Miracle-dz/UniFAR-FTUs huggingface dataset:
Positive cascading effects of epiphytes enhance the persistence of a habitat‐forming macroalga and the biodiversity of the associated invertebrate community under increasing stress

Enhanced persistence of stress sensitive species in harsh environments due to amelioration of physical stress by habitat‐forming species has been widely documented. By contrast, less attention has been given to positive species interactions that may enhance stress tolerance in habitat‐forming species, with positive cascading effects on biodiversity and ecosystem functioning. We used a combination of field surveys and experiments to assess the effects of the epiphyte Jania rubens, on its subtidal macroalgal host Halopithys incurva, and their cascading effects on the associated invertebrate community, along a depth gradient associated with increasing stress (i.e. light stress at shallower depths). Correlative studies showed that the biomass and photosynthetic efficiency of H. incurva increased with depth, along with a decrease of epiphyte biomass. The experimental manipulation of epiphytes (removal in shallow water and addition in deep water) revealed that their effects on H. incurva physiology varied from positive in shallow habitats to negative in deep habitats. These results suggest that reduction of light/UV stress by J. rubens allows H. incurva to persist in shallow‐water habitats that would be otherwise unsuitable. In addition, colonization by large clumps of J. rubens increased the abundance and diversity of associated invertebrates in shallow habitat, suggesting that positive feedbacks between H. incurva, acting as the primary habitat‐former, and J. rubens, acting as a secondary habitat‐former, generate a facilitation cascade. Synthesis. Our study suggests that the persistence of some habitat‐forming species and their ability to support biodiversity may rely upon physical stress reduction by other species (e.g. epiphytes in our case) that are generally neglected when planning conservation strategies. A deeper understanding of context dependency in positive species interactions is essential for predicting patterns of species distribution under increasingly stressful climate scenarios.
FACTORS AFFECTING DISPOSITION EFFECT IN EQUITY INVESTMENT: A SOCIAL NETWORK ANALYSIS APPROACH

The study aims at identifying the factors influencing the disposition effect acting on equity investors and further identifying the relationship between the influencing factors. The study aims at conducting a complete analysis of the influencing factors along with measuring their impact on disposition effect using Social Network Analysis (SNA). The factors affecting disposition effect on investors were identified through the literature review. Experts’ opinions were sought for determining the relationship among the factors and finally, the importance of those factors was analyzed using Social Network Analysis (SNA). It was found that social trust, investor emotion are the two most important factors affecting the other factors of disposition effect and consequently disposition effect finally. Besides, mental accounting; regret aversion, trading intensity, trading volume, and portfolio performance strongly influence the effect of disposition on investors because of their higher in-degree and out-degree. Therefore, the policymakers need to impart training to the investors to understand the mechanism of the stock market so that they can evaluate their standing in the stock market which, in the long run, will be reflected in their investment behavior.
Mineralogical Record for Stepwise Hydroclimatic Changes in Lake Qinghai Sediments Since the Last Glacial Period

Lake Qinghai is sensitive to climatic changes because of its pivotal location between mid-latitude Westerlies and the low-latitude East Asian monsoon. An 18.6 m long drilling core (1Fs) from Lake Qinghai provides new information on the hydroclimatic dynamics since the last glacial period. Here, we present the results of bulk mineral assemblages of this core. X-ray diffraction (XRD) results showed that the bulk minerals of the core sediments consist of major clastic minerals (e.g., quartz, feldspar, muscovite), carbonates (e.g., calcite, aragonite, dolomite), and minor clay minerals (e.g., chlorite). Quartz as an exogenous detrital mineral in lake sediments, its abundance is related to lake level changes resulting from regional climate changes via fluvial/aeolian transportation. Aragonite was precipitated from water solutions or chemical alteration of pre-existing minerals or biogenic mediation, closely related to lake hydroclimate change. Mineral assemblages revealed remarkable stepwise hydroclimatic changes. High quartz content and low calcite without aragonite suggested a cold-wet climate condition under predominant westerlies during the last glacial period from 35 to 25.3 ka. Afterward, quartz decreased and aragonite occasionally appeared, indicating an unstable hydroclimatic condition during the last deglaciation. Since the Early Holocene (11.9–8.2 ka), predominant minerals shifted from terrigenous quartz to authigenic carbonates, suggesting an increasing lake level, possibly due to intensified Asian summer monsoon with increased effective moisture. Aragonite became the primary carbonate mineral, implying a warming and humid hydroclimate environment with a relatively higher lake-level. During the Middle Holocene (8.2–4.2 ka), aragonite showed a decreasing trend indicating a higher lake level with weak evaporation. During the Late Holocene since 4.2 ka, there were lower quartz and aragonite, suggesting a deep lake with a weak summer monsoon. Our quartz and carbonate minerals record provided essential clues to reconstruct hydroclimate change in Lake Qinghai since the last glacial period.
Corrigenda of EU Legislative Acts as an Indicator of Quality Assurance Failures

