Miracle-dz/UniFAR-FTUs huggingface dataset:
Situated Accounts: Qualitative Interviews with Women Educational Managers

Abstract Generally, researchers do seem to pay attention to the manner in which social and contextual attributes may transform interpersonal sensitivities and communication in the interview. This paper argues that qualitative interviews cannot be divorced from their contexts and therefore it is a ‘situated account’. This means that the interview is shaped by the fact that the ‘cast’ is the researcher, that particular woman/man, and that it is happening in a particular place, at a particular time, in response to particular shaping questions. Ten methodological issues are highlighted by the description of interview processes of the case study that explored the subjective accounts of five of the six women who were principals of secondary schools in Venda, Limpopo Province in South Africa, in 1996, in order to understand how they accessed managerial positions. The methodological issues discussed confirm that an interview cannot be separated from its context. Thus the interviewer must be aware of the contextual factors and be able to go around them. The article suggests that maintaining a “situated friendship” and employing reflexive approach as a form of localism can reduce the risk of ‘harmful effects’ when doing qualitative interviewing.
An investigation of Cyberchondria in ‘The Age of Risk’

The importance of this paper arises in light of the increasing frequency for consumers to approach online sources about symptoms of illness, a process that has previously been described as 'Cyberchondria'. Critics are increasingly questioning the quality of interactive health information in 'The Age of Risk'. Research in this field is often concerned with a focus on the negatives of the Internet. This raises questions from sociological and feminist academics as to whether the Internet is a direct mediator of health and illness information, or whether there are other social and cultural factors involved which contribute to the risk of the ‘prosumer’. This paper approaches these problems discussing the importance of implementing software quality measures to control the potential negative effects of the information on those who are entering the information with a negative ‘lay epistemology’. Drawing on techniques of discourse analysis, qualitative data was collected in interviews concerning laypeople’s use of health and illness channels. This paper identifies the system that laypeople use in gathering knowledge from a number of sources in order to form their own ‘lay epistemology’. Using the method of ‘intersectionality’, cultural and socially constructed categories have been used in analysis. This paper suggests that although the Internet is a major source of information, there are decisions which the layperson makes prior to this approach which affect their discernment of their findings. This paper looks at how consumers differ in their interpretation of this information which aids academics in the development of systems to protect those groups that are vulnerable.
NLRP1 Functions Downstream of the MAPK/ERK Signaling via ATF4 and Contributes to Acquired Targeted Therapy Resistance in Human Metastatic Melanoma

The BRAF V600E mutation leads to constitutive activation of the mitogen-activated protein kinase (MAPK)/extracellular signal-regulated kinase (ERK) pathway and its downstream effector responses. Uncovering the hidden downstream effectors can aid in understanding melanoma biology and improve targeted therapy efficacy. The inflammasome sensor, NACHT, LRR, and PYD domains-containing protein 1 (NLRP1), is responsible for IL-1β maturation and itself is a melanoma tumor promoter. Here, we report that NLRP1 is a downstream effector of MAPK/ERK signaling through the activating transcription factor 4 (ATF4), creating regulation in metastatic melanoma cells. We confirmed that the NLRP1 gene is a target of ATF4. Interestingly, ATF4/NLRP1 regulation by the MAPK/ERK pathway uses distinct mechanisms in melanoma cells before and after the acquired resistance to targeted therapy. In parental cells, ATF4/NLRP1 is regulated by the MAPK/ERK pathway through the ribosomal S6 kinase 2 (RSK2). However, vemurafenib (VEM) and trametinib (TRA)-resistant cells lose the signaling via RSK2 and activate the cAMP/protein kinase A (PKA) pathway to redirect ATF4/NLRP1. Therefore, NLRP1 expression and IL-1β secretion were downregulated in response to VEM and TRA in parental cells but enhanced in drug-resistant cells. Lastly, silencing NLRP1 in drug-resistant cells reduced their cell growth and inhibited colony formation. In summary, we demonstrated that NLRP1 functions downstream of the MAPK/ERK signaling via ATF4 and is a player of targeted therapy resistance in melanoma. Targeting NLRP1 may improve the therapeutic efficacy of targeted therapy in melanoma.
Correlation between flexibility of chain-like polyelectrolyte and thermodynamic properties of its solution

