Miracle-dz/UniFAR-FTUs huggingface dataset:
The impact of the economic crisis and policy actions on GHG emissions from road transport in Spain

Road traffic is the greatest contributor to the carbon footprint of the transport sector and reducing it has become one of the main targets of sustainable transport policies. An analysis of the main factors influencing greenhouse gas (GHG) emissions is essential for designing new energy- and environmentally efficient strategies for the road transport. This paper addresses this need by (i) identifying factors which influence the carbon footprint, including traffic activity, fuel economy and socioeconomic development; and (ii) proposing a methodological framework which uses Modified Laspeyres Index decomposition to analyze the effect of important drivers on the changes in emissions of road transport in Spain during the period from 1990 to 2010. The results demonstrate that the country׳s economic growth has been closely linked to the rise in GHG emissions. The innovative contribution of this paper is the special analysis of the changes in mobility patterns and GHG emissions during the economic crisis, when, for the first time, Spanish road traffic emissions decreased. The reduction of road transport and improved energy efficiency has been powerful contributors to this decrease, demonstrating the effectiveness of energy-saving measures. On the basis of this analysis, several tailored policy recommendations have been suggested for future implementation.
ADRC with Feedfoward Control For Time-Delay Systems

A novel Active disturbance rejection control (ADRC) with feedforward control is proposed for time-delay systems. The feedforward control, which is inspired by the classic Smith predictor, is added to the original ADRC scheme and tuned to improve the reference tracking performance. The ADRC is mainly tuned to reject total disturbance including model uncertainties and external disturbance. The feedforward control does not change the poles of the main closed-loop system and the stability of the main closed-loop system depends on the conventional ADRC whose stability has been solved theoretically. A first-order plus time-delay (FOPTD) system is used in simulation study where the increasing system order method for time-delay system is used in ADRC. Simulations for reference tracking, external disturbance and variations of time-delay, time-constant and process gain of the plant show that the proposed ADRC with feedforward control provides more effective tracking performance and disturbance rejection abilities than the conventional ADRC for time-delay systems.
Dissolved inorganic phosphorus, dissolved iron, and Trichodesmium in the oligotrophic South China Sea

Dissolved inorganic phosphorus (DIP) concentrations in the oligotrophic surface waters of the South China Sea decrease from ∼20 nM in March 2000 to ∼5 nM in July 2000, in response to seasonal water column stratification. These minimum DIP concentrations are one order of magnitude higher than those in the P‐limited, iron‐replete stratified surface waters of the western North Atlantic, suggesting that the ecosystem in the South China Sea may be limited by bioavailable nitrogen or some trace nutrient rather than DIP. Nutrient enrichment experiments using either nitrate, phosphate or both indicate that nitrogen limits the net growth of phytoplankton in the South China Sea, at least during March and July 2000. The fixed nitrogen limitation may result from the excess phosphate (N:P<16) transported into the South China Sea from the North Pacific relative to microbial population needs, or from iron control of nitrogen fixation. The iron‐limited nitrogen fixation hypothesis is supported by the observation of low population densities of Trichodesmium spp. (<48 × 103 trichomes/m3), the putative N2 fixing cyanobacterium, and with low concentrations of dissolved iron (∼0.2–0.3 nM) in the South China Sea surface water. Our results suggest that nitrogen fixation can be limited by available iron even in regions with a high rate of atmospheric dust deposition such as in the South China Sea.
Determining attributes of Indian real property valuation using principal component analysis

Introduction: Accurate property valuation depends on correct analysis of the contributing factors. Real property valuation is required to be carried out for various purposes including buying, selling, mortgage, tax calculation etc. Aim of this study is to ascertain the prominent factors affecting property value in Indian housing market. Methodology: Total nineteen variables were identified from literature as well as discussion with experts. Opinion of the experts about the level of significance of each of the variables towards value of property was taken through a well structured questionnaire survey. Data obtained from the survey was processed using Principal Component Analysis (PCA) which helped to decrease the number of variables into seven most important factors affecting value of real property in Indian housing market. Results: The seven most important factors that affect Indian real property value included living conditions of residents; characteristics of housing; regional influence; utilities; age of property; economic, political & social influence; area & legal aspect. Conclusion: The study is an effort of its kind in applying PCA for Indian housing market and can form the basis for preparing automated value prediction model.
Improvement and evaluation of simulated global biogenic soil NO emissions in an AC-GCM