The objective of this chapter is to approach the topic of translation quality through the lens of corrigenda, an instrument which formally rectifies errors in EU legal acts. This instrument is part of the European Commission’s ex-post quality monitoring metrics included in the correction rate. Corrigenda have been rarely studied despite their potential to give insight into the nature of translation errors which were serious enough to require a formal rectification. We analyze the practice of corrigenda quantitatively and qualitatively, by investigating correction rates and the nature of corrigenda from a micro-diachronic perspective of 2004-2006 and 2015-2017 to correlate them with the maturity of the Polish Eurolect. Our findings show the growing number of corrigenda in the latter period, a large number of drafting corrections, an unpredictability of correction rates and inconsistencies in the corrigendum process. The largest group of corrections concerns terminology and phraseology. The early period is marked by unstable terminology and intraand intertextual inconsistencies. The mature period also shows intertextual inconsistencies but, above all, domestications of terminology and phraseology to the national usage, pointing out to the key challenge of a supranational and national interplay in EU translation.
Lung Segmentation on High-Resolution Computerized Tomography Images Using Deep Learning: A Preliminary Step for Radiomics Studies

Background: The aim of this work is to identify an automatic, accurate, and fast deep learning segmentation approach, applied to the parenchyma, using a very small dataset of high-resolution computed tomography images of patients with idiopathic pulmonary fibrosis. In this way, we aim to enhance the methodology performed by healthcare operators in radiomics studies where operator-independent segmentation methods must be used to correctly identify the target and, consequently, the texture-based prediction model. Methods: Two deep learning models were investigated: (i) U-Net, already used in many biomedical image segmentation tasks, and (ii) E-Net, used for image segmentation tasks in self-driving cars, where hardware availability is limited and accurate segmentation is critical for user safety. Our small image dataset is composed of 42 studies of patients with idiopathic pulmonary fibrosis, of which only 32 were used for the training phase. We compared the performance of the two models in terms of the similarity of their segmentation outcome with the gold standard and in terms of their resources’ requirements. Results: E-Net can be used to obtain accurate (dice similarity coefficient = 95.90%), fast (20.32 s), and clinically acceptable segmentation of the lung region. Conclusions: We demonstrated that deep learning models can be efficiently applied to rapidly segment and quantify the parenchyma of patients with pulmonary fibrosis, without any radiologist supervision, in order to produce user-independent results.
Active Tectonics in Tuscany (Central Italy): Ten Years of Seismicity (2009-2019)

Strong earthquakes (moment magnitude MW ≥ 5.5) are uncommon in Tuscany and surroundings (central Italy). The last strong seismic event occurred a century ago (September 7, 1920 Garfagnana, MW = 6.53). The paucity of seismic instrumental recordings hinders the identification of the tectonic regime active in Tuscany. On the other hand, the geological and geomorphological pieces of evidence collected so far, concerning potential active and capable faults, are scarce, fragmentary and ambiguous. In this work I shed light on the active deformation of Tuscany by using two independent approaches: earthquake source mechanisms and GNSS (GPS) geodetic measurements. I have considered 41 small seismic events (MW ≤ 5.1) that occurred in the study area during the last decade. The related source mechanisms (retrieved by the Time Domain Moment Tensor method) define a relatively clear picture of the active deformation: extension along the northern Apennine watershed and strike-slip regime within inner Tuscany, up to the Tyrrhenian coast. This pattern broadly agrees with the horizontal strain field reconstructed by the geodetic velocity field. The latter has been constrained by a network of 840 GPS stations located in Italy and neighboring countries, operating in the last 20 years.
Measuring the impact of clean energy production on CO2 abatement in Denmark: Upper bound estimation and forecasting *

Using annual data from 1978 through 2016, and monthly data from January 2005 through November 2017 from Denmark, we provide a precise estimate of the upper bound on the potential impact of the adoption of wind energy on the reduction of CO2 emissions from energy production. We separate causal impacts from endogenous effects in regressions using instrumental variables including average wind speed, and from spurious effects in dynamic systems using impulse‐response analysis and cointegration techniques. A one percentage point increase in the share of wind in total energy production is found to cause a reduction in CO2 emissions of the order 0.3%, based on endogeneity‐corrected regression, and 0.5% over 2 years in a fractional vector error‐correction model, after allowing the cumulative effects to take place. This corresponds to an upper bound estimate of 0.69 tonnes of CO2 emissions avoided per additional MWh of wind energy produced. We find that after a structural break at the time of introduction of the EU ETS and the Kyoto Protocol in 2005, the country has been on track towards meeting its long‐term goals for emission reduction and green energy production, but not before.
Efficient synthesis of size-controlled open-framework nanoparticles fabricated with a micro-mixer: route to the improvement of Cs adsorption performance

