Miracle-dz/UniFAR-FTUs huggingface dataset:
Determinants of Adoption and Use of Open Access Publishing by Academic Staff in Nigeria Universities

The emergence of the World Wide Web (WWW) has changed the scholarly publishing system. Today, Open Access (OA) scholarly publishing offers free access and wide dissemination for research findings anytime and anywhere as an additional value for scholarly content. Despite the potentials of OA publishing, its adoption and use is still low. This paper determines factors influencing the adoption and use of OA publishing by academic staff in universities in Nigeria using an adapted Unified Theory of Acceptance and Use Technology (UTAUT). The study applies methodolog - ical triangulation by combining quantitative and qualitative approaches. The empirical data were collected from 317 academic staff in universities in southwest Nigeria. The questionnaire forms were analyzed using the Statistical Pack - age for Social Sciences (IBM-SPSS) 19.0 version to generate descriptive statistics, Analysis of Variance, and Hierarchical Multiple Regression. Thematically, analysis also applies to the interviews. The results show that awareness, attitude, performance expectancy, Internet self-efficacy, and facilitating conditions significantly influenced the adoption and use of OA publishing. The study also reveals that due to lack of OA policy, most of the respondents did not know about OA. The findings further establish that all predictors and moderating variables jointly contributed 64.4% total variance towards the adoption and use of OA publishing. One of the implications of this study is that there is a need for adequate facilities to support adoption and use of OA publishing. The findings inform the proposed framework for improving and evaluating the adoption and use of OA publishing. The findings also have theoretical, societal, and methodological significance to all stakeholders.
Registration-based Distortion and Binocular Representation for Blind Quality Assessment of Multiply-Distorted Stereoscopic Image

Multiply-distorted stereoscopic images are common in real-world applications. The mixture of multiple distortions leads to complex binocular visual behavior of multiply-distorted stereoscopic images, so the existing blind singly-distorted stereoscopic image quality assessment (IQA) methods cannot obtain satisfactory result-s on multiply-distorted stereoscopic images. Because binocular rivalry caused by different distortions in the left and right views greatly inﬂuences the ﬁnal stereoscopic image quality, we present a registration-based distortion and binocular representation for blind quality assessment of multiply-distorted stereoscopic image in this paper. We ﬁrst use a registration-based distortion representation to represent the distortion in the stereoscopic image. Then we represent the binocular rivalry by merging the left and right views into a cyclopean image. Considering that the color and intensity of pixels in the RGB image can better reﬂect the information of the distorted image, then a grayscale cyclopean image is further converted to the color binocular representation through tone mapping. Finally, a multiply-distorted stereoscopic IQA method based on a double-stream convolutional neural network is proposed. The two sub-networks are used to extract quality features from the registration-based distortion representation and color binocular representation, respectively. Experimental re-sults demonstrate that the proposed model outperforms the state-of-the-art models on the multiply-distorted
A MEMORYLESS SYMMETRIC RANK-ONE METHOD WITH SUFFICIENT DESCENT PROPERTY FOR UNCONSTRAINED OPTIMIZATION

Quasi-Newton methods are widely used for solving unconstrained optimization problems. However, it is diﬃcult to apply quasi-Newton methods directly to large-scale unconstrained optimization problems, because they need the storage of memories for matrices. In order to overcome this diﬃculty, memory-less quasi-Newton methods were proposed. Shanno (1978) derived the memoryless BFGS method. Recently, several researchers studied the memoryless quasi-Newton method based on the symmetric rank-one formula. However existing memoryless symmetric rank-one methods do not necessarily satisfy the suﬃcient descent condition. In this paper, we focus on the symmetric rank-one formula based on the spectral scaling secant condition and derive a memoryless quasi-Newton method based on the formula. Moreover we show that the method always satis(cid:12)es the suﬃcient descent condition and converges globally for general objective functions. Finally, preliminary numerical results are shown.
A Comparative Study of Gender Difference in Palatal Rugae Patterns among Bengali Subjects in Murshidabad