Abstract. Biogenic NO emissions from soils (SNO x ) play important direct and indirect roles in tropospheric chemistry. The most widely applied algorithm to calculate SNO x in global models was published 15 years ago by Yienger and Levy (1995), and was based on very few measurements. Since then, numerous new measurements have been published, which we used to build up a compilation of world wide field measurements covering the period from 1978 to 2010. Recently, several satellite-based top-down approaches, which recalculated the different sources of NO x (fossil fuel, biomass burning, soil and lightning), have shown an underestimation of SNO x by the algorithm of Yienger and Levy (1995). Nevertheless, to our knowledge no general improvements of this algorithm, besides suggested scalings of the total source magnitude, have yet been published. Here we present major improvements to the algorithm, which should help to optimize the representation of SNO x in atmospheric-chemistry global climate models, without modifying the underlying principals or mathematical equations. The changes include: (1) using a new landcover map, with twice the number of landcover classes, and using annually varying fertilizer application rates; (2) adopting a fraction of 1.0 % for the applied fertilizer lost as NO, based on our compilation of measurements; (3) using the volumetric soil moisture to distinguish between the wet and dry states; and (4) adjusting the emission factors to reproduce the measured emissions in our compilation (based on either their geometric or arithmetic mean values). These steps lead to increased global annual SNO x , and our total above canopy SNO x source of 8.6 Tg yr −1 (using the geometric mean) ends up being close to one of the satellite-based top-down approaches (8.9 Tg yr −1 ). The above canopy SNO x source using the arithmetic mean is 27.6 Tg yr −1 , which is higher than all previous estimates, but compares better with a regional top-down study in eastern China. This suggests that both top-down and bottom-up approaches will be needed in future attempts to provide a better calculation of SNO x .
Local Search-based Enhanced Multi-objective Genetic Algorithm and Its Application to the Gestational Diabetes Diagnosis

In evolutionary computation, several multiobjective genetic algorithms (MOGAs) have been widely used to solve multi-objective optimization problems (MOOPs). The version NSGA-II, developed by Deb et al., is a useful package using a population-based genetic algorithm to solve optimization problems with multiple objectives subject to constraints. This study proposes an enhanced version of NSGA-II, termed LS-EMOGA herein, which modifies the crossover and mutation operators of original NSGA-II by an extended intermediate crossover and a nonuniform mutation and also incorporates a local search (LS) procedure to improve the fine-turning ability of the solution searching. The performance of the proposed LS-EMOGA is assessed by evaluating five benchmark cases of MOOPs. The computed solutions are compared with those of obtained using NSGA-II and proposed MOGA without local search procedure (EMOGA version). Moreover, the proposed LS-EMOGA combines a k-means clustering algorithm to apply to the case diagnosis of gestational diabetic disease. 
Ecosystem modelling for ecosystem-based management of bivalve aquaculture sites in data‑poor environments

