Miracle-dz/UniFAR-FTUs huggingface dataset:
Overcoming Tertiary Institutions ’ Challenges through Science and Technical Education

The paper looked at various challenges confronting tertiary institutions in Nigeria, such as insecurity, cultism, examination malpractices, corruption, poor funding among others. The paper highlighted importance of science and technical education in overcoming these challenges. Emphasis was laid on skill acquisition programme; entrepreneurship education and Community Learning Service (CLS) for both science and technical students in tertiary institutions. The paper was concluded by suggesting some recommendations for tackling tertiary institutions challenges in Nigeria such as funding of Science and Technical Education programs in Nigerian tertiary institutions; the funding should not be left for government alone, but stakeholders and private/corporate organizations should join hands in funding Nigerian tertiary institutions.
Measurement of prompt hadron production ratios in pp collisions at √ s = 0 . 9 and 7 TeV

The charged-particle production ratios ¯ p/p , K − /K + , π − /π + , (p + ¯ p)/(π + + π − ) , (K + + K − )/(π + + π − ) and (p + ¯ p)/(K + + K − ) are measured with the LHCb detector using 0 . 3 nb − 1 of pp collisions delivered by the LHC at √ s = 0 . 9 TeV and 1 . 8 nb − 1 at √ s = 7 TeV. The measurements are performed as a function of transverse momentum p T and pseudorapidity η . The production ratios are compared to the predictions of several Monte Carlo generator settings, none of which are able to describe adequately all observables. The ratio ¯ p/p is also considered as a function of rapidity loss, (cid:5)y ≡ y beam − y , and is used to constrain models of baryon transport.
Co-delivery of glycyrrhizin and doxorubicin by alginate nanogel particles attenuates the activation of macrophage and enhances the therapeutic efficacy for hepatocellular carcinoma

Nanocarrier drug delivery systems (NDDS) have been paid more attention over conventional drug delivery system for cancer therapy. However, the efficacy is hampered by the fast clearance of activated macrophage from the blood circulation system. In this study, glycyrrhizin (GL) was introduced into alginate (ALG) nanogel particles (NGPs) to construct multifunctional delivery vehicle to decrease the fast clearance of activated macrophage and enhance the anticancer efficacy with the combination therapy of GL and doxorubicin (DOX). Methods: We firstly synthesized the GL-ALG NGPs with intermolecular hydrogen bond and ionic bond as the multifunctional delivery vehicle. The immune response and phagocytosis of macrophage on GL-ALG NGPs were investigated on RAW 264.7 macrophages. The pharmacokinetic study of DOX loaded in GL-ALG NGPs was performed in rats. The active targeting effects of GL-ALG NGPs were further studied on hepatocellular carcinoma cell (HepG2) and H22 tumor-bearing mice. Moreover, the anticancer molecular mechanism of DOX/GL-ALG NGPs was investigated on HepG2 cells in vitro and tumor-bearing mice in vivo. Results: GL-ALG NGPs could not only avoid triggering the immuno-inflammatory responses of macrophages but also decreasing the phagocytosis of macrophage. The bioavailability of DOX was increased about 13.2 times by DOX/GL-ALG NGPs than free DOX in blood. The mice with normal immune functions used in constructing the tumor-bearing mice instead of the nude mouse also indicated the good biocompatibility of NGPs. GL-mediated ALG NGPs exhibited excellent hepatocellular carcinoma targeting effect in vitro and in vivo. The results suggested that the anticancer molecular mechanism of the combination therapy of glycyrrhizin and doxorubicin in ALG NGPs was performed via regulating apoptosis pathway of Bax/Bcl-2 ratio and caspase-3 activity, which was also verified in H22 tumor-bearing mice. Conclusion: DOX/GL-ALG NGPs could attenuate the activation of macrophage and enhance the therapeutic efficacy for hepatocellular carcinoma. Our results suggest that the combination therapy would provide a new strategy for liver cancer treatment.
Economic valuation of forest fire programs in Andalusia ( Spain ) : Social preferences and willingness to pay

The risk of forest fires has been relatively insufficiently studied from an economic perspective while it has been largely addressed by different academic disciplines like biology, ecology or physics. This study reports on an economic valuation survey of alternative fire prevention programs in the province of Malaga, southern Spain. Its main objective was to elicit social preferences and willingness to pay for several aspects related with forest fire management, such as: (i) fuelbreak cleaning technique (controlled grazing, prescribed burning and mechanical treatments), (ii) fuelbreak design (from traditional lineal unshaded firebreaks to more landscape and environmentally friendly structures such as shaded fuelbreaks) and (iii) fuelbreak density (linked to annually burned area). Results show respondents’ preferences are namely influenced by fuelbreak cleaning techniques and by the density of the fuelbreak network. Furthermore, estimations on the welfare change for the population were analyzed for several alternative fire prevention programs that could eventually be launched in the region. Lessons learned from this study could be relevant for the development of fire prevention policies and specific prevention campaigns in Mediterranean forests. Additional keywords: compensating surplus scenarios, contingent ranking, random parameters models, wildfires
Dortmund Equivalence Transformations for Acyclic Phase Type Distributions

