Miracle-dz/UniFAR-FTUs huggingface dataset:
Within-Person and Between-Sample Sensitivity to Dimensions of Risk

This paper reports the results of a survey designed to elicit probability judgements' for different kind of events. We find limited sensitivity to time both within-person and between groups of people. Second, we find some sensitivity to scope within-person although arguably less than we might expect and limited sensitivity to scope between groups of people. Finally, the subjective probabilities about crime and injuries appear to be largely unaffected either by feedback about the known frequencies of such events or by people's experience/practice estimating the likelihood of pure chance events. JEL Classification: C42, C81, D84.
BioZero—Designing Nature-Inspired Net-Zero Building

This article introduces BioZero, a nature-inspired near-zero building proposed for Quay St, Brooklyn, New York. The building is designed for the maximum use of daylight and natural ventilation. This is the result of its shallow plan depth and the inner light wells/ventilation stacks, which also serve the inner circulation space. The light wells/ventilation stacks are created as a result of the organic shape of the internal partitions. The building is constructed from a steel frame and hemp-lime bio-composite material (hempcrete), which smooths out the fluctuations of internal air temperature and relative humidity. The south facing façade is fitted with the Cadmium Telluride (CdTe) photovoltaic array that covers 90% of the opaque surface area of the façade. The design was based on nature-inspired computation, with sustainability principles as guiding constraints. The main findings are that the building achieves −227 tonnes of negative embodied carbon due to sequestration of CO2 in the hemp plant from which the material was harvested, and a net-zero operation. The main conclusions are that in the context of climate emergency, nature inspired design leads to energy efficient buildings with a high level of thermal comfort, which are buildable and sustainable.
Greening the Swiss National Bank's Portfolio

Central banks are increasingly concerned about climate-related risks and want to ensure that the financial system is resilient to them. As they integrate these risks into financial stability monitoring, they also discuss how to apply environmental criteria to their own policy portfolio management, without compromising their policy mandate. We describe different strategies and assess their relevance for central banks, using the Swiss National Bank’s (SNB) equity portfolio as a laboratory. We develop a carbon-conscious screening approach that is likely consistent with its policy mandate. The approach reduces the portfolio’s carbon footprint by 20%, with little impact on diversification or performance.
Development of Fake News Model using Machine Learning through Natural Language Processing

Fake news detection research is still in the early stage as this is a relatively new phenomenon in the interest raised by society. Machine learning helps to solve complex problems and to build AI systems nowadays and especially in those cases where we have tacit knowledge or the knowledge that is not known. We used machine learning algorithms and for identification of fake news; we applied three classifiers; Passive Aggressive, Na\"ive Bayes, and Support Vector Machine. Simple classification is not completely correct in fake news detection because classification methods are not specialized for fake news. With the integration of machine learning and text-based processing, we can detect fake news and build classifiers that can classify the news data. Text classification mainly focuses on extracting various features of text and after that incorporating those features into classification. The big challenge in this area is the lack of an efficient way to differentiate between fake and non-fake due to the unavailability of corpora. We applied three different machine learning classifiers on two publicly available datasets. Experimental analysis based on the existing dataset indicates a very encouraging and improved performance.
The Gap between Language Teaching Policies and Classroom Practices in the Turkish EFL Context: The Effects on Teacher Motivation1

This qualitative study explores Turkish English as a Foreign Language (EFL) teachers’ perspectives regarding current English Language Teaching (ELT) policies, ELT curriculum, assessment practices, and teacher motivation in the Turkish EFL setting. The study’s participants in this study were three native Turkish EFL teachers, teaching at elementary, middle school and high school levels. Data in the present study were collected with semi-structured online interviews. The interview data were coded with a priori codes, and the data were analyzed according to thematic analysis. The focus of the study was to explore whether EFL teachers teaching at primary and secondary levels observed a gap between the language teaching policies and actual classroom implementation of these policies in the Turkish EFL context, and if there was a perceived gap, how this gap affected EFL teachers’ motivation at different grade levels. The study found that teachers’ classroom practices were inconsistent with the expectations of official language teaching policy. Even though the findings of this study are not generalizable, the findings of this study are transferrable to other educational contexts and can be used to deepen understanding of the policy and practice gap phenomenon in different EFL and English as a Second Language (ESL) contexts.
Potent Suppressor of p2lras Function