Although models of carrying capacity have been around for some time, their use in aquaculture management has been limited. This is partially due to the cost involved in generating and testing the models. However, the use of more generic and flexible models could facilitate the implementation of modelling in management. We have built a generic core for coupling biogeo- chemical and hydrodynamic models using Simile (www.simulistics.com), a visual simulation en - vironment software that is well-suited to accommodate fully spatial models. Specifically, Simile integrates PEST (model-independent parameter estimation, Watermark Numerical Computing, www. pesthomepage.org), an optimization tool that uses the Gauss-Marquardt-Levenberg algo- rithm and can be used to estimate the value of a parameter, or set of parameters, in order to mini- mize the discrepancies between the model results and a dataset chosen by the user. The other crit- ical aspect of modelling exercises is the large amount of data necessary to set up, tune and ground truth the ecosystem model. However, ecoinformatics and improvements in remote sensing procedures have facilitated acquisition of these datasets, even in data-poor environments. In this paper we describe the required datasets and stages of model development necessary to build a biogeochemical model that can be used as a decision-making tool for bivalve aquaculture man- agement in data-poor environments.
Summertime tropospheric ozone enhancement associated with a cold front passage due to stratosphere‐to‐troposphere transport and biomass burning: Simultaneous ground‐based lidar and airborne measurements

Stratosphere‐to‐troposphere transport (STT) and biomass burning (BB) are two important natural sources for tropospheric ozone that can result in elevated ozone and air‐quality episode events. High‐resolution observations of multiple related species are critical for complex ozone source attribution. In this article, we present an analysis of coinciding ground‐based and airborne observations, including ozone lidar, ozonesonde, high spectral resolution lidar (HSRL), and multiple airborne in situ measurements, made on 28 and 29 June 2013 during the Southeast Nexus field campaign. The ozone lidar and HSRL reveal detailed ozone and aerosol structures as well as the temporal evolution associated with a cold front passage. The observations also captured two enhanced (+30 ppbv) ozone layers in the free troposphere (FT), which were determined from this study to be caused by a mixture of BB and stratospheric sources. The mechanism for this STT is tropopause folding associated with a cutoff upper level low‐pressure system according to the analysis of its potential vorticity structure. The depth of the tropopause fold appears to be shallow for this case compared to events observed in other seasons; however, the impact on lower tropospheric ozone was clearly observed. This event suggests that strong STT may occur in the southeast United States during the summer and can potentially impact lower troposphere during these times. Statistical analysis of the airborne observations of trace gases suggests a coincident influence of BB transport in the FT impacting the vertical structure of ozone during this case study.
Revisiting the Side Crushing Test Using the Three-Point Bending Test for the Strength Measurement of Catalyst Supports

The side crushing test is commonly used to characterize the mechanical strength of catalyst supports. However its interpretation is complex for cylindrical supports due to their irregular geometry and the various fracture modes induced. A better analysis of the crushing test, altogether with a comparison of the results obtained with the three-Point Bending test (3PB) and an analysis of the defects present within the supports, provide a better interpretation of their crushing strength data. Experimental results show that two different fracture modes appear during the crushing test – one under bending configuration and one under crushing configuration – inducing a large scatter of the data. Moreover, a comparison with the 3PB test shows that the strength measured in crushing is lower and the scatter of the data is larger than the ones obtained in bending. This is a consequence of a Weibull size effect and of the presence of macro-defects within one type of the tested supports. It is concluded that an analysis of the fracture modes activated during crushing has to be carried out to obtain a correct distribution of the strength data. The presence of macro-defects within the microstructure of the supports decreases drastically the crushing strength, while their influence on the bending strength is more limited.
Anomalous Majorana Neutrino Masses from Torsionful Quantum Gravity

The effect of quantum torsion in theories of quantum gravity is usually described by an axionlike field which couples to matter and to gravitation and radiation gauge fields. In perturbation theory, the couplings of this torsion-descent axion field are of derivative type and so preserve a shift symmetry. This shift symmetry may be broken, if the torsion-descent axion field mixes with other axions, which could be related to moduli fields in string-inspired effective theories. In particular, the shift symmetry may break explicitly via nonperturbative effects, when these axions couple to fermions via chirality-changing Yukawa couplings with appropriately suppressed coefficients. We show how in such theories an effective right-handed Majorana neutrino mass can be generated at two loops by gravitational interactions that involve global anomalies related to quantum torsion. We estimate the magnitude of the gravitationally induced Majorana mass and find that it is highly model dependent, ranging from the multi-TeV to keV scale.
Mining Life Insurance Data for Customer Attrition Analysis