We demonstrated an efficient method for size-controlled nanoparticles of the open framework coordination polymer potassium copper hexacyanoferrate (KCuHCF) using only aqueous solutions of the raw materials and a Y-type micro-mixer. Despite the high viscosity of the synthesized NP slurry, the micro-mixer provides continuous synthesis without clogging for a few hours with a high flow rate of 100 mL min−1, i.e. a linear velocity of 94 m s−1. The crystallite size, evaluated by the Scherrer equation using X-ray diffraction measurements, can be controlled by changing the flow rate. With the highest flow rate of 100 mL min−1, the smallest NPs with a size of ∼11 nm were obtained, less than half of the NP size obtained using the batch method. By downsizing the nanoparticles (NPs) using the micro-mixer synthesis, the Cs adsorption performance of potassium copper hexacyanoferrate (KCuHCF) was drastically improved. The KCuHCF with the smallest primary particles showed the fastest Cs adsorption: 1.4 times in the saturated capacity, 3.9 times in the distribution coefficient, and 7.7 times in the rate constant for the pseudo-second order adsorption theory, compared with the batch-synthesized sample.
THE CRITIQUE OF MADDISON’S METHOD OF REVISING CHINA’S GDP DATA

Economist Angus Maddison is famous for his exploring the revision of economic statistical data, including China’s GDP data since the 1990s. This is a useful work. Maddison has revised China's GDP data from multiple angles, including the revision of China's non-material service sector GDP data. Maddison assumed that the non-material service sector in China has had a zero scientific and technological progress rate since the 1990s, while based on the data from the National Bureau of Statistics of China, the rate of scientific and technological progress in the non-material service sector should be big. Maddison's assumptions have led to a significant reduction in China's GDP data, and thus China's economic growth rate has dropped significantly. This paper argues that the high-tech progress rate of the non-material service sector-led and promoted by information technology is not only possible but also very likely, so China’s GDP data is credible in general, and of course, some small deviations and inaccuracies existed in China statistical GDP is understandable and acceptable.
The Comparison of High School Students’ Understanding of Kinematic Materials: Case of Question Representations

This present study aimed to compare the understanding on kinematic concepts between public and private high school students in terms of the type of questions representation. Therefore, this quantitative and descriptive study applied survey methods in conducting the research. 190 students of private high school and 199 students of public high school were involved as the research subjects. The main instrument in this study was an isomorphic multiple-choice test which was developed into verbal representations, pictures and graphics. Specifically, this research instrument was adapted from Force Motion Concept Evaluation (FMCE) and High School National Exam which had been validated with a reliability number of 0.74. Another key point, descriptive statistical and inferential independent t-test were used as the data analysis. Consequently, the results showed that there were significant differences in conceptual understanding between private and public high schools’ students. The concept understanding in private high school was lower than in public high school, which was evidenced with the average scores of public high school students by 42,68 and private high school students by 22,93. All in all, high school students are more capable in answering questions over verbal representation instead of understanding the concepts with graphical representations.
Mathematical modeling of the oil extrusion process with pre-grinding of raw materials in a twin-screw extruder

The extrusion process of oil-containing raw materials using a twin-screw extruder is becoming increasingly common in food technology. The problem of high energy costs for the implementation of this process is solved by reducing the resistance of the process mass due to the preliminary grinding of raw materials. The classical theory of extrusion is based mainly on the use of theoretical solutions of mathematical models of processes, which are simplified and allow determining integral parameters using coefficients, the preparation of which for the calculation of the corresponding processes and equipment is a rather complicated and approximate procedure. Mathematical modelling of the movement of the technological medium at the individual stages of the processing of raw materials allows us to determine the analytical dependences for the power and energy parameters of the system and to carry out their effective technical and economic evaluation. Using the methods of mathematical analysis and data processing in the MathCAD software environment, graphical dependences of the power and energy parameters of the research technical system were obtained. By increasing the density of the oil-containing raw materials, which is extruded in the research extruder by 40.5% the pressure force increases by 41%, that is, there is an almost proportional relationship between the pressure force and the density of the processed raw material. With an increase in the angular velocity of the drive shaft ω more than 8 rad.s-1, the pressure force in the research process increases sharply. With an increase in the density of raw materials, it is grinded before extrusion by 40%, the power consumption for the grinding process increases by 2.8 times for the recommended operating mode. Energy losses for pressing completely grinded raw materials are reduced by 2.52 times.
Genetic Characterization of Multiple Antibiotics Resistance Genes of Escherichia coli Strain from Cow Milk and Its Products Sold in Abuja, Nigeria

