Miracle-dz/UniFAR-FTUs huggingface dataset:
Understanding black issues in postgraduate counsellor training

This paper presents a brief account of a qualitative multicultural study and heuristic exploration of how trainee counsellors understand black issues in their training and in their therapeutic work with clients. This initiative is supported by a previous survey of black clients and therapists who suggest that changes are needed in training. It presents current legislation and need for equalities in Higher Education and counsellor training, by challenging the dominance of Eurocentric approaches. A pluralistic, flexible Action Research methodology will be outlined. The theory and context of previous studies are presented. Phases of the process are described to show how this study was approached. Phase one describes how interviews with a variety of experienced practitioners confirmed the need for the study. Using examples of trainees’ narratives, phase two describes how the phenomenon of black issues was integrated into training and the process of generating data. The paper shows how the explication process reveals elements of fear, history, guilt and racism, present in the dynamic of black issues. The paper highlights how racism features highly in trainees’ concerns and influences their ability to share and understand. A snapshot of emerging concepts such as ‘finding a voice’ and ‘recognition trauma’ which are developed to assist the reflexive process is featured. The role of the researcher and black trainees as ‘black expert’ is discussed. In the context of ethical concerns and working through the researcher’s counter transference as a black female tutor researcher, the process of modelling within a participatory role is described. An excerpt from a discussion with colleagues gives an essence of the outcome. The outcome is summarised in the conclusion:’A bridge from fear to transformation’. The study enabled both trainees and staff as collaborators to shift from a position of fear and not knowing to engaging in active dialogue about black issues on a personal and professional basis.
Convex Regularization Method for Solving Cauchy Problem of the Helmholtz Equation

In this paper, we introduce the Convex Regularization Method (CRM) for regularizing the (instability) solution of the Helmholtz equation with Cauchy data. The CRM makes it possible for the solution of Helmholtz equation to depend continuously on the small perturbations in the Cauchy data. In addition, the numerical computation of the reg- ularized Helmholtz equation with Cauchy data is stable, accurate and gives high rate of convergence of solution in Hilbert space. Undoubtedly, the error estimated analysis associated with CRM is minimal. Mathematics Subject Classi cation : 44B28; 44B30 Keywords : Convex Regularization Method, ill-posed Helmholtz equation with Cauchy data, stable solution
Interactive comment on “ Insight into collision zone dynamics from topography : numerical modelling results and observations ” by A

1 The models are dynamic models – and I note that the subduction phase has unrealistic time dependence – see figure 4D; there is no case of subduction increasing from 10 to 30cm/yr over a few million years and then slowing to <5cm/yr in less than another few million years. The question in one’s mind is – is this model suitable? How does the answer differ with differing initial conditions? This could be addressed by trying to develop a more realistic initial condition behaviour – or at least compare a few different C407
Early Oligocene Foraminifera from Kap Brewster, East Greenland

Otwornice dolnego oligocenu z Kap Brewster, wschodnia Grenlandia Early Oligocene foraminiferal assemblages from the shallow-marine Krabbedalen Formation (Kap Dalton Group) at Kap Brewster, East Greenland, yielded 33 foraminiferal species, belonging to 23 genera and 17 families. Agglutinated foraminifera dominate the assemblage. Their large, well-cemented tests, are usually composed of coarse sand grains. Calcareous benthos is second in frequency, calcareous plankton (one species) and other microfossils are a rare admixture. The unusually large test size of some agglutinated foraminifera, particularly those of Cyclammina cancellata Brady and Reophax pilulifer Brady, are interpreted as a response to cooling of the Early Oligocene coastal sea by the East Greenland Current.
Initial Harm Reduction by N-Acetylcysteine Alleviates Cartilage Degeneration after Blunt Single-Impact Cartilage Trauma in Vivo