Although p2l1 is localized to the plasma membrane, proteins it interacts with, such as the GTPaseactivating proteins (GAPs) ras GAP and neurofibromin (NF1), are not, suggesting that one function of p2l1 GTP may be to target such proteins to the plasma membrane. To investigate the effects of targeting ras GAP to the plasma membrane, ras C-terminal motifs sufficient for plasma membrane localization of p2l1 were cloned onto the C terminus of ras GAP. Plasma membrane-targeted ras GAP is growth inhibitory to NIH 3T3 fibroblasts and COS cells. This growth inhibition correlates with GAP catalytic activity, since the plasma membrane-targeted C-terminal catalytic domain or the GAP-related domain of neurofibromin is inhibitory, whereas the similarly targeted N-terminal domain is not. Moreover, the inhibition is abrogated by the inactivating mutation L9021, which abolishes ras GAP catalytic activity. Coexpression of oncogenic mutant ras rescues cell viability, but the majority of rescued colonies are phenotypically untransformed. Furthermore, in focus assays, targeted ras GAP suppresses transformation by oncogenic mutant ras, and in reversion assays, targeted ras GAP can revert cells transformed by oncogenic mutant ras. Neither the targeted or nontargeted N-terminal domain nor the L9021 mutant of ras GAP has any transforming activity. These data demonstrate that ras GAP can function as a negative regulator ofras and that plasma membrane localization potentiates this activity. However, if ras GAP is involved in the effector functions of p2l1, it can only be part of the effector complex for cell transformation.
Multi-Scale Task Multiple Instance Learning for the Classification of Digital Pathology Images with Global Annotations

Whole slide images (WSIs) are high-resolution digitized images of tissue samples, stored including diﬀerent magniﬁcation levels. WSIs datasets often include only global annotations, available thanks to pathology reports. Global annotations refer to global ﬁndings in the high-resolution image and do not include information about the location of the regions of interest or the magniﬁcation levels used to identify a ﬁnding. This fact can limit the training of machine learning models, as WSIs are usually very large and each magniﬁcation level includes diﬀerent information about the tissue. This paper presents a Multi-Scale Task Multiple Instance Learning (MuSTMIL) method, allowing to better exploit data paired with global labels and to combine contextual and detailed information identiﬁed at several magniﬁcation levels. The method is based on a multiple instance learning framework © 2021 N. Marini et al .
IJLLS-12-2020-0098_proof 286..301

Purpose – The purpose of this paper is to explore the merits of lesson study (LS) as a research approach for research in (science) education. A lesson was developed to introduce students to model-based reasoning: a higher order thinking skill that is seen as one of the major reasoning strategies in science. Design/methodology/approach –Participants of the LS teamwere three secondary school teachers and two educational researchers. Additionally, one participant fulfilled both roles. Both qualitative and quantitative data were used to investigate the effect of the developed lesson on students and to formulate focal points for using the LS as a research approach. Findings –The developed lesson successfully familiarized students with model-based reasoning. Three main focal points were formulated for using LS as a research approach: (1) make sure that the teachers support the research question that the researchers bring into the LS cycle, (2) take into account that the lesson is supposed to answer a research question that might cause extra stress for the teachers in an LS team and (3) state the role of both researchers and teachers in an LS team clearly at the beginning of the LS cycle. Originality/value – This study aims to investigate whether LS can be used as a research approach by the educational research community.
Diminishing Immune Responses against Variants of Concern in Dialysis Patients 4 Months after SARS-CoV-2 mRNA Vaccination

Patients undergoing chronic hemodialysis were among the first to receive SARS-CoV-2 vaccinations due to their increased risk for severe COVID-19 disease and high case fatality rates. To date, there have been minimal longitudinal studies in hemodialysis patients to ascertain whether protection offered by vaccination is long-lasting. To assess how surrogates for protection changed over time, we examined both the humoral and cellular response in a previously reported cohort of at-risk hemodialysis patients and healthy donors, four months after their second dose of Pfizer BNT162b2. Compared to three weeks post-second vaccination, both cellular and humoral responses against the original SARS-CoV-2 isolate as well as variants of concern were significantly reduced, with some dialyzed individuals having no B- or T-cell response. Our data strongly support the need for a third booster in hemodialysis patients and potentially other at-risk individuals.
Fair Machine Learning and Anti-subordination

