Miracle-dz/UniFAR-FTUs huggingface dataset:
Algal-driven priming of cellulose decomposition along a phosphorus gradient in stream mesocosms

Primary producer-based and detrital-based energy pathways in streams are intertwined. Interactions between algae and heterotrophic microorganisms may accelerate or inhibit recalcitrant organic detritus decomposition depending on the environmental conditions. The magnitude and direction of this priming effect have been attributed to nutrient availability, but the influence of nutrients can be difficult to disentangle. To date, no studies have examined priming across a single-nutrient gradient where every other variable is tightly controlled. The purpose of this study was to investigate the role of algal priming on decomposition of standardized cellulose substrates across an extensive phosphorus (P) gradient in laboratory mesocosms. We placed unbleached cotton strips into 11 recirculating mesocosms, each divided into a light section and a dark section. Each mesocosm was subjected to a different P concentration ranging from 1 to 1024 µg P/L, with all other nutrients maintained at saturating concentrations. P stimulated algal biomass in the light, but fungal biomass responded more to P in the dark. Decomposition, measured as loss of tensile strength (an indicator of cellulose catabolism), and extracellular cellulase enzyme activities were lower in the light treatment than the dark treatment above ∼16 μg P/L, indicating a suppression of decomposition by algae. This negative priming was likely due to preferential use of algal exudates by fungi in the light treatments under P-replete conditions, which may be caused by maximum algal accrual and possibly bulk labile organic matter exudation above these concentrations. A lack of positive priming in this study may have been due to negligible nutrient concentrations in the cotton and saturating nitrogen (N) concentrations in the water, suggesting that positive priming is primarily associated with N mining and, to a lesser extent, P mining. This study highlights how complex interactions between algae and microbial heterotrophs coupled with altered light and nutrient regimes may have consequences for stream food webs.
Generalized Fractional Calculus for Gompertz-Type Models

This paper focuses on the construction of deterministic and stochastic extensions of the Gompertz curve by means of generalized fractional derivatives induced by complete Bernstein functions. Precisely, we first introduce a class of linear stochastic equations involving a generalized fractional integral and we study the properties of its solutions. This is done by proving the existence and uniqueness of Gaussian solutions of such equations via a fixed point argument and then by showing that, under suitable conditions, the expected value of the solution solves a generalized fractional linear equation. Regularity of the absolute p-moment functions is proved by using generalized Grönwall inequalities. Deterministic generalized fractional Gompertz curves are introduced by means of Caputo-type generalized fractional derivatives, possibly with respect to other functions. Their stochastic counterparts are then constructed by using the previously considered integral equations to define a rate process and a generalization of lognormal distributions to ensure that the median of the newly constructed process coincides with the deterministic curve.
The Seismicity of Indonesia and Tectonic Implications

Indonesian seismicity provides important insights into the tectonics and hazards of a region that is, characterized by a remarkable diversity in faulting, including subduction, extension, thrusting, and strike‐slip faulting. We present a synthesis of Indonesian seismotectonics by documenting the distributions of hypocenters (≥M 4.6) and focal mechanisms (≥M 5.0) over ∼20 years, quantifying seismicity rates, and comparing observed seismicity trends with recent tectonic and tomography models. Of the 20,622 events ≥M 4.6 observed in the study region, ∼77% are shallow (≤70 km depth) and of magnitudes
Teachers’ experiences of transformative professional learning to narrow the values practice gap related to inclusive practice

ABSTRACT The literature supports transformative models of professional learning and development (PLD) such as professional learning communities (PLCs). However, there is a research gap relating to PLCs for inclusive practice. This paper draws on findings from a qualitative study with 10 teachers in an urban primary school in the Republic of Ireland, who engaged in a PLC for inclusive practice facilitated by one of the researchers. Two years later the researchers undertook semi-structured interviews with nine of the original participants and five classroom observations to explore if and how teachers can sustain inclusive practices in changing times. The findings evidenced sustained changes in teachers’ individual and collaborative practices, affirming an argument that PLCs can support teachers to develop and sustain inclusive practices in the longer term. This paper offers a conceptual framework for prospectively planning PLCs to narrow the values practice gap for inclusive practice.
Intrusion Detection in Critical Infrastructures: A Literature Review

Over the years, the digitization of all aspects of life in modern societies is considered an acquired advantage. However, like the terrestrial world, the digital world is not perfect and many dangers and threats are present. In the present work, we conduct a systematic review on the methods of network detection and cyber attacks that can take place in a critical infrastructure. As is shown, the implementation of a system that learns from the system behavior (machine learning), on multiple levels and spots any diversity, is one of the most effective solutions.
AI based decision making: combining strategies to improve operational performance

