacrylamide gel electrophoresis (SDS-PAGE) analysis showed the presence of γ, β, α1 and α2 collagen chains in all ECMs. Gelation kinetics of ECM hydrogels was significantly slower than collagen control. Compressive modulus of skin ECM was the highest and birth ECM was the lowest. Skin and birth ECM hydrogels were more stable than bone and fat ECM hydrogels. CMSCs encapsulated in birth ECM hydrogels exhibited the highest metabolic activity. Rheological characterization revealed that all ECM-derived inks exhibited shear thinning properties, and skin-derived ECM inks were most suitable for extrusion-based bioprinting for the concentration and printing conditions used in this study. Overall, results demonstrate that the physicochemical and biological properties of ECM hydrogels vary significantly depending on the tissue source. Therefore, careful selection of tissue source is important for development of ECM-based biomimetic tissue constructs for regenerative medicine applications.
Bayesian Model Averaging for Wind Speed Ensemble Forecasts Using Wind Speed and Direction

AbstractIn this paper, probabilistic wind speed forecasts are constructed based on ensemble numerical weather prediction (NWP) forecasts for both wind speed and wind direction. Including other NWP variables in addition to the one subject to forecasting is common for statistical calibration of deterministic forecasts. However, this practice is rarely seen for ensemble forecasts, probably because of a lack of methods. A Bayesian modeling approach (BMA) is adopted, and a flexible model class based on splines is introduced for the mean model. The spline model allows both wind speed and wind direction to be included nonlinearly. The proposed methodology is tested for forecasting hourly maximum 10-min wind speeds based on ensemble forecasts from the European Centre for Medium-Range Weather Forecasts at 204 locations in Norway for lead times from +12 to +108 h. An improvement in the continuous ranked probability score is seen for approximately 85% of the locations using the proposed method compared to standard B.
The impact of the 17 March 2015 St. Patrick's Day storm on the evolutionary pattern of equatorial ionization anomaly over the Indian longitudes using high‐resolution spatiotemporal TEC maps: New insights

The impact of the St. Patrick's Day storm (17 March 2015) on the major equatorial electrodynamical process viz., the equatorial ionization anomaly (EIA) has been assessed using 2‐D (5° latitude × 5° longitude) total electron content (TEC) maps generated from the ground‐based Satellite‐Based Augmentation System‐enabled receiver data. The various aspects of EIA, specifically the (i) evolution/devolution, (ii) longitudinal structure, and (iii) its variability during different phases of a geomagnetic storm, have been brought out. These 2‐D TEC maps, which have a large latitudinal (5°S–45°N) and longitudinal (55–110°E) coverage, show the complete reversal in the longitudinal structure/pattern of EIA during the recovery phase of the storm as compared to the quiet day. These results have been explained in the light of the combined effects of the storm associated processes such as (i) the penetration electric fields of magnetosphere origin, (ii) storm‐induced thermospheric winds, and (iii) activation of the consequent disturbance dynamo effectively distorting the longitudinal wave number 4 structure of the EIA. It has been shown unambiguously that even a separation of ~10°–15° longitude could experience significantly different forcings. The relevance and the far‐reaching consequences of the study in the light of the current trends and requirements for reliable satellite‐based navigation are highlighted.
A high brightness parametric source of entangled photon states

We report on a high brilliant source of polarization-entangled photon pairs. It consists of a type-I crystal which operates in an interferometric scheme where all the photon couples emitted at a certain wavelength and belonging to the phase matching cone take part in the entanglement and can be measured. In these peculiar conditions, we have obtained a violation of Bell's inequalities of 213 standard deviations. The brightness and the robustness of the source have been also characterized by different experiments. Tunable non maximally entangled states have been produced with this source, without postselection, to give an experimental demonstration of the Hardy's ladder proof about the contradiction between quantum mechanics and local realism for more than 40% of photon pairs belonging to the emission cone.
Cloning and expression characterization of elongation of very long-chain fatty acids protein 6 (elovl6) with dietary fatty acids, ambient salinity and starvation stress in Scylla paramamosain