This short note introduces different equivalence transformations for acyclic phase type distributions. The goal of the first two transformations is to generate a representation of a phase type distribution which is more amenable for subsequent analysis steps or for an expansion of the distribution into a stochastic process. The third transformation is used to reduce the number of states of an acyclic phase type distribution.
Coherent Estimations for Residential Photovoltaic Uptake in Germany Including Spatial Spillover Effects

The share of solar energy in German electricity generation has increased strongly over recent years. This is largely due to guaranteed feed-in tariffs together with decreasing prices for solar panels. Residential PV systems play a decisive part providing households with a possibility to contribute to the Energiewende and benefit from the use of renewable energy. Their regional distribution varies distinctly across Germany implying different requirements in distribution grids as well as uneven utilization of national policy measures. Our paper focusses on the spatial diffusion of roof mounted PV systems and the underlying drivers in Germany. We extend previous findings not only by including additional explanatory variables but also by considering cross-regional spillover using spatial econometric models. Estimation results show that spatial dependence is a relevant determinant for explaining regional clusters of PV adoption. Recurrent visual perception or peer-effects might explain spatial autocorrelation as potential adopters follow decisions by actors in the proximity. Another reason for spatial dependence might be a concentration of craft skills or solar initiatives, which leads to an accelerated diffusion in a region and its surroundings. Whereas the first explanation corresponds to the specification of a spatial lag model, the latter is in line with a spatial error specification. However, our results indicate that although spatial lag is present, spatial dependence in the residuals has higher explanatory power. Hence, we suppose that spatial spillover is not mainly driven by social imitation but by unobserved regional characteristics. Notably, high values for solar radiation, the share of detached houses, electricity demand and inverse population density of a region favour the PV uptake.
Hospitality Education Relationship between Social Carrying Capacity and Tourism Carrying Capacity : A Case of Annapurna Conservation Area , Nepal

Th e paper aims to examine the relationship between social carrying capacity and tourism carrying capacity in the Annapurna Conservation Area (ACA), Nepal (along the popular Annapurna Base Camp Trail). Carrying Capacity is a key indicator in assessing the sustainable tourism development at a given place. Th e study used Survey Research Design to obtain information from tourist and local residents. From the research, it was evident that the visitors were highly satisfi ed with the tourism activities, along with conservation and development activities at ACA. Similarly, local residents were satisfi ed with the development of tourism in ACA, yet they perceived crowding, and congestion, cultural degradation as some impending challenges in the near future. Social Carrying Capacity in the ACA has not exceed its threshold, even though this popular trekking destination has been witnessing robust growth in the number of tourist in the region post armed-confl ict (1997-2007). Hypothesis test result indicate that the relationship between dependent variable [Tourism Carrying Capacity (TCC)] and independent variable [Social Carrying Capacity (SCC)] has a positive correlation. Adequate and appropriate management intervention Journal of Tourism & Hospitality Educa on 9 (2019) 9-29 Journal of Tourism & Hospitality Educa on 9 (2019) 9-29 10 by the Nepal Trust for Nature Conservation (NTNC)/Annapurna Conservation Area Project (ACAP) there has been well-planned and sustained tourism growth in the region.
Towards Secure Multi-Keyword Top-k Retrieval over Encrypted Cloud Data ∗

Cloud computing has emerging as a promising pattern for data outsourcing and high-quality data services. However, concerns of sensitive information on cloud potentially causes privacy problems. Data encryption protects data security to some extent, but at the cost of compromised eﬃciency. Searchable symmetric encryption (SSE) allows retrieval of encrypted data over cloud. In this paper, we focus on addressing data privacy issues using searchable symmetric encryption (SSE). For the ﬁrst time, we formulate the privacy issue from the aspect of similarity relevance and scheme robustness. We observe that server-side ranking based on order-preserving encryption (OPE) inevitably leaks data privacy. To eliminate the leakage, we propose a two-round searchable encryption (TRSE) scheme that supports top-k multi-keyword retrieval. In TRSE, we employ a vector space model and homomorphic encryption. The vector space model helps to provide suﬃcient search accuracy, and the homomorphic encryption enables users to involve in the ranking while the majority of computing work is done on the server side by operations only on ciphertext. As a result, information leakage can be eliminated and data security is ensured. Thorough security and performance analysis show that the proposed scheme guarantees high security and practical eﬃciency.
Title Prototyping and evaluating SDN-based multicast architectures for live video streaming