Joint injuries are highly associated with the development of post-traumatic osteoarthritis. Previous studies revealed cell- and matrix-protective effects of N-acetylcysteine (NAC) after ex vivo cartilage trauma, while chondroanabolic stimulation with bone morphogenetic protein 7 (BMP7) enhanced type II collagen (COL2) expression. Here, as a next step, we investigated the combined and individual efficacy of intra-articular antioxidative and chondroanabolic treatment in a rabbit in vivo cartilage trauma model. Animals were randomly divided into group A (right joint: trauma (T); left joint: T+BMP7) and group B (right joint: T+NAC; left joint: T+BMP7+NAC). Condyles were impacted with the use of a spring-loaded impact device to ensure defined, single trauma administration. After 12 weeks, histopathological analysis was performed and the presence of matrix metalloproteinase 13 (MMP-13) and COL2 was assessed. Trauma-induced hypocellularity, MMP-13 expression, and cell cluster formation were reduced in NAC-treated animals. In contrast, BMP7 further increased cluster formation. Moreover, synovial concentrations of COL2 carboxy propeptide (CPII) and proteoglycan staining intensities were enhanced in NAC- and NAC+BMP7-treated joints. For the first time, the efficacy of NAC regarding early harm reduction after blunt cartilage trauma was demonstrated in vivo. However, parallel administration of BMP7 was not significantly superior compared to NAC alone.
The periglacial engine of mountain erosion – Part 2: Modelling large-scale landscape evolution

Abstract. There is growing recognition of strong periglacial control on bedrock erosion in mountain landscapes, including the shaping of low-relief surfaces at high elevations (summit flats). But, as yet, the hypothesis that frost action was crucial to the assumed Late Cenozoic rise in erosion rates remains compelling and untested. Here we present a landscape evolution model incorporating two key periglacial processes – regolith production via frost cracking and sediment transport via frost creep – which together are harnessed to variations in temperature and the evolving thickness of sediment cover. Our computational experiments time-integrate the contribution of frost action to shaping mountain topography over million-year timescales, with the primary and highly reproducible outcome being the development of flattish or gently convex summit flats. A simple scaling of temperature to marine δ18O records spanning the past 14 Myr indicates that the highest summit flats in mid- to high-latitude mountains may have formed via frost action prior to the Quaternary. We suggest that deep cooling in the Quaternary accelerated mechanical weathering globally by significantly expanding the area subject to frost. Further, the inclusion of subglacial erosion alongside periglacial processes in our computational experiments points to alpine glaciers increasing the long-term efficiency of frost-driven erosion by steepening hillslopes.
Metagenomic Insights into the Bacterial Functions of a Diesel-Degrading Consortium for the Rhizoremediation of Diesel-Polluted Soil

Diesel is a complex pollutant composed of a mixture of aliphatic and aromatic hydrocarbons. Because of this complexity, diesel bioremediation requires multiple microorganisms, which harbor the catabolic pathways to degrade the mixture. By enrichment cultivation of rhizospheric soil from a diesel-polluted site, we have isolated a bacterial consortium that can grow aerobically with diesel and different alkanes and polycyclic aromatic hydrocarbons (PAHs) as the sole carbon and energy source. Microbiome diversity analyses based on 16S rRNA gene showed that the diesel-degrading consortium consists of 76 amplicon sequence variants (ASVs) and it is dominated by Pseudomonas, Aquabacterium, Chryseobacterium, and Sphingomonadaceae. Changes in microbiome composition were observed when growing on specific hydrocarbons, reflecting that different populations degrade different hydrocarbons. Shotgun metagenome sequence analysis of the consortium growing on diesel has identified redundant genes encoding enzymes implicated in the initial oxidation of alkanes (AlkB, LadA, CYP450) and a variety of hydroxylating and ring-cleavage dioxygenases involved in aromatic and polyaromatic hydrocarbon degradation. The phylogenetic assignment of these enzymes to specific genera allowed us to model the role of specific populations in the diesel-degrading consortium. Rhizoremediation of diesel-polluted soil microcosms using the consortium, resulted in an important enhancement in the reduction of total petroleum hydrocarbons (TPHs), making it suited for rhizoremediation applications.
A strategy to interface isogeometric analysis with Lagrangian finite elements - application to fluid-structure interaction problems