The availability of large datasets and massive computing power has led to a surge in use of automated decision-making frameworks in a variety of domains; the list of applications includes (and is not limited to) healthcare, risk assessment, advertising, lending, and content moderation. However, the presence of biased datasets and/or use of misrepresentative models has had an impact on these automated frameworks as well; multiple studies have pointed out that prediction algorithms often propagate biases and negative stereotypes against historically-oppressed groups. Given the importance of the applications where automation is being employed currently and the possible lack of human oversight in their deployment, it is important that the learned algorithms not only stop the propagation of such biases but also make efforts in curbing the factors that enable such discrimination in first place.
Towards Transparent and Explainable Attention Models, ML Reproducibility Challenge 2020

The original paper proposes new LSTM variants that are supposed to improve the transparency and interpretability of the attention mechanism. They claim that modi ed LSTMs do not hurt the performance (Claim 1) and the attention distributions in the modi ed model variants provide a faithful explanation of the model’s predictions (Claim 2). Additionally, we provide our extensions. We verify whether the mean conicity of the attention values in the Vanilla Transformer is similar to the conicity of the Vanilla LSTM (Claim 4), whether the performance of a modi ed Transformer does not signi cantly hurt performance across different datasets (Claim 5) and if the orthogonalization procedure has homogeneous effects across 4 languages on the sentiment classi cation task (Claim 6).
Teaching Finance through Storytelling: Impact on Students' Learning

The use of storytelling for instruction has been advocated for long. But whether the use of a story during a lecture actually results in an improvement in students‟ learning? This article tries to find an answer to the question by using a story titled “Demons‟ Treasure” for teaching the topic of “Expected Return and Risk on Investments”. The study is based on a sample of 47 students who were divided randomly into a control group (which was taught without the use of story) and an experimental group (which was taught with the use of story). Students‟ learning was assessed through a subject based quiz. It was found that the use of story did not bring any significant change in quiz scores of the two groups but it did make the lecture interesting and brought other desired outcomes that may be considered essential for making their learning wholesome.
Number of Numbers: Does Quantitative Textual Disclosure Reduce Information Risk?

Theoretical research argues that numbers convey more precise information than words. Based on this work, we hypothesize that when managers provide disclosure with a greater proportion of quantitative information, information risk will decrease and firm value will increase. We offer three main findings. First, after controlling for the cash flow news in earnings conference calls, we find a positive association between the extent of hard information (i.e., numerical disclosure) and short-window stock returns around the call. This result suggests that information risk decreases when managers provide greater numerical disclosure. Second, we find that this positive association is larger when firms’ information environment is otherwise poor. Finally, we find that this positive association is larger when uncertainty about firm performance is higher (i.e., when the firm issues a negative earnings surprise). Overall, our results suggest that investors react to the extent of hard information (i.e., numerical disclosure) in earnings conference calls.
Hepatitis B Virus Gene Expression In Vivo by Tumor Necrosis

We have recently reported that administration of recombinant tumor necrosis factor alpha (TNF-a) to hepatitis B virus (HBV) transgenic mice reduces the hepatic steady-state content of HBV-specific mRNA by up to 80% in the absence of liver cell injury. In the current study, we analyzed the regulatory effects of several other inflammatory cytokines in the same transgenic model system. Hepatic HBV mRNA content was reduced by up to 90% following administration of a single noncytopathic dose (100,000 U) of interleukin 2 (IL-2). Comparable effects were produced by administration of alpha and beta interferons (IFN-ca and IFN-,l), but only after multiple injections of at least 500,000 U per mouse. Importantly, the regulatory effect of IL-2 was completely blocked by the prior administration of antibodies to tumor necrosis factor alpha (TNF-a), which did not block the effect of IFN-ot or IFN-,1. In contrast to these observations, recombinant IFN--y, IL-1, IL-3, IL-6, TNF-P, transforming growth factor beta, and granulocyte-monocyte colony-stimulating factor were inactive in this system. These results suggest that selected inflammatory cytokines can down-regulate HBV gene expression in vivo by at least two pathways, one that is dependent on TNF-ot and another that is not. These results imply that antigen-nonspecific products of the intrahepatic HBV-specific inflammatory response may contribute to viral clearance or persistence during HBV infection.
STRUCTURE AND FUNCTION OF THE GRAM-NEGATIVE CELL ENVELOPE 615 MEMBRANE PHOSPHOLIPIDS OF E. COLI: AN OVERVIEW