Customer attrition is an increasingly pressing issue faced by many insurance providers today. Retaining customers who purchase life insurance policies is an even bigger challenge since the policy duration spans for more than twenty years. Companies are eager to reduce these attrition rates in the customer-base by analyzing operational data. Data mining techniques play an important role in facilitating these retention efforts. The objective of this study is to analyse customer attrition by classifying all policy holders who are likely to terminate their policies. These customers who are at high risk of attrition can then be targeted for promotions to reduce the rate of attrition. Data mining techniques such as Decision trees and Neural Networks are employed in this study. Models generated are evaluated using ROC curves and AUC values. Our research also adopts cost sensitive learning strategies to address issues such as imbalanced class labels and unequal misclassification costs. 
Focus on Implantation Implantation mechanisms: insights from the sheep

Implantation in all mammals involves shedding of the zona pellucida, followed by orientation, apposition, attachment and adhesion of the blastocyst to the endometrium. Endometrial invasion does not occur in domestic ruminants; thus, definitive implantation is achieved by adhesion of the mononuclear trophoblast cells to the endometrial lumenal epithelium (LE) and formation of syncytia by the fusion of trophoblast binucleate cells with the LE. This review highlights new information on mechanisms regulating the implantation cascade in sheep. The embryo enters the uterus on day 4 at the morula stage of development and then develops into a blastocyst by day 6. The blastocyst sheds the zona pellucida (day 8), elongates to a filamentous form (days 11‐16), and adheres to the endometrial LE (day 16). Between days 14 and 16, the binucleate cells begin to differentiate in the trophoblast and subsequently migrate and fuse with the endometrial LE to form syncytia. Continuous exposure of the endometrium to progesterone in early pregnancy downregulates the progesterone receptors in the epithelia, a process which is associated with loss of the cell-surface mucin MUC1 and induction of several secreted adhesion proteins. Recurrent early pregnancy loss in the uterine gland knockout ewe model indicates that secretions of the endometrial epithelia have a physiologic role in blastocyst elongation and implantation. A number of endometrial proteins have been identified as potential regulators of blastocyst development and implantation in sheep, including glycosylated cell adhesion molecule 1 (GlyCAM-1), galectin-15, integrins and osteopontin. The epithelial derived secreted adhesion proteins (GlyCAM-1, galectin-15 and osteopontin) are expressed in a dynamic temporal and spatial manner and regulated by progesterone and/or interferon tau, which is the pregnancy recognition signal produced by the trophoblast during blastocyst elongation. The noninvasive and protracted nature of implantation in domestic animals provides valuable opportunities to investigate fundamental processes of implantation that are shared among all mammals. Understanding of the cellular and molecular signals that regulate uterine receptivity and implantation can be used to diagnose and identify causes of recurrent pregnancy loss and to improve pregnancy outcome in domestic animals and humans. Reproduction (2004) 128 657–668
Effect of processing methods on the nutritional contents of bitter leaf (Vernonia amygdalina)

This study was conducted to determine the effect of four different processing methods on the nutritional contents of bitter leaf (Vernonia amygdalia). Fresh bitter leaves were subjected to different conventional food processing techniques, namely soaking in water (over night), blanching, abrasion with salt and without salt (Nacl) as well as fresh leave samples replicated three times. The fresh and treated samples were analyzed for antioxidant properties (reducing power and free radical scavenging ability), proximate compositions, mineral contents and antinutrient contents (tannin and phytate). The results obtained revealed that the reducing power of bitter leaf (0.53) was significant decreased with all the processing methods in the study. The free radical scavenging ability of fresh bitter leaf sample (70%) was significantly higher than in other treated samples (53-57%). The protein (6.0 – 7.3% ) and moisture contents (81.5 – 84.0% ) of variously treated bitter leaf were significantly (p≤0.05) lower than that of fresh leaves (8.4%) and (84.4%) respectively. Similarly, there was a decrease in the fat content by blanching and abrasion without salt 1.0% and 0.9% respectively , while soaking and abrasion with salt was increased by 2.2% and 2.3% respectively. The crude fiber content was lower with soaking while it was significantly (p≤0.05) higher with abrasion with salt. Blanching and soaking caused a significant (p≤0.05) decreased in the ash content while abrasions elevated its contents. Also, the various processing methods caused a significant reduction in mineral content of vegetable. The tannin content of v. amygdalina leaf (0.6%) was significantly (p≤0.05) reduced by the various treatments (0.4-0.5%). Similar trend was observed for phytate content with the exception of the soaked sample which showed no decrease. It could therefore be concluded that soaking overnight and blanching caused a significant reduction in the nutritional values of bitter leaf than other processing methods studied.
Discovery of concentric broken rings at sub-arcsec separations in the HD 141569A gas-rich, debris disk with VLT/SPHERE

