Miracle-dz/UniFAR-FTUs huggingface dataset:
Graphite pencil electrodes as electrochemical sensors for environmental analysis: a review of features, developments, and applications

Graphite pencil electrodes (GPEs) are carbon-based electrodes that are recognized by their low cost, simplicity, commercial availability, ease of modification and disposability. GPEs are attractive substrates for electrochemical sensing because of their unique feature of “disposability” compared to other commonly used carbon-based electrodes. Mechanically rigid GPEs are easy to modify and miniaturize. The sensitivity and selectivity of GPE toward certain analytes can be enhanced by applying different modification materials. The primary focus of this review article is to highlight the applications of GPEs in the analysis of inorganic and organic pollutants in different environmental matrices. This review gives a brief overview of the various types of inorganic and organic pollutants and their impact on the environment. The key features of modified GPEs that enhance their electrocatalytic activity toward detection of certain target analytes are critically appraised. In the end, we summarize the current status, weaknesses and future prospects of GPE based sensors for environmental analysis.
Redescription of a predatory and cannibalistic nematode, Butlerius butleri Goodey, 1929 (Rhabditida: Diplogastridae), from South Africa, including its first SEM study

Butlerius butleri was isolated during a survey on free-living soil nematodes from South Africa. The South African population of B. butleri is characterised by having a large stoma divided into two chambers and bearing a thorn-like dorsal tooth, spicules 44 (41-49) μm long, gubernaculum 29 (28-30) μm long, three pairs of precloacal papillae and five pairs of postcloacal papillae, and a filiform tail 280 (204-332) μm long in females, 310 (256-356) μm long in males. The SEM observation showed the cheilostom is divided into six conical plates 2.1-2.3 μm long. Nblast of 18S rDNA revealed 99% similarity and 6-7 bp differences with the B. butleri (KP453998) from Iran. Molecular analysis of B. butleri based on the sequence of the 18S and 28S rDNA placed it together with Butlerius and close to Pseudodiplogasteroides and Diplogasteroides. This species showed predatory and cannibalistic behaviours, feeding on other B. butleri in the substrate. SEM photographs of the species are presented for the first time.
Messinian Italian Bovidae revised: paleobiogeographic and biochronological implications

ABSTRACT Bovidae from the Messinian localities of Italian Peninsula are poorly known and documented except in the Monticino Quarry record (Brisighella, central Italy), which represents, therefore, a key locality for the understanding of Bovidae diversity and biogeography during the Messinian in Italy. In the present paper, the material published in the 1989 along with new, unpublished bovid material from Monticino Quarry are revised in order to clarify the taxonomic attribution of the Monticino’ bovids and to better understand their geographic and chronological distribution, as well as the Bovidae diversity in Italy during the Messinian. The updated and revised data on the Italian small, spiral-horned antelope from Monticino Quarry, and the additional specimens from Borro Strolla (Tuscany) and Verduno (Piedmont), suggests it has to be referred to the genus Oioceros, i.e., Oioceros occidentalis nov. comb. In addition, the presence of four other bovids at Monticino is attested here: Bovidae indet. (small-size), Bovinae indet. (medium-large size cf. Boselaphini), Bovinae indet. cf. Parabos, and Antilopinae indet. (medium size). The biochronological correlations and paleobiogeographic implications of these findings are discussed, suggesting a close affinity in faunal assemblage among the northern and central Italian latest Messinian localities and supporting the dispersal of bovids from East to West during the Messinian (before and during the Messinian Salinity Crisis).
Optimal subsampling for linear quantile regression models