Background: Antibiotic resistance has remained a global concern. Food pathogens that carry resistance genes will cause public health threat irrespective of their pathogenicity, as this pool of resistance genes are disseminated via food chain. The antibiotic susceptibility of E. coli isolates to different antibiotics were investigated and resistance genes were genetically identified by multiplex Polymerase Chain Reaction (PCR). The study aimed to determine the phenotypic antibiotic resistance pattern of the E. coli isolates and characterize the antibiotics resistance genes in the E. coli isolates from the Cow milk and milk products. Original Research Article Okechukwu et al.; JABB, 23(7): 40-50, 2020; Article no.JABB. 54639 2 Results: The study showed that the E. coli isolates were Multidrug resistant (MDR) to several antibiotics with resistance pattern of four to ten combinations of antibiotics and the antibiotics resistance occurred mostly in three classes of antibiotics, namely: β-lactams, Amphenicol and Tetracycline. The antibiotics resistance genes expressed in the multidrug resistant E. coli isolates were tetA 22(78.6%), dfrA1 9(32.1%), blaCITM and blaSHV 3(10.7%), tetB and blaTEM 1(3.6%), qnr 0(0%) and aac (3)-iv 0(0%). Conclusion: The study showed that the cow milk and its products sold on the streets of Abuja are contaminated with resistant E. coli that can pose health risk to the consumers. Monitoring and screening for resistant food pathogens in food especially of animal origin is vital to mitigate the prevalence of antibiotics resistance.
Does Higher Education Reduce Mortality? Evidence from a Natural Experiment

We provide new evidence on the causal effect of education on health. Our empirical strategy exploits the reduction in access to college experienced by individuals reaching college age shortly after the 1973 military coup in Chile, which led to a sharp downward kink in enrollment for the affected cohorts. Using data from the vital statistics for the period 1994-2017, we document an upward kink in the age-adjusted yearly mortality rate for these cohorts, a pattern that we also observe in matched individual-level records for hospitalized patients. Leveraging the downward kink in college enrollment, we estimate a negative effect of college on mortality, which is larger for men, but also sizable for women. Affected individuals have worse labor market outcomes, lower income, and are more likely to be enrolled in the public health system. They also report lower consumption of health services, which suggests that economic disadvantage and limited access to care plausibly contribute to the effect of education on health.
Multicultural citizenship for the highly skilled? Naturalization, human capital, and the boundaries of belonging in Canada’s middle-class nation-building

Taking Canada as a widely envied and imitated example of liberal, “difference-blind” economic immigration, in this paper, I examine the permeability, constraints, and symbolic meaning of the different requirements of the naturalization process from the perspective of those who have undergone the process. Based on interviews with recently naturalized Canadians, my study reveals that the three steps of the application process – filing the application, studying the citizenship guide and sitting the test, attending the citizenship ceremony and swearing the citizenship oath – constitute mostly blurred boundaries for skilled and highly educated immigrants, with occasional bright boundaries related to management flaws, classed naturalization, and cultural biases. Specifically, immigrants endowed with valued forms of human capital are naturalizing fast and easily even if they are members of racial, ethnic or religious minorities. This underscores the strength of multiculturalism as national identity and ethos of societal integration. However, the attainment of citizenship in the multicultural nation does not come quasi-automatically as a right for everyone after years of lawful residency. Rather, it is granted as an earned privilege only to those who demonstrate the successful mastery of the skills and mindset of middle-class professionals. Since naturalization now operates along the same econocentric logic that governs immigrant selection through the points system, individuals admitted through non-economic streams, such as refugees and immigrants in the family class are increasingly struggling with the naturalization process. This raises questions about the implicit biases and new fault lines of seemingly difference-blind middle-class nation-building through immigration.
Defining Conditional Belonging: The Case of Female Science Fiction Fans

This article offers a rigorous conceptualisation of an undeveloped sociological concept: conditional belonging. It implements and develops conditional belonging in the setting of everyday life by examining female fans of science fiction. Based on 30 in-depth interviews with female fans of Doctor Who and Star Wars, this study defines conditional belonging as a liminal state in which new members are constructed as a threatening ‘other’ and required to demonstrate conformity to the community. Having to align with values established by veteran members disrupts the ability of those who conditionally belong to perceive their identities as authentic. Conditional belonging is explored in offline and online settings, exposing the tactics used online by female fans to ensure their belonging. Through demonstrating the ways in which conditional belonging is cultivated and enforced, this article contributes to a nuanced understanding of belonging, not as a binary condition, but a multi-layered, complex one.