Structural and thermodynamic properties of the model solution containing charged oligomers and the equivalent number of counterions were studied by means of the canonical Monte Carlo simulation technique. The oligomers are represented as (flexible) freely jointed chains or as a linear (rigid) array of charged hard spheres. In accordance with the primitive model of electrolyte solutions, the counterions are modeled as charged hard spheres and the solvent as dielectric continuum. Significant differences in the pair distribution functions, obtained for the rigid (rod-like) and flexible model are found but the differences in thermodynamic properties, such as, enthalpy of dilution and excess chemical potential, are less significant. The results are discussed in light of the experimental data an aqueous polyelectrolyte solutions. The simulations suggest that deviations from the fully extended (rod-like) conformation yield slightly stronger binding of counterions. On the other hand, the flexibility of polyions, even when coupled with the ion-size effects, cannot be blamed for qualitative differences between the theoretical results and experimental data for enthalpy of dilution.
Expanding the Clinical and Genetic Spectrum of RAB28-Related Cone-Rod Dystrophy: Pathogenicity of Novel Variants in Italian Families

The small Ras-related GTPase Rab-28 is highly expressed in photoreceptor cells, where it possibly participates in membrane trafficking. To date, six alterations in the RAB28 gene have been associated with autosomal recessive cone-rod dystrophies. Confirmed variants include splicing variants, missense and nonsense mutations. Here, we present a thorough phenotypical and genotypical characterization of five individuals belonging to four Italian families, constituting the largest cohort of RAB28 patients reported in literature to date. All probands displayed similar clinical phenotype consisting of photophobia, decreased visual acuity, central outer retinal thinning, and impaired color vision. By sequencing the four probands, we identified: a novel homozygous splicing variant; two novel nonsense variants in homozygosis; a novel missense variant in compound heterozygous state with a previously reported nonsense variant. Exhaustive molecular dynamics simulations of the missense variant p.(Thr26Asn) in both its active and inactive states revealed an allosteric structural mechanism that impairs the binding of Mg2+, thus decreasing the affinity for GTP. The impaired GTP-GDP exchange ultimately locks Rab-28 in a GDP-bound inactive state. The loss-of-function mutation p.(Thr26Asn) was present in a compound heterozygosis with the nonsense variant p.(Arg137*), which does not cause mRNA-mediated decay, but is rather likely degraded due to its incomplete folding. The frameshift p.(Thr26Valfs4*) and nonsense p.(Leu13*) and p.(Trp107*) variants, if translated, would lack several key structural components necessary for the correct functioning of the encoded protein.
Detailed molecular dynamics simulation of the self-diffusion of n-alkane and cis-1,4 polyisoprene oligomer melts

Results are presented for the self-diffusion properties of monodisperse n-alkanes and cis-1,4 polyisoprene (PI) oligomer melts, as obtained through detailed atomistic molecular dynamics (MD) simulations. The simulations have been conducted in the NVT statistical ensemble on model systems thoroughly pre-equilibrated through an efficient Monte Carlo (MC) algorithm. Results for the self-diffusion coefficient D as a function of molecular weight M support a scaling law of the form D∼Mb, with b strongly depending on temperature T, for both the n-alkanes and the cis-1,4 PI melts. The simulation results have been fitted to an expression for D involving elements of Rouse dynamics and Cohen–Turnbull–Bueche chain-end (excess free volume) effects, proposed recently by von Meerwall et al. [J. Chem. Phys. 108, 4299 (1998)]. Using a geometric analysis involving tessellation of space in Delaunay tetrahedra developed by Greenfield and Theodorou [Macromolecules 26, 5461 (1993)], we have also calculated the excess chain-end.
Decision-making in early breast cancer : guidelines and decision tools

The meta-analysis of trials of adjuvant systemic therapy for early breast cancer provides robust information on the impact of both cytotoxic chemotherapy and tamoxifen on relapse-free and overall survival to 15 years from diagnosis. These data are described in terms of relative risk reduction and are not meant to be viewed as a prescription for therapy. To translate relative risk reductions into absolute benefits for the individual patient and then trade off the gains against the long-term and short-term sideeffects and toxicities is a highly complex process for the clinician, and current guidelines are formatted in such a way that they fail to use current information in a way that allows a quantitative assessment of the benefits and risks of adjuvant therapy. This review article explores current guidelines and describes some aids that may be used to help inform women about their treatment options for early breast cancer. # 2002 Elsevier Science Ltd. All rights reserved.
Modelling financial development and electricity consumption nexus for Ghana