Subsampling techniques are efficient methods for handling big data. Quite a few optimal sampling methods have been developed for parametric models in which the loss functions are differentiable with respect to parameters. However, they do not apply to quantile regression (QR) models as the involved check function is not differentiable. To circumvent the non‐differentiability problem, we consider directly estimating the linear QR coefficient by minimizing the Hansen–Hurwitz estimator of the usual loss function for QR. We establish the asymptotic normality of the resulting estimator under a generic sampling method, and then develop optimal subsampling methods for linear QR. In particular, we propose a one‐stage subsampling method, which depends only on the lengths of covariates, and a two‐stage subsampling method, which is a combination of the one‐stage sampling and the ideal optimal subsampling methods. Our simulation and real data based simulation studies show that the two recommended sampling methods always outperform simple random sampling in terms of mean square error, whether the linear QR model is valid or not.
Investigating Data Sharing in Speech Recognition for an Under-Resourced Language: The Case of Algerian Dialect

The Arabic language has many varieties, including its standard form, Modern Standard Arabic (MSA), and its spoken forms, namely the dialects. Those dialects are representative examples of under-resourced languages for which automatic speech recognition is considered as an unresolved issue. To address this issue, we recorded several hours of spoken Algerian dialect and used them to train a baseline model. This model was boosted afterwards by taking advantage of other languages that impact this dialect by integrating their data in one large corpus and by investigating three approaches: multilingual training, multitask learning and transfer learning. The best performance was achieved using a limited and balanced amount of acoustic data from each additional language, as compared to the data size of the studied dialect. This approach led to an improvement of 3.8% in terms of word error rate in comparison to the baseline system trained only on the dialect data.
What do they really think? the repertory grid technique as an educational research tool for revealing tacit cognitive structures

ABSTRACT The Repertory Grid Technique (RGT) is a qualitative method, based on the Personal Construct Psychology (PCP) theory, which provides a powerful tool to elicit tacit personal construction systems, with minimal intervention and interpretation. Although the contributory potential of the RGT as a cognitive research tool in science education has been documented, few researchers are familiar with it. In this article we describe in detail the principles and steps of the RGT, and how it can be utilised, including practical recommendations and analyzed examples. We illustrate how different studies in science education have utilised the diverse models of the RGT to address different research questions, and its advantages and contribution to the field. We hope to open a window to the PCP theory and the use of the RGT as a profound method for science education research, which may have implications for teaching and learning processes.
Chaotic Dynamics and Complexity in Real and Physical Systems

Emergence of chaos and complex behavior in real and physical systems has been discussed within the framework of nonlinear dynamical systems. The problems investigated include complexity of Child’s swing dynamics , chaotic neuronal dynamics (FHN model), complex Food-web dynamics, Financial model (involving interest rate, investment demand and price index) etc. Proper numerical simulations have been carried out to unravel the complex dynamics of these systems and significant results obtained are displayed through tables and various plots like bifurcations, attractors, Lyapunov exponents, topological entropies, correlation dimensions, recurrence plots etc. The significance of artificial neural network (ANN) framework for time series generation of some dynamical system is suggested.
Anxiety Amplifies Plasma Oxytocin Levels in Older Individuals with type 2 Diabetes. Findings from the Cross-Sectional KORA-Age Study.

PurposeBeyond its role in parturition, lactation, and emotion regulation, oxytocin (OXT) plays an important role in metabolism and energy homeostasis, although evidence is still limited. We investigated the association between endogenous OXT levels and type 2 diabetes mellitus (T2DM) and whether anxiety may modify its association.MethodsA cross-sectional analysis was conducted in 1006 participants aged 65-93 years (mean=75.9, SD ± 6.6) from the population-based KORA-Age study. Multivariable generalized linear regression analyses were performed to examine the association between non-extracted plasma OXT levels and T2DM with adjustments for potential confounders. ResultsAcross the OXT tertile groups, no substantial differences between sociodemographic, lifestyle, cardiometabolic or psychosocial factors were found except for multimorbidity. The differences between the OXT tertile groups with respect to obesity status were on the borderline of statistical significance (P=0.05). However, a significant statistical interaction between T2DM and anxiety on OXT levels was found (p = 0.03). In T2DM individuals with anxiety, substantially higher plasma OXT levels (Least Squares (LS) mean = 340.82 pg/ml, 95% CI 231.12-502.59) were observed compared to those without anxiety (217.08 pg/ml, 95% CI 190.93 – 247.99) (p=0.02). No significant association between T2DM and OXT levels in individuals without anxiety was found. ConclusionOXT levels were significantly elevated in T2DM subjects, particularly among older individuals with anxiety. The modifying role of anxiety highlights that anxiogenic stimuli may be associated with enhanced OXT signalling, particularly in subjects who suffer from T2DM as a severe pathological feature of dysregulated metabolism.
Dynamic behaviour of pavement on a two-parameter viscoelastic foundation subjected to loads moving with variable speeds