(cleft lip, cleft palate etc.,) or injured hard palates were excluded from the present study. Persons residing outside Murshidabad or those unwilling to give consent were also kept out of the present study. Informed consent was taken from all participants. The oral cavity of subject was rinsed with chlorhexidine (0.12%) mouth wash. An alginate impression of the hard palate of subject was taken and casted by dental stone. The rugae patterns were marked with black permanent marker pen and then were analysed by using the easiest, most practical and standardised technique of Thomas and Kotze classification [4]. This classification is based on the parameters like total number of rugae, number of primary rugae, predominant shape of rugae, predominant direction of rugae and their unifications. Length of rugae was evaluated as primary (>5 mm), secondary (3-5 mm) and fragmentary (<3 mm). Rugae less than 2 mm were not included. Shape of rugae was recorded as curved, wavy, straight and circular [Table/Fig-1]. The direction of rugae was evaluated by measuring the angle formed by the line joining its origin and termination and the line perpendicular to the median raphe and
Hybrid architecture for vehicle lateral collision avoidance

In this study, the authors consider the problem of collision avoidance of ground vehicles. In this framework, they focus on a single vehicle, and they guarantee that a given safe set is not exited during a mission. More specifically, they consider the yaw-lateral motion of a two-wheel vehicle subject to a side wind, and they design a state-feedback controller such that the vehicle follows the nominal trajectory with a given maximum error. For these purposes, they resort to a control system where a supervisor, implemented as a hybrid automata, decides to switch between two controllers, depending on the measured vehicle lateral displacement from the nominal trajectory. The two controllers are designed using an H ∞ approach and the input–output finite-time stability approach, respectively. Some simulation results are included, showing the effectiveness of the proposed architecture.
3D vector finite-element electromagnetic forward modeling for large loop sources using a total-field algorithm and unstructured tetrahedral grids

ABSTRACTUnstructured tetrahedral grids with local refinement facilitate the use of total-field solution approaches to geophysical electromagnetic (EM) forward problems. These approaches, when combined with the vector finite-element (FE) method and with refinement near transmitters and receivers, can give accurate solutions and can easily handle realistic models with complex geometry and topography. We have applied this approach to 3D forward modeling for fixed- and moving-loop configurations. MUMPS, a direct solver, was used to solve the linear system of equations generated by FE analysis. A direct solver is particularly suited to the moving-loop configuration for which the right side is different for every transmitter loop, but for which the coefficient matrix is unchanged. Therefore, the coefficient matrix need only be factorized once, and then the system can be solved efficiently for all different right sides. We compared our results with several typical scenarios from the literature: a conductive bric.
“The Terrors of Kingly Power”: The Unusual Dental Pathology of King Pyrrhus of Epirus

Pyrrhus of Epirus, widely respected and feared by his contemporaries, was a legendary figure in the ancient world. In this paper, we investigate Plutarch’s description of the king’s unique dental pathology. There are several possibilities to explain the ancient king's presentation, including several different types of developmental dysplasia. However, our conclusion is that it was likely due to a significant dental calculus overgrowth, often seen in the ancient Greek diet of the time. Whatever the underlying cause, Pyrrhus' intimidating visage helped secure the king a legacy that lasts to this day.
Does Therapeutic Exercise Support Improvement in Cognitive Function and Instrumental Activities of Daily Living in Patients with Mild Alzheimer’s Disease? A Randomized Controlled Trial