The paper contributes to the body of knowledge in the area of energy consumption and financial sector development by empirically assessing the long run and short run links and causality between electricity consumption and financial development (proxied by credit to the private sector). The paper is based on quantitative causal study using time series data from 1970-2011. Data were analysed using Autoregressive Distributed Lag Model (ARDL) and Granger Causality Test. There is significant cointegration relationship among the series variables in the model estimated. There is no statistical significant long run and short run relationship between financial development (proxied by credit to the private sector) and electricity consumption. There is bidirectional causality between financial development and electricity consumption. This calls for future studies to contribute to the debate by assessing structural breaks in the series. Policy makers should consider these findings in planning for electricity consumption to avoid unplanned energy shortage which might have adverse effect on the economy.
Multiscale space-time-frequency feature-guided multitask learning CNN for motor imagery EEG classification

Objective. Motor imagery (MI) electroencephalography (EEG) classification is regarded as a promising technology for brain–computer interface (BCI) systems, which help people to communicate with the outside world using neural activities. However, decoding human intent accurately is a challenging task because of its small signal-to-noise ratio and non-stationary characteristics. Methods that directly extract features from raw EEG signals ignores key frequency domain information. One of the challenges in MI classification tasks is finding a way to supplement the frequency domain information ignored by the raw EEG signal. Approach. In this study, we fuse different models using their complementary characteristics to develop a multiscale space-time-frequency feature-guided multitask learning convolutional neural network (CNN) architecture. The proposed method consists of four modules: the space-time feature-based representation module, time-frequency feature-based representation module, multimodal fused feature-guided generation module, and classification module. The proposed framework is based on multitask learning. The four modules are trained using three tasks simultaneously and jointly optimized. Results. The proposed method is evaluated using three public challenge datasets. Through quantitative analysis, we demonstrate that our proposed method outperforms most state-of-the-art machine learning and deep learning techniques for EEG classification, thereby demonstrating the robustness and effectiveness of our method. Moreover, the proposed method is employed to realize control of robot based on EEG signal, verifying its feasibility in real-time applications. Significance. To the best of our knowledge, a deep CNN architecture that fuses different input cases, which have complementary characteristics, has not been applied to BCI tasks. Because of the interaction of the three tasks in the multitask learning architecture, our method can improve the generalization and accuracy of subject-dependent and subject-independent methods with limited annotated data.
Co-Catalytic Action of Faceted Non-Noble Metal Deposits on Titania Photocatalyst for Multielectron Oxygen Reduction

In order to clarify the reason of often reported low photocatalytic activity of rutile titania compared to that of anatase titania and the sluggish kinetics for oxygen reduction of rutile titania, in this study, faceted copper(I) oxide (Cu2O) particles (FCPs), i.e., cube, cuboctahedron and octahedron, were deposited onto rutile particles by an in-situ wet chemical method, and the co-catalytic action of FCPs was studied in the oxidative decomposition of acetic acid. The oxygen reduction reaction kinetics of bare and FCP-loaded titania samples in photodecomposition of organic compounds were investigated by light-intensity dependence measurement. FCPs serve as the specific sites (sink) which accumulate excited electrons to drive multielectron oxygen reduction reactions, as the counter reaction in photodecomposition of organic compounds by positive holes, which significantly improves the photocatalytic activity of rutile titania particles.
Cutaneous Carotenoid Level Measured by Multiple Spatially Resolved Reflection Spectroscopy Sensors Correlates with Vegetable Intake and Is Increased by Continual Intake of Vegetable Juice

Although vegetables are beneficial for human health, in many countries, the recommended vegetable intake is not reached. To assess vegetable intake, it is important to understand vegetable consumption. Therefore, we conducted a cross-sectional and intervention study of 26 healthy individuals (50% women; 37.0 ± 8.9 years) and estimated vegetable intake on the basis of the cutaneous carotenoid level (CCL) with a noninvasive skin carotenoid sensor, considering that vegetable juice intake can increase CCL. Participants consumed vegetable juice containing 350 g of vegetables daily for 4 weeks. Blood carotenoid levels and CCL were measured for 12 weeks. Cross-sectional analysis showed a significant positive correlation between CCL and vegetable intake (r = 0.489). Vegetable juice consumption significantly increased CCL and the blood levels of α-carotene, β-carotene, and lycopene (p < 0.05). The correlation coefficient between the blood level and CCL for lycopene was smaller (r = 0.001) compared to that between the blood level and CCL for α-carotene (r = 0.523) and β-carotene (r = 0.460), likely because of bioavailability differences. In conclusion, noninvasive skin carotenoid measurements are effective for determining vegetable intake, and vegetable juice significantly increases CCL.
Data Mining Critical Infrastructure Systems : Models and Tools