ABSTRACT The dynamic response of a multilayer finite plate resting on a two-parameter viscoelastic foundation to moving variable loads is obtained analytically/numerically. The governing differential equation of a multi-layer finite plate resting on a two-parameter viscoelastic foundation is derived firstly. Then, the dynamic response is derived analytically using mode superposition and Duhamel’s formula, followed by the solving of the numerical method. Next, the proposed solution is verified by comparing the degraded solution with both the field measurement data and the known theoretical results. Three different loading models are assessed to select the loading model that would provide insight into the effects of acceleration and deceleration. The effects of foundation parameters and vehicle parameters, especially the acceleration or deceleration and initial velocity of the moving load, on the dynamic response of the multilayer plate are compared through parametric studies. The numerical results suggest that acceleration and deceleration exert considerable effects on the dynamic response of the plate, and that the stiffness of pavement exposed to frequent acceleration and deceleration should be increased by at least 15% to counteract the effects of variable speed.
Voice or silence: antecedents of whistleblowing intentions

This study aims to examine the effects of peer ethical behavior and individual differences in valuation of fairness vs loyalty on whistleblowing intentions in academic settings. This study also tests the underlying mechanism responsible for the effects of peer behavior on reporting intentions, namely, fear of reprisal. ,A survey was conducted with 947 undergraduate students. The model was tested using ordinary least squares regression models followed by bootstrapped mediation analyses. ,Results showed that the effects of peer ethical behavior on whistleblowing intentions are mediated by fear of retaliation. Moreover, the findings indicated that, for low-severity transgressions, there is an interactive effect between fear of retaliation and endorsement of fairness over loyalty on whistleblowing intentions. ,When the misconduct is seen as minor, a potential whistleblower may understand that the expected costs outweigh the possible benefits of blowing the whistle. In such situations, higher fear of retaliation would undermine the effects of individual’s endorsement of fairness over loyalty on reporting intentions. ,As the social environment significantly affects someone’s whistleblowing intentions, there should be visible efforts to improve and to foster an ethical infrastructure in organizations. ,As fear of retaliation by peers is one of the most important determinants affecting the decision to report misconduct in general, there must be serious efforts from leaders to mitigate any threat of retaliation to those who come forward. ,This work contributes to the discussion about individual and situational antecedents of whistleblowing. More importantly, it sheds light on one potential boundary condition for the influence of the fairness–loyalty tradeoff on whistleblowing decisions: severity of the transgression. The findings provide initial evidence that, for low-severity transgressions, fear of retaliation weakens the positive effects of one’s moral compass in terms of preference for fairness over loyalty on whistleblowing intentions.
Assessment of HCMV-encoded microRNAs in plasma as potential biomarkers in pregnant women with adverse pregnancy outcomes