Isogeometrically enriched finite elements offer efficient localized isogeometric analysis (IGA) enrichment for numerical simulations involving large computational domains. This is achieved by employing surface enriched elements to interface isogeometric elements with classical Langrangian finite elements. In this paper, we explore their applicability and merits for fluid-structure interaction (FSI) analysis. The implemented approach not only offers an enrichment of the finite element space, but also offers a framework for discretizing and analyzing fluid and structure with different finite element approaches, namely, classical Lagrange finite elements and IGA. In this context, a monolithic solution approach with an explicit grid update mechanism is implemented for FSI. The applicability and the impact of the isogeometric enrichment approach on the accuracy of the numerical solution is assessed by comparing the obtained results with existing reference solutions of FSI benchmark examples involving two- and three-dimensional incompressible fluid flow past hyper-elastic solids.
On the Cold Big Bang Cosmology and the Flatness Problem

In my papers \cite{Assis1} and \cite{Assis2}, I obtain a Cold Big Bang Cosmology, fitting the cosmological data, with an absolute zero primordial temperature, a natural cutoff for the cosmological data to a vanishingly small entropy at a singular microstate of a comoving domain of the cosmological fluid. Now, in this brief paper, we show the energy density of the $t$-sliced universe must actually be the critical one, following as consequence of the solution in \cite{Assis1} and \cite{Assis2}. It must be pointed out that the result obtained here in this paper on the flatness problem does not contradict the solution in \cite{Assis1}, viz., does not contradict the open universe, with $k=-1$, obtained in \cite{Assis1}, since the solution in \cite{Assis1} had negative pressure and negative total cosmological energy density, hence lesser that the critical positive density. The critical density we obtain here is due to the positive fluctuations I previously discussed regarding the Heisenberg mechanism in \cite{Assis2}. Hence, the energy density due to fluctuation turns out to be positive, the critical one, this being calculated in \cite{Assis2} from the fluctuations within the $t$-sliced spherical shell at its $t$-sliced hypersurface, being the total energy density that generates the fluctuations, actually, negative in \cite{Assis1} and \cite{Assis2}, hence, again, lesser than the critical one and supporting $k=-1$. These results are complementary and support my previous results.
Teacher Outcomes of School-Wide Positive Behavior Support

Thousands of schools throughout the country are now implementing School-Wide Positive Behavior Support (SWPBS) as a way to improve school culture, safety, and climate. Research is needed to assess the effects of implementing SWPBS on (a) teacher stress and (b) teacher efficacy. The present pilot study provides a preliminary study of these variables by analyzing self-report measures conducted by 20 teachers within schools of differing levels of SWPBS implementation. Results indicated a statistically significant relationship between SWPBS implementation and teacher perception of educational efficacy. Results did not indicate a significant relationship, but rather a trend in the anticipated direction, between SWPBS implementation and reduced perception of teacher stress. Limitations of the study are discussed and directions for future research are recommended.
MODELING AND STRUCTURAL DESIGN OF A CONCRETE BLOCK PAVEMENT SYSTEM