This randomized controlled trial aims to investigate the effect of 12 weeks of therapeutic exercise on cognitive function and daily activities in patients with mild Alzheimer’s disease (AD). A total of 171 patients with mild AD from the Amarousion Day Care Center of the Alzheimer Society of Athens and the Athens General Hospital “G. Gennimatas” were randomly divided into three groups. Group A (aerobic and resistance exercise, n = 57), group B (resistance exercise, n = 57), and group C (control group, n = 57). Group A followed a weekly program consisting of 5 days with 30 min walking and 3 days with resistance exercises for about 45 min. Group B followed only a resistance exercise program, the same as group A. Group C did not participate in any exercise program. After the intervention, cognitive function was assessed with the Cognitive Examination-Revised (ACE-R), Trail Making Test A-B (TMT A-B), and Digit Span Test Forward and Backward (DST F-B) and daily activities with the instrumental activities of daily living scale (IADLs). A significant intervention effect was observed for all outcome measures (global cognitive function and instrumental activities of daily living). ANCOVA Bonferroni corrected post hoc tests revealed that the aerobic and resistance group improved compared to the control group on all measurement scales. The resistance group also showed an improvement compared to the control group. No significant effects were found between the aerobic and resistance group and the resistance group in any of the outcome measures.
Domain Boundary Formation Within an Intercalated Pb Monolayer Featuring Charge‐Neutral Epitaxial Graphene

The synthesis of new graphene‐based quantum materials by intercalation is an auspicious approach. However, an accompanying proximity coupling depends crucially on the structural details of the new heterostructure. It is studied in detail the Pb monolayer structure after intercalation into the graphene buffer layer on the SiC(0001) interface by means of photoelectron spectroscopy, x‐ray standing waves, and scanning tunneling microscopy. A coherent fraction close to unity proves the formation of a flat Pb monolayer on the SiC surface. An interlayer distance of 3.67 Å to the suspended graphene underlines the formation of a truly van der Waals heterostructure. The 2D Pb layer reveals a quasi ten‐fold periodicity due to the formation of a grain boundary network, ensuring the saturation of the Si surface bonds. Moreover, the densely‐packed Pb layer also efficiently minimizes the doping influence by the SiC substrate, both from the surface dangling bonds and the SiC surface polarization, giving rise to charge‐neutral monolayer graphene. The observation of a long‐ranged ( 3×3$\sqrt {3}\times \sqrt {3}$ ) reconstruction on the graphene lattice at tunneling conditions close to Fermi energy is most likely a result of a nesting condition to be perfectly fulfilled.
Global kinetic ballooning mode simulations in BOUT++

We report on simulation results of a 3+1 gyro-Landau-fluid (GLF) model in BOUT++ framework, which contributes to increasing the physics understanding of the edge turbulence. We find that there is no second stability region of kinetic ballooning modes (KBM) in the concentric circular geometry. The first unstable β of KBM decreases below the ideal ballooning mode threshold with increasing ηi. In order to study the KBM in the real tokamak equilibrium, we find that the approximation of shifted circular geometry (β≪ε2) is not valid for a high β global equilibrium near the second stability region of KBM. Thus we generate a series of real equilibria from a global equilibrium solver CORSICA, including both Shafranov shift and elongation effects, but not including bootstrap current. In these real equilibria, the second stability region of KBM are observed in our global linear simulations. The most unstable mode for different β are the same while the mode number spectrum near the second stability region is wider than the case near the first stability region. The nonlinear simulations show that the energy loss of an ELM keeps increasing with β, because the linear drive of the turbulence remains strong for the case near the second stability region during profile evolution.
MM G Mathematical Modelling and Geometry Volume 4 , No 3 , p . 31 – 49 ( 2016 ) Orbital Stellar Stereoscopic Observatory Project : Motivation and Autonomous Navigation in the Heliocentric Transfer and Operational Orbits