Background Human cytomegalovirus (HCMV) is the most frequent cause of congenital infections and can lead to adverse pregnancy outcomes (APOs). HCMV encodes multiple microRNAs (miRNAs) that have been reported to be partially related to host immune responses, cell cycle regulation, viral replication, and viral latency, and can be detected in human plasma. However, the relevance for HCMV-encoded miRNAs in maternal plasma as an indicator for APOs has never been evaluated. Methods Expression profiles of 22 HCMV-encoded miRNAs were first measured in plasma samples from 20 pregnant women with APOs and 28 normal controls using quantitative reverse-transcription polymerase chain reaction. Next, markedly changed miRNAs were validated in another independent validation set consisting of 20 pregnant women with APOs and 27 control subjects. Markedly changed miRNAs were further assessed in the placenta tissues. HCMV DNA in peripheral blood leukocytes (PBLs) and anti-HCMV immunoglobulin M (IgM) and anti-HCMV immunoglobulin G (IgG) in plasma were also examined in both training and validation sets. Diagnostic value and risk factors were compared between APO cohorts and normal controls. Results Analysis of the training and validation data sets revealed that plasma concentrations of hcmv-miR-UL148D, hcmv-miR-US25-1-5p and hcmv-miR-US5-1 were significantly increased in pregnant women with APOs compared with normal controls. Hcmv-miR-US25-1-5p presented the largest area under the receiver-operating characteristic (ROC) curve (AUC) (0.735; 95% CI, 0.635–0.836), with a sensitivity of 68% and specificity of 71%. Furthermore, plasma levels of hcmv-miR-US25-1-5p and hcmv-miR-US5-1 correlated positively with APOs (P=0.029 and 0.035, respectively). Hcmv-miR-US25-1-5p in the placenta tissues were dramatically increased in APOs, and correlated with plasma hcmv-miR-US25-1-5p. Nevertheless, neither the concentration of HCMV DNA in PBLs nor the positivity rates of anti-HCMV IgM and anti-HCMV IgG in plasma showed a statistically significant correlation with APOs. Conclusions We identified a unique signature of HCMV-encoded miRNAs in pregnant women with APOs that may be useful as a potential noninvasive biomarker for predicting and monitoring APOs during HCMV infection.
Design and implementation of I‐slot conformal circular patch antenna on sphere structure

In this article, an I‐slot circular patch antenna conformed on a spherical structure is proposed. For the implementation of the proposed antenna, the polylactic acid (PLA) material is used with the help of a 3D printer. In accordance with this purpose, we determine the permittivity value of the PLA with a T‐resonator method before the design process. Then, the geometrical design of the spherical patch antenna is optimized by means of a differential evolution algorithm. After the design and optimization process, the conformal spherical patch antenna is fabricated on a sphere cap. The main characteristics of the proposed antenna are given for both the simulations and the measurements. It is seen that the simulation results agree well with the measurement results. Furthermore, an experiment is performed in order to examine the application possibility of the presented spherical antenna. For this experiment, a spherical communication module with the proposed antenna and an inner wireless transmitter system is built. In this experiment, the spherical module is rolled down a slope while it continuously transmits pseudo‐random numbers. The data are received by a receiver station at the top of the slope. The received data are evaluated in terms of the amount of received packets per unit of time. The numerical results indicate that the proposed antenna can be used for dynamic spherical systems such as throwable objects and spherical robots.
The impacts of community-based water development projects on rural poverty among small-holder farmers: Evidence from the Ewaso Ng’iro North Catchment Area, Kenya

Abstract The main challenge with respect to water in the rural setting, lies in access, control and management. Collective action has been taken up following the International Water Management (IWM) principles and institutionalized in the Kenyan legal framework through water resource users’ associations (WRUAs). We carried out this study to assess whether this collective action has any impact on household poverty using objective poverty measures (consumption and income), a subjective poverty measure and a water poverty measure. We used 2019 household survey data of 652 randomly selected rural households from the Upper Ewaso Ng’iro North Catchment Area. We employed the full information maximum likelihood endogenous probit regression model to obtain the impact of WRUA membership on household poverty status. We find that collective water management can have welfare improving impacts for rural households, especially where there low public investments in water provision, management and access. We recommend that WRUAs be empowered through financial, legal and capacity building interventions to enhance their community impacts.
Modelling the atmospheric chemistry of volcanic plumes