STRUCTURE AND FUNCTION OF THE GRAM-NEGATIVE CELL ENVELOPE 615 MEMBRANE PHOSPHOLIPIDS OF E. COLI: AN OVERVIEW . 616 Extraction and Composition . 616 Formation of Common Precursors . 617 Fatty acids . 617 sn-Glycero-3-phosphate . 619 Other precursors . 619 Phospholipid Biosynthesis . 621 ENZYMOLOGY OF PHOSPHOLIPID SYNTHESIS . 622 Synthesis of Phosphatidic Acid and Cytidine 5'-Diphosphate Diglyceride . 622 Phosphatidic acid . 622 Cytidine 5'-diphosphate diglyceride . 624 Phosphatidylserine and Phosphatidylethanolamine . 624 Phosphatidylserine synthetase . 624 Phosphatidylserine decarboxylase 6.26 Phosphatidylglycerol and Cardiolipin . 626 Phosphatidylglycerophosphate synthetase . 626 Phosphatidylglycerophosphate phosphatase . 627 Cardiolipin synthetase 627 Phospholipid Turnover and Membrane-Derived Oligosaccharides . 628 Diglyceride Kinase . 629 Phospholipid Breakdown . 629 Detergent-resistant phospholipase A of the outer membrane . 630 Detergent-sensitive phospholipase A . 631 Lysophosphoipases . 631 Phospholipases C and D . 631 Other specific hydrolytic enzymes. (i) Phosphatidic acid phosphatase . 631 (ii) Cytidine 5'-diphosphate diglyceride hydrolase . 631 GENETIC MODIFICATION OF MEMBRANE LIPID SYNTHESIS . 631 sn-Glycero-3-Phosphate Auxotrophs and Mutants in Phosphatidic Acid Synthesis 632 Mutants in Phosphatidylethanolamine Synthesis . 634 Mutant isolation by colony autoradiography . 634 Phosphatidylserine synthetase . 635 Phosphatidylserine decarboxylase . 636 Mutants in Polyglycerophosphatide Synthesis 636 Phosphatidylglycerophosphate synthetase . 636 Cardiolipin synthetase 637 Mutants in Phospholipid Turnover and the Diglyceride Cycle 637 Genetic inhibition of polyglycerophosphatide turnover 637 Mutants in diglyceride kinase and role of the diglyceride cycle 637 Mutants in Catabolic Enzymes 638 Detergent-resistant phospholipase A . 638 Cloning of Genes Involved in Membrane Lipid Synthesis 638 REGULATION OF MEMBRANE LIPID SYNTHESIS AND ITS ROLE IN MEMBRANE ASSEMBLY 639 What Regulates Lipid Content and Rate of Lipid Synthesis? 639 Does Guanosine Tetraphosphate Play a Direct Role in Regulation of Lipid Synthesis? 640 What Regulates the Length and Unsaturation of Fatty Acids? 641 What Regulates the Ratio of Polar Headgroups in Membranes? 641 What Factors Activate Phospholipid Enzymes In Vivo? 642 What Coordinates Membrane Lipid, Membrane Protein, and Macromolecular Syntheses? 642
Direct Testing of Blood Cultures for Detection of the Serotype

Monoclonal antibodies (MAbs) reactive with serotype 5 and 8 capsular polysaccharides of Staphylococcus aureus have been used to test, by enzyme-linked immunosorbent assay (ELISA), blood culture fluids for the presence of S. aureus. A total of 748 blood cultures from 665 patients yielding 706 bacterial isolates belonging to more than 26 bacterial species were studied. Ail blood cultures containing bacterial strains belonging to species other than S. aureus were negative in ELISA. All 23 blood cultures containing serotype 5 S. aureus were positive in ELISA with the corresponding MAb. Out of 20 blood cultures containing serotype 8 S. aureus, 19 were positive with the corresponding MAb. AIl 5 blood cultures containing nontypeable S. aureus were negative in ELISA with both MAbs. This method provides reliable identification of serotype 5 or serotype 8 S. aureus by direct testing of blood culture fluids with ELISA.
Analysis of extractives from Pinus halepensis and Eucalyptus camaldulensis as predominant trees in Algeria