Critical infrastructures (CIs) such as power, water, transportation, and telecommunication are highly complex interacting systems that are vital to national security, economy and public life. They play an important role in several core urban computing challenges. Advances in computing resources and techniques have led to enormous progress in developing intelligent frameworks for analyzing these large heterogeneous systems. In this article, we survey state-of-the-art and foundational work in this upcoming area from a data mining perspective. We discuss basic concepts of CIs, their properties, impacts on them due to natural or human-caused disturbances and different computational methodologies used for modeling and understanding their behavior. We also discuss recent work that specifically deals with two critical sectors of CIs, namely power and transportation systems. Finally, we also describe several existing tools and methods that are used to facilitate decision making for domain operators, enable efficient and faster disaster response for federal and state agencies and help improve the security and resiliency of these CIs.
Hellman CLIENT Client Random Server Random Premaster Secret Session Keys MAC Secrets IVs SERVER Client Random Server Random ClientHello ServerHello

Cryptographic libraries that implement Transport Layer Security (TLS) have a responsibility to delete cryptographic keys once they’re no longer in use. Any key that’s left in memory can potentially be recovered through the actions of an attacker, up to and including the physical capture and forensic analysis of a device’s memory. This paper describes an analysis of the TLS library stack used in recent Android distributions, combining a C language core (BoringSSL) with multiple layers of Java code (Conscrypt, OkHttp, and Java Secure Sockets). We first conducted a black-box analysis of virtual machine images, allowing us to discover keys that might remain recoverable. After identifying several such keys, we subsequently pinpointed undesirable interactions across these layers, where the higherlevel use of BoringSSL’s reference counting features, from Java code, prevented BoringSSL from cleaning up its keys. This interaction poses a threat to all Android applications built on standard HTTPS libraries, exposing master secrets to memory disclosure attacks. We found all versions we investigated from Android 4 to the latest Android 8 are vulnerable, showing that this problem has been long overlooked. The Android Chrome application is proven to be particularly problematic. We suggest modest changes to the Android codebase to mitigate these issues, and have reported these to Google to help them patch the vulnerability in future Android systems.
“Down the Rabbit Hole” of Vaccine Misinformation on YouTube: Network Exposure Study

Background Social media platforms such as YouTube are hotbeds for the spread of misinformation about vaccines. Objective The aim of this study was to explore how individuals are exposed to antivaccine misinformation on YouTube based on whether they start their viewing from a keyword-based search or from antivaccine seed videos. Methods Four networks of videos based on YouTube recommendations were collected in November 2019. Two search networks were created from provaccine and antivaccine keywords to resemble goal-oriented browsing. Two seed networks were constructed from conspiracy and antivaccine expert seed videos to resemble direct navigation. Video contents and network structures were analyzed using the network exposure model. Results Viewers are more likely to encounter antivaccine videos through direct navigation starting from an antivaccine video than through goal-oriented browsing. In the two seed networks, provaccine videos, antivaccine videos, and videos containing health misinformation were all found to be more likely to lead to more antivaccine videos. Conclusions YouTube has boosted the search rankings of provaccine videos to combat the influence of antivaccine information. However, when viewers are directed to antivaccine videos on YouTube from another site, the recommendation algorithm is still likely to expose them to additional antivaccine information.
Human capital, trade, FDI and economic growth in Thailand: what causes what?

We investigate the causal links between human capital, openness through trade and FDI, and economic growth using quarterly data for Thailand over the period 1973:2-2000:4. A number of hypotheses are investigated including, in particular, FDI-led growth and export-led growth, as well as the reverse linkages from growth to FDI and exports. The importance of human capital is highlighted as complementary to trade and FDI inflows, underlying the importance of technology adoption. We find that, after controlling for domestic investment, government expenditure and imports, support for FDI-led growth is not as strong as export-led growth, although allowing for the joint interaction of FDI and human capital reveals a positive FDI effect above a minimum threshold of human capital, estimated to be around 4.5 years of average secondary schooling attainment. Extending our study using multivariate causality tests conducted within a vector error correction framework, we also find significant effects of domestic investment and trade openness, providing support for import-led growth, but direct support for FDI-led growth as well as growth-led FDI is again relatively weak, reinforcing the conclusion that trade openness has played a more significant role than FDI in influencing Thai economic growth. But the results reveal a subtle role for technology transfer through the complementary effect of trade on FDI, and FDI on government expenditure, which thereby influences human capital development with spillovers onto domestic investment and growth. This leads us to argue that there is a potential role for FDI interacting with human capital in influencing the future development of the Thai economy, given its recently active policy of FDI promotion.