Abstract Volcanoes are the principal way by which volatiles are transferred from the solid Earth to the atmosphere-hydrosphere system. Once released into the atmosphere, volcanic emissions rapidly undergo a complex series of chemical reactions. This thesis seeks to further the understanding of such processes by both observation and numerical modelling. I have adapted WRF-Chem to model passive degassing from Mount Etna, the chemistry of its plume, and its influence on the wider atmosphere. This investigation considers model plumes from the point of emission up to a day’s travel from the vent and is able to reproduce observed phenomena of BrO formation and O3 depletion within volcanic plumes. The model plume influences several atmospheric chemistry systems, including reactive nitrogen and organic chemistry. Plume chemistry is driven by sunlight, and I examine how the modelled phenomena identified in this investigation vary with the diurnal cycle. In the modelled plume all of the bromine is involved in O3-destructive cycling. When HBr is exhausted, volcanic HCl sustains the cycling. The rate-limiting factor of this cycling, and therefore the rate of O3 destruction, is sunlight. I find qualitative differences between the chemistry of low and high intensity plumes, with the bromine chemistry in the latter case being limited by O3 depletion. This modelling investigation is complemented by an observational study of O3 in a young Etnean plume from which I estimate the rate of in-plume O3 destruction within seconds to minutes after emission. These investigations demonstrate that volcanic plumes can be included in complex, 3D atmospheric chemistry models, and that the output from these can be used to observe and quantify influences of volcanic plumes on the wider atmosphere.
Contextual Information-Preserved Architecture Learning for Remote-Sensing Scene Classification

Convolutional neural networks (CNNs) have recently been widely used in remote-sensing scene classification. Additionally, it is becoming very popular to automatically learn specific CNN architectures for specific data sets. The rich contextual information in high-resolution remote-sensing images (RSIs) is critical to remote-sensing intelligent understanding tasks. However, architecture learning approaches tend to simplify the original data (i.e., resizing images to smaller resolution) for efficiency, yet result in contextual information loss of RSIs. In this article, we proposed a contextual information-preserved architecture learning (CIPAL) framework for remote-sensing scene classification to utilize the contextual information in RSIs as much as possible during the architecture learning process. We introduce channel compression into CIPAL, which can reduce the memory and time consumption of architecture learning and make it possible to construct a larger architecture space. We add potential operators that are rarely used for scene classification tasks (i.e., atrous convolution) into the architecture space to explore unknown architectures that are more suitable for remote-sensing scenes. The experimental results on four remote-sensing scene classification benchmarks indicate that CIPAL learns architectures with less time consumption than similar works, and the newly found architectures outperform popular hand-designed architectures for better use of contextual information in RSIs. Different architectures are good at learning different representations, and our proposed architecture learning method potentially helps us understand which types of representations are crucial for RSI intelligent understanding.
Psychometric Properties of the Persian Version of the Weight Control Strategies Scale (WCSS)

Objective: The purpose of the present study was to examine the validity and reliability of the Persian version of the Weight Control Strategies Scale among individuals engaged in weight loss or weight maintenance. Method : This descriptive study conducted from October 2019 to February 2020 on social media networks. A total of 420 men and women were selected using consecutive sampling. They completed the Persian version of the Weight Control Strategies Scale and the Self-Compassion Scale. Data were analyzed using descriptive statistics, Cronbach’s α, confirmatory factor analysis, and Pearson product-moment correlations. Results: Internal consistency for the total score of the Persian version of Weight Control Strategies Scale was excellent and acceptable to good for all 4 subscales (in all cases over α = 0.70). Confirmatory factor analysis supported the factor structure of the original model of the scale, but, it was different from the model at the item level. Moreover, the Persian version of Weight Control Strategies Scale had good convergent validity. Conclusion: Psychometrically speaking, the Persian version of the Weight Control Strategies Scale is a valid and reliable tool to assess the psychological and behavioral profile of individuals engaging in losing or maintaining weight, both for clinical and research purposes.