M. S. Chubey, V. V. Kouprianov, V. N. L’vov, S. D. Tsekmeister, A. V. Bakholdin, S. V. Markelov, and G. V. Levko 1 Central (Pulkovo) Astronomical Observatory, Russian Academy of Sciences, 65 Pulkovskoye Ave., Saint Petersburg, 196140, Russia 2 Department of Physics and Astronomy, University of North Carolina at Chapel Hill, Phillips Hall, 120 E. Cameron Ave., Chapel Hill, NC 27599, USA 3 Saint Petersburg National Research University of Information Technologies, Mechanics and Optics, 49 Kronverkskiy Pr. , Saint Petersburg, 197101, Russia 4 Special Astrophysical Observatory, Russian Academy of Sciences, Nizhnij Arkhyz, Zelenchukskiy Region, Karachai-Cherkessian Republic, 369167, Russia 5 Saint Petersburg Research Institute of Television, 22 Politekhnicheskaya St., Saint Petersburg, 194021, Russia e-mail: mchubey@gao.spb. ru, b v.k@bk.ru, c epos-gao@mail.ru, d bakholdin@aco.ifmo. ru, markel@sao.ru, f levgen@mail.ru
Comparison of supervised machine learning algorithms for waterborne pathogen detection using mobile phone fluorescence microscopy

Abstract Giardia lamblia is a waterborne parasite that affects millions of people every year worldwide, causing a diarrheal illness known as giardiasis. Timely detection of the presence of the cysts of this parasite in drinking water is important to prevent the spread of the disease, especially in resource-limited settings. Here we provide extended experimental testing and evaluation of the performance and repeatability of a field-portable and cost-effective microscopy platform for automated detection and counting of Giardia cysts in water samples, including tap water, non-potable water, and pond water. This compact platform is based on our previous work, and is composed of a smartphone-based fluorescence microscope, a disposable sample processing cassette, and a custom-developed smartphone application. Our mobile phone microscope has a large field of view of ~0.8 cm2 and weighs only ~180 g, excluding the phone. A custom-developed smartphone application provides a user-friendly graphical interface, guiding the users to capture a fluorescence image of the sample filter membrane and analyze it automatically at our servers using an image processing algorithm and training data, consisting of >30,000 images of cysts and >100,000 images of other fluorescent particles that are captured, including, e.g. dust. The total time that it takes from sample preparation to automated cyst counting is less than an hour for each 10 ml of water sample that is tested. We compared the sensitivity and the specificity of our platform using multiple supervised classification models, including support vector machines and nearest neighbors, and demonstrated that a bootstrap aggregating (i.e. bagging) approach using raw image file format provides the best performance for automated detection of Giardia cysts. We evaluated the performance of this machine learning enabled pathogen detection device with water samples taken from different sources (e.g. tap water, non-potable water, pond water) and achieved a limit of detection of 12 cysts per 10 ml, an average cyst capture efficiency of ~79%, and an accuracy of ~95%. Providing rapid detection and quantification of waterborne pathogens without the need for a microbiology expert, this field-portable imaging and sensing platform running on a smartphone could be very useful for water quality monitoring in resource-limited settings.
Weighted k-cardinality trees

We consider the k -CARD TREE problem, i.e., the problem of finding in a given undirected graph G a subtree with k edges, having minimum weight. Applications of this problem arise in oil-field leasing and facility layout. While the general problem is shown to be strongly NP hard, it can be solved in polynomial time if G is itself a tree. We give an integer programming formulation of k-CARD TREE, and an efficient exact separation routine for a set of generalized subtour elimination constraints. The polyhedral structure of the convex huLl of the integer solutions is studied.
Mechanisms of jet instability: role of deceleration

This paper shows that decrease of velocity magnitude downstream enhances the shear-layer instability in jetlike single- and two-fluid flows. This feature has not been recognized in stability studies, performed in the parallel and quasi-parallel flow approximations, because the deceleration effect is strongly non-parallel. It was first revealed in conical similarity flows. The similarity allows for reducing the base-flow and stability problems to ordinary differential equations exactly conserving the acceleration terms. This helps reveal the deceleration effect. The development of numerical technique for stability studies of two-dimensional flows helped understand the instability nature of swirling flows in sealed containers. It was found for an elongated cylinder with one rotating end disk and stationary other walls that the instability develops in the counterflow near the rotating disk, where the backflow decelerates and the shear-layer and deceleration effects cooperate. An interesting stabilizing effect of acceleration is observed in a model heat exchanger. The thermal convection develops in a rotating cylindrical container whose sidewall is adiabatic and the end disks have different temperatures. The centrifugal acceleration suppresses, while the temperature difference stimulates, the shear-layer instability of this flow. Next, the review discusses two-fluid flows in a sealed vertical container, driven by either bottom (whirlpool model) or lid (waterspout model) rotation. As the rotation speeds up, the shear-layer instability develops in a jet-like boundary layer in the air–water flows. The jet forms near a rotating disk, goes to the interface near the sidewall, and converges to the axis near the interface. New circulatory cells emerge in both fluids and the interface significantly bends. The instability develops after such flow pattern becomes well formed. The instability focuses near the interface where the jet-like motion approaches a new cell, decelerates, and diverges—hence the deceleration and shear-layer effects work together. In oil–water flows, the instability develops in the lower fluid, either in its depth or near the interface depending on the water volume fraction. Thus, the review shows that deceleration enhanced the shear-layer instability in a wide group of flows.
Detection of Schizophrenia using Machine Learning