Introduction: Elongation of very long-chain fatty acids protein 6 (ELOVL6) played crucial roles in regulating energy expenditure and fatty acid metabolism. Many studies have performed to investigate the physiological roles and regulatory mechanisms of elovl6 in fish and animals, while few studies were reported in crustaceans. Methods: Here we reported on the molecular cloning, tissue distribution and expression profiles in response to dietary fatty acids, ambient salinity and starvation stress in Scylla paramamosain by using rapid amplification of cDNA ends (RACE) and quantitative real-time PCR. Results: Three elovl6 isoforms (named elovl6a, elovl6b and elovl6c) were isolated from S. paramamosain in the present study. The complete sequence of elovl6a was 1345 bp, the full-length sequence of elovl6b was 1419 bp, and the obtained elovl6c sequence was 1375 bp in full length. The elovl6a, elovl6b and elovl6c encoded 287, 329 and 301 amino acids respectively, and exhibited the typical structural features of ELOVL protein family members. Phylogenetic analysis showed that the ELOVL6a from S. paramamosain clustered most closely to ELOVL6 from Portunus trituberculatus and Eriocheir sinensis, while the ELOVL6b and ELOVL6c from S. paramamosain gathered alone into a single branch. Quantitative real-time PCR exhibited that the relatively abundant expression of elovl6b was observed in intestine and stomach, and the elovl6a and elovl6c were highly expressed in hepatopancreas. In addition, studies found that replacing fish oil with soybean oil could significantly increase the transcriptional levels of three elovl6 in hepatopancreas of S. paramamosain, and the expression of elovl6a and elovl6c in hepatopancreas were more sensitive to dietary fatty acids than the elovl6b. Compared with the normal sea water group (27‰), the expression of sterol-regulatory element binding protein1c (srebp-1), elovl6a, elovl6b and elovl6c were upregulated in the low salinity groups, particularly in 7‰. On the contrary, the starvation stress suppressed the expression of srebp-1, elovl6a, elovl6b and elovl6c. Discussion: These results may contribute to understand the functions of elovl6 in fatty acid synthesis and regulatory mechanisms in crustaceans.
Experimental investigation of the inertial effects occurring in impact tests on plastics with varying mass distribution

Aim of the work is to elucidate some aspects of the phenomenology of impact tests in order to improve previously proposed modelizations. The experimental investigation focused on the influence of specimen dimensions and specimen mass distribution on the inertial effects observed in the initial part of an impact test. The experiments were carried out on single-edge notched specimens in the “one-point bending” mode. The flexural compliance of the notched specimens was varied by varying notch depth and specimen length and their mass distribution was varied by varying their length and by adding some concentrated masses. Analysis of the load-time traces recorded by the instrumented tup of the striker impacting the specimen at 1 m/s shows the distinct role played by the “contact mass” involved in the very first instants of the impact process, and by the inertia of the specimen wings. The “dynamic” one-point bend compliance of the specimen appears to be proportional to its “static” three-point bend compliance, if the specimen length in the former bending mode is equated to the span between the anvils in the latter bending mode. These results gave hints to the improvement of a previously proposed ‘analogical’ model for simulating the dynamics of the impact test.
Exploring Low-resource Neural Machine Translation for Sinhala-Tamil Language Pair

At present, Neural Machine Translation is a promising approach for machine translation. Transformer-based deep learning architectures in particular show a substantial performance increase in translating between various language pairs. However, many low-resource language pairs still struggle to lend themselves to Neural Machine Translation due to their data-hungry nature. In this article, we investigate methods of expanding the parallel corpus to enhance translation quality within a model training pipeline, starting from the initial collection of parallel data to the training process of baseline models. Grounded on state-of-the-art Neural Machine Translation approaches such as hyper-parameter tuning, and data augmentation with forward and backward translation, we define a set of best practices for improving Tamil-to-Sinhala machine translation and empirically validate our methods using standard evaluation metrics. Our results demonstrate that the Neural Machine Translation models trained on larger amounts of back-translated data outperform other synthetic data generation approaches in Transformer base training settings. We further demonstrate that, even for language pairs with limited resources, Transformer models are able to tune to outperform existing state-of-the-art Statistical Machine Translation models by as much as 3.28 BLEU points in the Tamil to Sinhala translation scenarios.
The Impact of Frailty on Palliative Care Receipt, Emergency Room Visits and Hospital Deaths in Cancer Patients: A Registry-Based Study