This study investigates the strategic alignment between marketing and information technology (IT) strategies and provides production and operations decision makers a model for improving operational performance. Based on a comprehensive literature review, the combined strategies were used to develop a novel decision-making framework. The hypothesised relationships of an SEM model are validated with data collected from 242 managers from various industries. An artificial intelligence (AI)–based method is developed using artificial neural networks (ANN) feeding into a decision-making framework which explores the optimality of the combined strategies. The results indicate that (a) IT strategy is positively mediated by marketing strategy on performance and (b) the organisational structure moderates the mediation of marketing strategy on performance. The analysis confirms that the extracted strategies based on the proposed framework have superior performance compared to existing strategies. This paper contributes to the literature by conceptualising and empirically testing the mediation role of marketing strategy on IT strategy, performance and operational decision-making. The use of a novel three-phase decision-making framework which uses AI processes improves operational efficiency, increases insights and enhances the decision accuracy of complex problems at the strategic level in industries such as manufacturing. It could help operations executives to apply effective decisions.
Anisotropic, rate-dependent ductile fracture of Ti-6Al-4V alloy

An extensive experimental campaign was run to investigate the influence of the loading direction, stress state (triaxiality ratio ranging from −0.5 to 1), and strain rate (from 10−3 to 1.5x103s−1) on the ductile fracture of Ti-6Al-4V titanium alloy. Microscopic and macroscopic observations provided some insight into the shear-driven or micro-voiding-controlled damage mechanisms prevailing at low and high triaxiality ratios, respectively. Numerical simulations were run to determine the local loading paths to fracture in terms of plastic strain as a function of stress triaxiality ratio and Lode parameter. The ductility was found to be anisotropic, but only weakly dependent on the strain rate in the considered range. The anisotropy in ductility was different in tension (maximum along DD) and in compression (maximum along ND). The fracture strain decreased with the absolute value of the triaxiality, with a maximum close to zero. No clear correlation with the Lode parameter was found.
External Validation and Comparison of Clostridioides difficile Severity Scoring Systems.

BACKGROUND Many models have been developed to predict severe outcomes from Clostridioides difficile infection. These models are usually developed at a single institution and largely are not externally validated. This aim of this study was to validate previously published risk scores in a multicenter cohort of patients with CDI. METHODS Retrospective study on four separate inpatient cohorts with CDI from three distinct sites: The Universities of Michigan (2010-2012 and 2016), Chicago (2012), and Wisconsin (2012). The primary composite outcome was admission to an intensive care unit, colectomy, and/or death attributed to CDI within 30 days of positive testing. Both within each cohort and combined across all cohorts, published CDI severity scores were assessed and compared to each other and the IDSA guideline definitions of severe and fulminant CDI. RESULTS A total of 3,646 patients were included for analysis. Including the two IDSA guideline definitions, fourteen scores were assessed. Performance of scores varied within each cohort and in the combined set (mean area under the receiver operator characteristic curve(AUC 0.61, range 0.53-0.66). Only half of the scores had performance at or better than IDSA severe and fulminant definitions (AUCs 0.64 and 0.63, respectively). Most of the scoring systems had more false than true positives in the combined set (mean: 81.5%, range:0-91.5%). CONCLUSIONS No published CDI severity score showed stable, good predictive ability for adverse outcomes across multiple cohorts/institutions or in a combined multicenter cohort.
Classroom as heterotopia: English lessons as a space to problematise war

Abstract The incorporation of peace and war into the curriculum poses problems to teachers, especially in an examination-focussed school system. Whilst recent research concerning conflict has considered conflict-resolution within schools, and difficulties teachers face teaching about terrorism, little has been written on teaching 21st century war without the high-profile deployment of UK troops. In this article, I examine how peace and war are taught in an English school. After identifying the school’s overall war-focussed discourse, I focus on the practices of an ex-services English teacher and his techniques to debate, discuss, and ultimately problematise war creating a space akin to Foucault’s heterotopia. I argue this ‘other space’ allowed him to develop his practice and there is evidence of the heterotopia ‘leaking’ further afield. I suggest that although there are limitations to the classroom-as-heterotopia, it can nevertheless provide a space for practitioners to disrupt the wider discourse within their schools.
Self-service Technology Behavioral Intention: Indonesian Air Passengers

This research aims to better understand air travelers' expectations concerning the dimensions of rapid travel options. The analysis proposed an adaptive model that incorporates the advantages of self-check-in kiosk, perceived ease of use and perceived usefulness, passenger attitude, and behavioral intentions. An online survey study was carried out in Indonesia using purposive surveys, and there are a total of 600 valid answers. All hypotheses are acknowledged and verified by empirical results. Travelers do not automatically establish optimistic expectations or prefer to take advantage of an auto check kiosk because the facility is easy to use. Their mindset and expectations are defined by their belief that self-checking advantages are useful. While experienced passengers do not see using self-checking kiosks as an obstacle, it has been found that the perceived usefulness effect has a substantial influence on passengers 'attitudes.
Magma‐Mush Interactions in the Lower Oceanic Crust: Insights From Atlantis Bank Layered Series (Southwest Indian Ridge)