Software Defined Networking (SDN) is an emerging approach for network programmability, with the capacity to initialize, control, change, and manage network behavior dynamically via open interfaces. The rise of SDN presents an opportunity to overcome the limitations of rigid and static traditional Internet architecture and provide services like inter-domain network layer multicast for live video streaming. In this demonstration we present a platform to evaluate and compare SDN-based multicast architectures for live streaming and benchmark their performance against standard IP unicast. The platform is equipped with two graphical user interfaces (GUI). A Panoramic UI provides a mechanism to modify various evaluation parameters and monitor the effect on output in form of graphs and live statistics. An Animator UI displays traffic flows over the chosen network topology and offers packet level information for the ongoing video streams. We also present a prototype of mCast implemented on our platform. mCast is a novel SDN-based multicast architecture for live video streaming over the Internet. The feedback from our platform and its GUIs showcases how mCast can save network and system resources while improving the video quality for clients.
SIMULATION OF SELF-LEARNING CLUSTERING METHODS FOR SELECTING AND GROUPING SIMILAR PATCHES , USING TWO-DIMENSIONAL NONLINEAR SPACE-INVARIANT MODELS AND FUNCTIONS OF NORMALIZED " EQUIVALENCE "

The results of modeling combined with self-training clustering method of image fragments. For isolation, selection and use of cluster grouping of fragments of structural and topological features and two-dimensional spatial equivalence nonlinear functions. The simulation results showed that the method has good convergence. The method is fast, as the number of iterative steps selftraining clustering was equal to between 5 and 17 for the experiments. The method is easily displayed on the matrix-matrix procedures.
Islamic and Conventional Unit Trusts in Malaysia : A Performance Comparison

The Malaysian unit trust industry has been growing positively since the introduction of Amanah Saham Nasional and Amanah Saham Bumiputra in early 1980s and early 1990s respectively. The main objective of this paper is to evaluate the overall performance of Islamic and conventional unit trust funds in the context of Malaysia’s capital market, in terms of risk, return and diversification of selected unit trust in Malaysia for the 5-year period from 2002 to 2006. The paper applies the most popular measures of performance such as Sharpe index, Treynor index, and Jensen index. The overall findings suggest that mutual funds in Malaysia are able to add value. Pertaining to the return for both conventional and Islamic funds and the market indices, it is found that conventional funds outperform the market and on the contrary, Islamic funds underperform the market. It is also found that fund managers have poor timing ability and they are unable to correctly identify good bargain stocks and to forecast price movements of the general market. Therefore, due to these reasons, fund managers should be given more room to plan the portfolio of investment that fit the objective of the fund.
Improving the Accuracy of Mobile Touchscreen QWERTY

In this thesis we explore alternative keyboard layouts in hopes of finding one that increases the accuracy of text input on mobile touchscreen devices. In particular, we investigate if a single swap of 2 keys can significantly improve accuracy on mobile touchscreen QWERTY keyboards. We do so by carefully considering the placement of keys, exploiting a specific vulnerability that occurs within a keyboard layout, namely, that the placement of particular keys next to others may be increasing errors when typing. We simulate the act of typing on a mobile touchscreen QWERTY keyboard, beginning with modeling the typographical errors that can occur when doing so. We then construct a simple autocorrector using Bayesian methods, describing how we can autocorrect user input and evaluate the ability of the keyboard to output the correct text. Then, using our models, we provide methods of testing and define a metric, the WAR rating, which provides us a way of comparing the accuracy of a keyboard layout. After running our tests on all 325 2-key swap layouts against the original QWERTY layout, we show that there exists more than one 2-key swap that increases the accuracy of the current QWERTY layout, and that the best 2-key swap is i ↔ t, increasing accuracy by nearly 0.18 percent.
A NEW IMPLEMENTATION OF TAGUCHI ' S METHOD

Taguchi's method is an efficient and important optimization method based on orthogonal array concept which offers systematic and efficient process. it causes a balance in experiments design as well. In this paper, a new implementation of Taguchi's method for shape optimization of electromagnetic devices is presented and applied to torque profile optimization of Double Stator Switched Reluctance Motor (DSSRM). Due to nonlinearity of DSSRM Torque characteristic, Finite Element Analysis is implemented. Previous implementation of Taguchi's method does not use the output of optimization process efficiently, so the convergence to the optimum parameters levels is prolonged. Our presented method uses the same bases to the ordinary implementation, but, finally determines parameters which are dependent or have nonlinear effect on the system operation, and uses this information in the optimization process. This article uses the response table efficiently to obtain the optimum parameters levels. Simulation results show the efficiency and accuracy of the new method.
Induction heating on Thermally Remendable self-healing polymers containing magnetic nanoparticles