SUMMARY The application of concrete block pavements is developing very fast due to their resistance to deformation, their durability, easy and rapid construction, their ability to carry traffic immediately after construction, the possibility of reusing the concrete blocks, and their compatibility with the environment and aesthetic features. The application of mechanistic methods of design and finite element theory to concrete block pavements is therefore suggested as a good alternative to experimental methods. In this research the behavior of concrete block pavements was studied by using the finite element method. First, the components of the concrete block pavement system were modeled using slab analysis finite element software called SAFE. The results were compared against those from an existing valid model and after the reliability of the developed model had been confirmed, the structural behavior of this pavement system in different block-laying patterns was studied. As a result of this research, a base thickness design chart has been developed which is in accordance with the ICPI's design chart. Various methods are available for designing concrete block pavements, all of which are based on different analysis software. The advent of high-speed digital computers has made it possible to develop software with high processing speeds and user-friendly interfaces. One software package that can be used for analyzing a concrete block pavement system is SAFE (Slab Analysis Finite Element). In this program, each of the components of different concrete block-laying patterns, as well as the other pavement layers, is modeled to study the slab performance. The structural behavior of this pavement system was studied by specifying the parameters and using them as inputs into the software. Based on the results of the models analyzed, an aggregate base thickness design chart has been developed which is in accordance with the design chart published by the ICPI (Interlocking Concrete Pavement Institute). 2. BACKGROUND
Assessing impact of forest cover change dynamics on high nature value farmland in Mediterranean mountain landscape

A general trend of scrub encroachment and natural forest expansion (old-field succession) has been occurring in the past fifty years in Mediterranean mountain areas. While this phenomenon enhances a series of ecological processes and environmental services, it may represent a threat for biodiversity conservation when occurring on high nature value (HNV) extensive farmland. These open areas, created by traditional farming systems, have been recognized as a critically important European biodiversity resource. Understanding the drivers of Land Use and Land Cover Change (LUCC) and their implications on the dynamics of forest and HNV farmland habitats plays a crucial role in biodiversity conservation in protected areas. In this perspective, the case study here presented aims to model recent (1989-2008) LUCC in a National Park of the Central Apennines (Italy) and to produce a mid-term forecast (2008-2020). In the past twenty years, 57% of the land uptake by shrubland and 46% by forest has been occurring on former HNV farmland. Mid-term projections (2008-2020) confirm further HNV farmland decline. Localization of HNV farmland habitats vulnerable to change is a valuable decision-making tool to tradeoff in protected areas the conservation of traditional landscapes with the increase of forest and shrubland areas. In this perspective, concrete socio-economical and silvicultural measures are outlined to preserve these socially and economically-fragile open habitats.
Demystifying online personas of Vietnamese young adults on Facebook: A Q-methodology approach

As online social networking sites (SNS) are becoming a part of many people’s daily life, they have become a topic of interest that attracts the attention of both academics and practitioners. The users’ behaviours on those sites are complex and have important implications. Individuals can use a wide range of SNS’s functionalities, for example, to socialise and promote their online identities or find friends of common interests. Reckless online behaviours on SNS have been shown to result in breaches of privacy and other risks such as cyber-bullying, cyber-stalking, and job loss. As a result, there are many concerns over these problems that prevent SNS from reaching their full potential. Given the vast number of user’s concerns, identified by prior studies, there is a need to explore a typology of users that classifies online personas. This typology would reveal more about the users’ needs and help improve their experience on SNS. To achieve that goal, we collected data from fourteen Vietnamese young adults of different backgrounds who use Facebook, which was then analysed with Q factor analysis. The findings suggested three distinctive online personas that include the Outgoing Connector, the Reserved Trustor, and the Threats Perceiver. Implications for marketing tactics and design of better users’ experiences on social networking sites were discussed, and the proposed typology could serve as a starting point for future research to further explore the different types of social media’s users.
Relationship between cross sectional volatility and stock returns: evidence from India