Magma migration and differentiation processes are key to understanding the development and evolution of oceanic magma reservoirs. To provide new quantitative geochemical constraints on these processes, we applied a high‐resolution approach to study an interlayered section of the lower oceanic crust sampled at Atlantis Bank, on the (ultra)slow‐spreading Southwest Indian Ridge. The section is characterized by sharp grain‐size layering between fine‐ and coarse‐grained olivine gabbros that is representative of other layered structures described at the Atlantis Bank oceanic core complex. The textures and fabrics of the layers and the nature of their contacts indicate formation by intrusion of a magma (i.e., crystal‐bearing) into an almost solidified coarse‐grained mush. Petrographic observations and in situ incompatible trace element signatures indicate that the fine‐ and coarse‐grained layers record reactive porous migration of melts. Widespread reactive porous flow occurred prior to intrusion within the coarse‐grained gabbro, producing mineral compositions enriched in incompatible elements. The intrusive fine‐grained lithology records a late stage event of localized reactive melt percolation in cm‐scale structures, which lead to strong light rare earth elements depletion relative to heavy rare earth elements. In addition, we highlight the occurrence of interactions at the contacts between layers and partial modification in compositions of the intruded lithology. This layered section likely represents a contact between two larger magma bodies emplaced within the lower crust during accretion, where the type of melt migration (intrusion or porous flow) and the modalities of melt percolation (widespread or localized) strongly govern the composition of the crustal lithologies.
Women and scientist: the yellow light on the ivory tower

The study purposes were to understand the background of women scientist (WS) in studying science, what motivate them to choose science and technology field, exploring their achievement, understanding their social support, exploring their problems. This research was qualitative case study approach. The key informant were four who come from Industrial Engineering and Mathematics and Science Faculty of Universitas Islam Indonesia. The data collection method used depth interviews, observation and documentation. The data test method used triangulation while analysis uses reduction-display-conclusion. The research found that WS studied science because of their interest of internal factor and the environment role of external factor. Their motives also gave benefit for others and increase their networking that is bit similar to McClelland’s Theory. WS had high excellent achievement in functional and structural positions, they received awards from their university until international award which are related to their research result. They also occupied important university structural position. They faced role conflict problem which similar to Greenhaus and Beutell (1985) Theory which increase their behavior changing. They faced marginalization because of their marital status and fear of success tendency which are losing cooking skills and having risk of not having friends which similar to Shaw and Costanzo (1982) Theory.
Metric Learning Based Feature Representation with Gated Fusion Model for Speech Emotion Recognition

Due to the lack of sufﬁcient speech emotional data, the recognition performance of existing speech emotion recognition (SER) approaches is relatively low and requires further improvement to meet the needs of real-life applications. For the problem of data scarcity, an increasingly popular solution is to transfer emotional information through pre-training models and extract additional features. However, the feature representation needs further compression because the training object of unsupervised learning is to reconstruct input, making the latent representation contain non-affective information. In this paper, we introduce deep metric learning to constrain the feature distribution of the pre-training model. Speciﬁcally, we propose a triplet loss to modify the representation extraction model as a pseudo-siamese network and achieve more efﬁcient knowledge transfer for emotion recognition. Furthermore, we propose a gated fusion method to learn the connection of features extracted from the pre-training model and supervised feature extraction model. We conduct experiments on the common benchmarking dataset IEMOCAP to verify the performance of the proposed model. The experimental results demonstrate the advantages of our model, outperforming the unsupervised transfer learning sys-tem by 3.7% and 3.88% in weighted accuracy and unweighted accuracy, respectively.
Profiting on the Stock Market in Pandemic Times: Study of COVID-19 Effects on CESEE Stock Markets