Self-healing polymeric materials have an inherent capacity to regain the ability to "carry" mechanical load even after a potential failure. This property may occur independently or to be triggered by a specific external stimulus (e.g. heat, radiation). In this paper we studied the Induction Heating process as an alternative way of activating this mechanism. For this purpose, test pieces were examined consisting of resin with a thermal capacity of self-healing while adding different magnetic nanoparticles of iron and iron oxide, which play the role of the heat sources in the material. Alongside we included a brief reference to the method of modelling the temperature field produced by the induction heating process. Key-Words: Self healing polymers, Induction Heating, Thermally Remendable Polymers
Toward Predictive Models of Tumor Growth: A General Diffuse-Interface Continuum Theory of Mixtures for Tumor Growth and a Bayesian Approach to Model Validation and Uncertainty Quantification

While a large and growing literature exists on mathematical and computational models of tumor growth, to date tumor growth models are largely qualitative in nature, and fall far short of being able to provide predictive results important in life-and-death decisions. This is largely due to the enormous complexity of evolving biological and chemical processes in living tissue and the complex interactions of many cellular and vascular constituents in living organisms. Several new technologies have emerged, however, which could lead to significant progress in this important area: 1) the development of so-called phase-field, or diffuse-interface models, which can be developed using continuum mixture theory, and which provide a general framework for modeling the action of multiple interacting constituents. These are based on generalizations of the Cahn-Hilliard models for spinoidal decomposition, and have been used recently in certain tumor growth theories; 2) the emergence of predictive computational methods based on the use of statistical methods for calibration, model validation, and uncertainty quantification; 3) advances in imaging, experimental cell biology, and other medical observational methodologies; and 4) the advent of petascale computing that makes possible the resolution of features at scales and at speeds that were unattainable only a short time in the past. In the present paper, we develop a general phenomenological thermomechanical theory of mixtures that employs phase-field or diffuse interface models of surface energies and reactions and which provides a framework for generalizing existing theories of the types that are in use in tumor growth modeling. In principle, the framework provides for the effects of M solid constituents, which may undergo large deformations, and for the effect of N − M fluid constituents, which could include highly nonlinear, non-Newtonian fluids. We then describe several special cases which have the potential of providing acceptable models of tumor growth. We then describe the beginning steps of the development of Bayesian methods for statistical calibration, model validation, and uncertainty quantification, which, with further work, could produce a truly predictive tool for studying tumor growth. In particular, we outline the processes of statistical calibration and validation that can be employed to determine if tumor growth models, drawn from the broad class of models developed here, are valid for prediction of key quantities of interest critical to making decisions on various medical protocals. We also describe how uncertainties in such key quantities of interest can be quantified in ways that can be used to establish confidence in predicted outcomes.
DESIGN OF ACCELERATOR MAGNETS

Analytical and numerical field computation methods for the design of conventional and superconducting accelerator magnets are presented. The field in the aperture of these magnets is governed by the Laplace equation. The consequences for the field quality estimation and the ideal pole shapes (for conventional magnets) and ideal current distributions (for superconducting magnets) are described. Examples of conventional (LEP) and superconducting (LHC) dipoles and quadrupoles are given. 1 Guiding fields for charged particles A charged particle moving with velocity v through an electro-magnetic field is subjected to the Lorentz force F = e( v × B + E). (1) While the particle moves from the location r1 to r2 with v = d r dt , it changes it’s energy by ∆E = ∫ r2 r1 Fd r = e ∫ r2 r1 ( v × B + E)d r . (2) The particle trajectory d r is always parallel to the velocity vector v. Therefore the vector v × B is perpendicular to d r, i.e., ( v × B) d r = 0. The magnetic field cannot contribute to a change in the particle’s energy. However, if forces perpendicular to the particle trajectory are needed, magnetic fields can serve for the guiding and the focusing of particle beams. At relativistic speed, electric and magnetic fields have the same effect on the particle trajectory if E = c B. A magnetic field of 1 T is then equivalent to an electric field of strength E = 3 · 108 V/m. A magnetic field of one Tesla strength can easily be achieved with conventional magnets (superconducting magnets on an industrial scale can reach up to 10 T), whereas electric field strength in the Giga Volt / meter range are technically not to be realized. This is the reason why for high energy particle accelerators only magnetic fields are used for guiding the beam. A charged particle forced to move along a circular trajectory looses energy by emission of photons according to ∆E = 1 3 0 e2E4 (m0c)R (3) with every turn completed [24], where R is the curvature of the trajectory and E is the energy of the beam. A comparison between electron and proton beams of the same energy yields: ∆Ep ∆Ee = ( mec 2 mpc )4 = ( 0.511MeV 938.19MeV )4 = 8.8 · 10−14. (4) For the heavier protons, synchrotron radiation is therefore not a limiting factor, however, the maximum energy is limited by the field in the dipole (bending) magnets. For a particle travelling on a circular closed orbit in an uniform bending field, the resulting Lorentz force e v B has to equal the centrifugal