This paper examines the relationship between cross sectional volatility (CSV) and stock returns for India. The authors use daily returns for 493 companies that form part of BSE-500 index from December 1993 to June 2010. Two measures of CSV are adopted-systematic and idiosyncratic. Systematic volatility (SV) is estimated using French, Schwert and Stambaugh (1987) and Schwert and Seguin (1990). While unsystematic volatility (UV) is estimated by computing residual variance for sample stocks using the errors of CAPM model. The authors find that high SV portfolios outper-form low SV portfolios which implies dominance of speculative behavior in stock markets. The CAPM and Fama-French model are unable to fully absorb the returns on high SV portfolio which are explained by introduction of an additional CSV factor constructed on lines of Ang, Hodrick, Xing and Zhang (2003). The CSV factor possibly contains information about volatility persistence which is priced by the market. The high UV portfolios perform much better than low UV portfolios which may be consistent with finance theory that suggests compensation for imperfect diversi-fication. The FF model is able to explain the returns on UV sorted portfolios owing to the fact that high UV portfolios comprize small size and low P/B stocks. The findings are important for market players and the present study contributes to the asset pricing anomaly literature especially for emerging markets.
Keynesian Macrodynamics: Convergence, Roads to Instability and the Emergence of Complex Business Fluctuations

We reformulate the traditional AS-AD growth model, with a Taylor policy rule replacing the conventional LM-curve. The essential features of the model are gradually adjusting wages and prices, perfect foresight on current inflation rates and an adaptive revision of the inflationary climate in which the economy is operating. We compare this approach with the New Keynesian approach with staggered price and wage setting and find that whilst both approaches have common components, they have radically different dynamic implications due to the treatment of the forward-looking part of our wage-price spiral. We show that an estimated version of our model implies local asymptotic stability, due to stable interaction of goods market dynamics with the interest rate policy rule of the central bank, and due to a normal working of a real-wage feedback chain. These results are however endangered when there is a global floor to money wage inflation rates, leading in fact to economic breakdown. In this latter case, the return of some money wage flexibility in deep depressions is of help in restoring the viability of the model, thereby avoiding explosive dynamics and the collapse of the economy.
Convolutional Recurrent Neural Network-Based Event Detection in Tunnels Using Multiple Microphones

This paper proposes a sound event detection (SED) method in tunnels to prevent further uncontrollable accidents. Tunnel accidents are accompanied by crashes and tire skids, which usually produce abnormal sounds. Since the tunnel environment always has a severe level of noise, the detection accuracy can be greatly reduced in the existing methods. To deal with the noise issue in the tunnel environment, the proposed method involves the preprocessing of tunnel acoustic signals and a classifier for detecting acoustic events in tunnels. For preprocessing, a non-negative tensor factorization (NTF) technique is used to separate the acoustic event signal from the noisy signal in the tunnel. In particular, the NTF technique developed in this paper consists of source separation and online noise learning. In other words, the noise basis is adapted by an online noise learning technique for enhancement in adverse noise conditions. Next, a convolutional recurrent neural network (CRNN) is extended to accommodate the contributions of the separated event signal and noise to the event detection; thus, the proposed CRNN is composed of event convolution layers and noise convolution layers in parallel followed by recurrent layers and the output layer. Here, a set of mel-filterbank feature parameters is used as the input features. Evaluations of the proposed method are conducted on two datasets: a publicly available road audio events dataset and a tunnel audio dataset recorded in a real traffic tunnel for six months. In the first evaluation where the background noise is low, the proposed CRNN-based SED method with online noise learning reduces the relative recognition error rate by 56.25% when compared to the conventional CRNN-based method with noise. In the second evaluation, where the tunnel background noise is more severe than in the first evaluation, the proposed CRNN-based SED method yields superior performance when compared to the conventional methods. In particular, it is shown that among all of the compared methods, the proposed method with the online noise learning provides the best recognition rate of 91.07% and reduces the recognition error rates by 47.40% and 28.56% when compared to the Gaussian mixture model (GMM)–hidden Markov model (HMM)-based and conventional CRNN-based SED methods, respectively. The computational complexity measurements also show that the proposed CRNN-based SED method requires a processing time of 599 ms for both the NTF-based source separation with online noise learning and CRNN classification when the tunnel noisy signal is one second long, which implies that the proposed method detects events in real-time.