This research deals with stock market reactions of Central Eastern and South Eastern European (CESEE) markets to the COVID-19 pandemic, via the event study methodology approach. Since the stock markets react quickly to certain announcements, the used methodology is appropriate to evaluate how the aforementioned markets reacted to certain events. The purpose of this research was to evaluate possibilities of obtaining profits on the stock markets during great turbulences, when a majority of the participants panic. More specifically, the contrarian trading strategies are observed if they can obtain gains, although a majority of the markets suffer great losses during pandemic shocks. The contributions to the existing literature of this research are as follows. Firstly, empirical research on CESEE stock markets regarding other relevant topics is still scarce and should be explored more. Secondly, the event study approach of COVID-19 effects utilized in this study has (to the knowledge of the author) not yet been explored on the aforementioned markets. Thirdly, based on the results of CESEE market reactions to specific announcements regarding COVID-19, a simulation of simple trading strategies will be made in order to estimate whether some investors could have profited in certain periods. The results of the study indicate promising results in terms of exploiting other investors’ panicking during the greatest decline of stock market indices. Namely, the initial results, as expected, indicate strong negative effects of specific COVID-19 announcements on the selected stock markets. Secondly, the obtained information was shown to be useful for contrarian strategy in order to exploit great dips in the stock market indices values.
Defining the Expression, Production, and Signaling Roles of Specialized Metabolites during Bacillus subtilis Differentiation

Bacterially produced specialized metabolites are frequently studied for their potential use as antibiotics and antifungals. However, a growing body of work has suggested that the antagonistic potential of specialized metabolites is not their only function. ABSTRACT Bacterial specialized (or secondary) metabolites are structurally diverse molecules that mediate intra- and interspecies interactions by altering growth and cellular physiology and differentiation. Bacillus subtilis, a Gram-positive model bacterium commonly used to study biofilm formation and sporulation, has the capacity to produce more than 10 specialized metabolites. Some of these B. subtilis specialized metabolites have been investigated for their role in facilitating cellular differentiation, but only rarely has the behavior of multiple metabolites been simultaneously investigated. In this study, we explored the interconnectivity of differentiation (biofilm and sporulation) and specialized metabolites in B. subtilis. Specifically, we interrogated how development influences specialized metabolites and vice versa. Using the sporulation-inducing medium DSM, we found that the majority of the specialized metabolites examined are expressed and produced during biofilm formation and sporulation. Additionally, we found that six of these metabolites (surfactin, ComX, bacillibactin, bacilysin, subtilosin A, and plipastatin) are necessary signaling molecules for proper progression of B. subtilis differentiation. This study further supports the growing body of work demonstrating that specialized metabolites have essential physiological functions as cell-cell communication signals in bacteria. IMPORTANCE Bacterially produced specialized metabolites are frequently studied for their potential use as antibiotics and antifungals. However, a growing body of work has suggested that the antagonistic potential of specialized metabolites is not their only function. Here, using Bacillus subtilis as our model bacterium, we demonstrated that developmental processes such as biofilm formation and sporulation are tightly linked to specialized metabolite gene expression and production. Additionally, under our differentiation-inducing conditions, six out of the nine specialized metabolites investigated behave as intraspecific signals that impact B. subtilis physiology and influence biofilm formation and sporulation. Our work supports the viewpoint that specialized metabolites have a clear role as cell-cell signaling molecules within differentiated populations of bacteria.
Estimation and selection in linear mixed models with missing data under compound symmetric structure

It is quite appealing to extend existing theories in classical linear models to correlated responses where linear mixed-effects models are utilized and the dependency in the data is modeled by random effects. In the mixed modeling framework, missing values occur naturally due to dropouts or non-responses, which is frequently encountered when dealing with real data. Motivated by such problems, we aim to investigate the estimation and model selection performance in linear mixed models when missing data are present. Inspired by the property of the indicator function for missingness and its relation to missing rates, we propose an approach that records missingness in an indicator-based matrix and derive the likelihood-based estimators for all parameters involved in the linear mixed-effects models. Based on the proposed method for estimation, we explore the relationship between estimation and selection behavior over missing rates. Simulations and a real data application are conducted for illustrating the effectiveness of the proposed method in selecting the most appropriate model and in estimating parameters.
Outcomes of poorly differentiated and plasmacytoid variant bladder urothelial carcinoma

The aim of this study is to assess the course and management of poorly differentiated bladder urothelial carcinoma (UC), including plasmacytoid UC (PUC), in our local area. Although bladder cancer is relatively common, PUC is a rare and aggressive subtype with a poor prognosis that is still poorly understood.
Family Background Characteristics and Student Achievement: Does School Ethos Play a Compensatory Role?

It is a well-known fact that family background characteristics affect school achievement, and according to Swedish law, school should play a compensatory role to outweigh such differences. Previous research has demonstrated that a strong school ethos is associated with higher student achievement, but whether school ethos can play a compensatory role for family background has not been investigated to the same extent. This study examines whether the predictive capacity of students’ family background on school achievement is moderated by school ethos. Data were derived from 9,349 ninth grade students (15–16 years) and 2,176 teachers in 159 school units in Stockholm. Multilevel linear regression analyses showed that family background characteristics, as well as school ethos, were associated with student achievement. School ethos did not, however, moderate the association between family background and school achievement. The results suggest that school ethos does not play a compensatory role, but rather, promotes school achievement for all students alike.