Abstract The lipophilic and hydrophilic extractives in the sapwood (sW) and heartwood (hW) of stems from Pinus halepensis Mill and Eucalyptus camaldulensis Dehnh trees grown in the north of Algeria were analyzed. The extraction of dried samples was carried out in an accelerated solvent extractor (ASE). The lipophilic substances were first extracted with n-hexane and then the hydrophilic ones with acetone/water. The extractives were analyzed by gas chromatography-flame ionization detection (GC-FID), GC-mass spectroscopy (MS) and high-performance size-exclusion chromatography (HPSEC). The largest amount of lipophilic extractives (≈13.4 mg g−1) was observed in the hW of P. halepensis, while the hW of E. camaldulensis contained the largest amount of hydrophilic extractives (≈116.3 mg g−1). Lipophilic extractives are mainly composed of oleoresins (resin acids, terpenes), fats (fatty acids, glycerides, steryl esters, sterols) and waxes (fatty alcohols). Hydrophilic extractives are composed of polyphenols (stilbenes, flavanols), sugars (monosaccharides) and sugar alcohols (cyclic polyols). The main identified lipophilic extractives are resin acids in pine and glycerides in eucalypt. The main identified hydrophilic extractives are cyclic polyols in pine and flavanols and monosaccharides in eucalypt. The total content of extractives is higher in hW than in sW.
Theoretical Investigation of Combustion and Performance Analysis of Diesel Engine under Low Load Conditions

Diesel engine is using prominently in islands and remote areas due to its reliability and stability for power generation. In recent years, most of the isolated power systems (e.g., islands and remote areas) have integrated renewable energies to reduce both the cost and pollution in diesel power generating system. However, due to intermittent and stochastic behaviour of renewable sources (e.g., solar and wind), it is unable to eliminate diesel generation entirely. In that case, low-load diesel operation (operation < 30% of maximum rated load) is particularly relevant for its ability to support higher levels of renewable penetration. In this paper, a thermodynamic model was developed using MATLAB for diesel engine combustion and performance. This model includes sub models such as heat release rate, heat transfer, double-Wiebe function, and ignition delay correlation. Engine thermal efficiency (TE), brake power (BP), indicated mean effective pressure (IMEP) and brake specific fuel consumption (BSFC) has been taken into consideration for performance analysis. The simulation results show that at 25% load, in-cylinder pressure and temperature are 168 bar and 2300 K which are the cause of lower heat release rate (74 J/deg) and longer ignition delay (0.25 ∼0.5 ms higher than that of conventional mode) and significantly responsible for lower efficiency (18%), brake power (4kW) and higher brake specific fuel consumption (1.2 g/kWh).
Adsorptive hydrogen chloride and combined hydrogen chloride–hydrogen sulphide removal from biogas for solid oxide fuel cell application

In order to reduce the toxic effect on solid oxide fuel cells performance caused by biogas contaminated with hydrogen chloride and hydrogen sulphide, the purification of biogas is essential. Adsorptive gas purification is a highly auspicious technology to provide pollution-free biogas for solid oxide fuel cell-based power units. In this work the authors examined the influence of different parameters onto the adsorption capacity of three commercially available sorbents. Experimental runs in a laboratory glass downflow fixed-bed reactor were carried out to analyse the adsorption capacity of a potassium carbonate impregnated activated carbon and two sorbents based on a mixture of aluminium oxide and silicon dioxide. Hydrogen chloride removal was accomplished with the impregnated activated carbon and metal oxide-based sorbents. Hydrogen chloride adsorption capacity was analysed under space velocities 8000 and 16,000 h−1. In addition, the effect of a hydrogen chloride inlet concentration of 100 and 1000 ppmv was investigated. Furthermore, pellets in the size of 3–4 mm in diameter were crushed into a fraction between 500 and 1000 µm to investigate the influence of particle size on hydrogen chloride adsorption capacity. Additionally, the combined adsorption of hydrogen chloride and hydrogen sulphide was realized using the impregnated activated carbon. The experimental runs and the results obtained in this work provide useful data for designing an adsorption reactor to clean up biogas and optimizing the process.