Background. Eastern Cooperative Oncology Group (ECOG) performance status is used in decision-making to identify fragile patients, despite the development of new and possibly more reliable measures. This study aimed to examine the impact of frailty on end-of-life healthcare utilization in deceased cancer patients. Method. Hospital Frailty Risk Scores (HFRS) were calculated based on 109 weighted International Classification of Diseases 10th revision (ICD-10) diagnoses, and HFRS was related to (a) receipt of specialized palliative care, (b) unplanned emergency room (ER) visits during the last month of life, and (c) acute hospital deaths. Results. A total of 20,431 deceased cancer patients in ordinary accommodations were studied (nursing home residents were excluded). Frailty, as defined by the HFRS, was more common in men than in women (42% vs. 38%, p < 0.001) and in people residing in less affluent residential areas (42% vs. 39%, p < 0.001). Patients with frailty were older (74.1 years vs. 70.4 years, p < 0.001). They received specialized palliative care (SPC) less often (76% vs. 81%, p < 0.001) but had more unplanned ER visits (50% vs. 35%, p < 0.001), and died more often in acute hospital settings (22% vs. 15%, p < 0.001). In multiple logistic regression models, the odds ratio (OR) was higher for frail people concerning ER visits (OR 1.81 (1.71–1.92), p < 0.001) and hospital deaths (OR 1.66 (1.51–1.81), p < 0.001), also in adjusted models, when controlled for age, sex, socioeconomic status at the area level, and for receipt of SPC. Conclusion. Frailty, as measured by the HFRS, significantly affects end-of-life cancer patients and should be considered in oncologic decision-making.
Using experts’ consensus (the Delphi method) to evaluate weighting techniques in web surveys not based on probability schemes

ABSTRACT Weighting techniques in web surveys based on no probability schemes are devised to correct biases due to self-selection, undercoverage, and nonresponse. In an interactive panel, 38 survey experts addressed weighting techniques and auxiliary variables in web surveys. Most of them corrected all biases jointly and applied calibration and propensity score adjustments. Although they claimed that sociodemographic and web-related variables are the most useful auxiliary variables to employ in adjustments, they considered only sociodemographic variables to correct biases because of their availability.
Peculiar Properties of Template-Assisted Aniline Polymerization in a Buffer Solution Using Laccase and a Laccase–Mediator System as Compared with Chemical Polymerization

The conventional chemical polymerization of aniline has been described in multiple publications, while enzymatic polymerization has been poorly explored. A comparative study of the template-assisted enzymatic and chemical polymerization of aniline in a buffer solution of sodium dodecylbenzenesulfonate micelles was performed for the first time. The high-redox potential laccase from the fungus Trametes hirsuta was used as a catalyst and air oxygen served as an oxidant. Potentiometric and spectral methods have shown that oligomeric/polymeric products of the enzymatic polymerization of aniline are synthesized in the conducting emeraldine salt form immediately after the reaction is initiated by the enzyme. The use of the laccase–mediator system enabled a higher rate of enzymatic polymerization and a higher yield of final products. Potassium octocyanomolybdate (IV) served as a redox mediator. The products of the enzymatic polymerization of aniline were studied by the ATR-FTIR, MALDI-TOF and atomic force microscopy methods. The chemical oxidative polymerization of aniline under the same conditions resulted in forming a non-conducting dark brown product.
Crypto quanto and inverse options

Over 90% of exchange trading on crypto options has always been on the Deribit platform. This centralized crypto exchange only lists inverse products because they do not accept fiat currency. Likewise, other major crypto options platforms only list crypto–stablecoin trading pairs in so‐called direct options, which are similar to the standard crypto options listed by the CME except the US dollar is replaced by a stablecoin version. Until now a clear mathematical exposition of these products has been lacking. We discuss the sources of market incompleteness in direct and inverse options and compare their pricing and hedging characteristics. Then we discuss the useful applications of currency protected “quanto” direct and inverse options for fiat‐based traders and describe their pricing and hedging characteristics, all in the Black–Scholes setting.