Schizophrenia is a mental illness that impacts approximately 1% of the global population. The condition can make it challenging for individuals with schizophrenia to differentiate between internally generated and externally generated stimuli due to abnormalities in the corollary discharge process of the nervous system. This phenomenon provides an explanation for certain symptoms associated with schizophrenia. Exploring this process and its connection to the disease's symptoms can contribute to our understanding of the abnormal brain processes observed in affected individuals. Advancements in the study of electrophysiological brain activity, along with improved access to EEG data, offer new possibilities for investigating and diagnosing neuronal disorders in real-world settings. In this study, a larger dataset of EEG data was utilized, including data from previous research published in Schizophrenia Bulletin Advance Access on July 10, 2013. The dataset combined EEG records from 22 healthy individuals and 36 individuals with schizophrenia, as well as additional data from 10 healthy individuals and 13 schizophrenia patients from a prior study. The classification phase involved considering two different methods for diagnosing schizophrenia using EEG signals. Traditional machine learning techniques, such as xgboost, decision trees, naïve Bayes, random forest, Long short-term memories (LSTMs), support vector machines, two-dimensional convolutional networks (2D-CNNs), and two-dimensional convolutional networks-LSTMs, were employed to classify the EEG signals. Deep learning models were also implemented, and various activation functions were compared. Among the proposed deep learning models, the SVM architecture demonstrated the highest performance level. The SVM model utilized the RBF Kernel with cross-validation values (CV) of 3, 6, and 8. Remarkably, the SVM model achieved a precision rate of 100 percent.
Wittgenstein On Mathematics

The philosophy of mathematics was one of Wittgenstein’s central concerns from the beginning of his philosophical career until close to the end: it is what he told Russell he wanted to work on when he came to Cambridge in the Autumn of 1911; it is one of the issues addressed in the Tractatus; it dominates his writings immediately after his return to philosophy, the Philosophical Remarks and Philosophical Grammar; it was a recurring theme of his Cambridge lecture courses throughout the 1930s; it was to have been the subject of the second half of the Philosophical Investigations as he originally conceived them; and it occupied much of his time during the Second World War. Yet Wittgenstein has had nothing like the influence on contemporary philosophy of mathematics as he has on the philosophy of mind or of language. Although all of Wittgenstein’s philosophy no doubt presents difficulties to the interpreter, the secondary literature on his philosophy of mathematics is peculiarly inconclusive even when it is judged by these standards. Why is this? In what follows I shall be describing some of Wittgenstein’s views in the hope that this may contribute to answering that question. After a brief sketch of the central ideas of Wittgenstein’s account of mathematics in the Tractatus, most of the chapter will be devoted to his middle period writings in the philosophy of mathematics, focusing on his rejection of the actual infinite and on his suggestion that the meaning of an arithmetical generalization is its proof. One aim will be to show how this led him to some central themes of his later writings, his attitude to formal inconsistency and the rule-following considerations. Then I will say something about Wittgenstein’s later philosophy of mathematics, such as it is. I shall conclude by offering a tentative diagnosis of its evident incompleteness.