Transition disks correspond to a short stage between the young protoplanetary phase and older debris phase. Along this evolutionary sequence, the gas component disappears leaving room for a dust-dominated environment where already-formed planets signpost their gravitational perturbations. We endeavor to study the very inner region of the well-known and complex debris, but still gas-rich disk, around HD 141569A using the exquisite high-contrast capability of SPHERE at the VLT. Recent near-infrared (IR) images suggest a relatively depleted cavity within ~200 au, while former mid-IR data indicate the presence of dust at separations shorter than ~100 au. We obtained multi-wavelength images in the near-IR in J, H2, H3 and Ks bands with the IRDIS camera and a 0.95-1.35 micrometers spectral data cube with the IFS. Data were acquired in pupil-tracking mode, thus allowing for angular differential imaging. We discovered several new structures inside 1", of which the most prominent is a bright ring with sharp edges (semi-major axis: 0.4") featuring a strong north-south brightness asymmetry. Other faint structures are also detected from 0.4" to 1" in the form of concentric ringlets and at least one spiral arm. Finally, the VISIR data at 8.6 micrometers suggests the presence of an additional dust population closer in. Besides, we do not detect companions more massive than 1-3 mass of Jupiter. The performance of SPHERE allows us to resolve the extended dust component, which was previously detected at thermal and visible wavelengths, into very complex patterns with strong asymmetries ; the nature of these asymmetries remains to be understood. Scenarios involving shepherding by planets or dust-gas interactions will have to be tested against these observations.
A two-circRNA signature predicts tumour recurrence in clinical non-functioning pituitary adenoma

Clinical non-functioning pituitary adenoma (NFPA) accounts for >30% of all pituitary adenomas, and the recurrence rate is notably high. The ability to predict tumour recurrence during initial surgery will aid in determining if adjunctive therapy is required to reduce recurrence. With the aim of developing a circular RNA (circRNA) signature to improve prognosis prediction in NFPA, the present study examined the circRNA expression profiles in 73 patients with NFPA from Beijing Tiantan Hospital using high-throughput RNA chip technology. The dataset was randomly separated into a training group and a test group using an R program. In the training group (n=37), a Cox proportional hazards regression model was used to analyse the genes associated with the recurrence and progression-free survival (PFS) of patients with NFPA. Meanwhile, a random survival forest algorithm, Kaplan-Meier and receiver operating characteristic curve (ROC) analyses were used to determine the multi-circRNA signature with the largest area under the ROC curve (AUROC) and verify its efficacy in the test group (n=36). In the training and test groups, the signatures of two circRNAs (hsa_circ_0000066 and hsa_circ_0069707) were specifically associated with the PFS of patients with NFPA (log-rank P<0.05). Furthermore, the two-circRNA signature had a high prediction accuracy for tumour recurrence, with an AUROC of 0.87 and 0.67 in the training and test groups, respectively; and the discriminative power of the signature was greater compared with that of age. The present study is the first to suggest a circRNA signature with a clinical application value for predicting recurrence/progression in patients with NFPA.