Miracle-dz/UniFAR-FTUs huggingface dataset:
Publishing Ethics and Predatory Practices: A Dilemma for All Stakeholders of Science Communication

Publishing scholarly articles in traditional and newly-launched journals is a responsible task, requiring diligence from authors, reviewers, editors, and publishers. The current generation of scientific authors has ample opportunities for publicizing their research. However, they have to selectively target journals and publish in compliance with the established norms of publishing ethics. Over the past few years, numerous illegitimate or predatory journals have emerged in most fields of science. By exploiting gold Open Access publishing, these journals paved the way for low-quality articles that threatened to change the landscape of evidence-based science. Authors, reviewers, editors, established publishers, and learned associations should be informed about predatory publishing practices and contribute to the trustworthiness of scholarly publications. In line with this, there have been several attempts to distinguish legitimate and illegitimate journals by blacklisting unethical journals (the Jeffrey Beall's list), issuing a statement on transparency and best publishing practices (the Open Access Scholarly Publishers Association's and other global organizations' draft document), and tightening the indexing criteria by the Directory of Open Access Journals. None of these measures alone turned to be sufficient. All stakeholders of science communication should be aware of multiple facets of unethical practices and publish well-checked and evidence-based articles.
1 Introduction – Problem Statements and Models

Matrix factorization is an important and unifying topic in signal processing and linear algebra, which has found numerous applications in many other areas. This chapter introduces basic linear and multi-linear 1 models for matrix and tensor factorizations and decompositions, and formulates the analysis framework for the solution of problems posed in this book. The workhorse in this book is Nonnegative Matrix Factorization (NMF) for sparse representation of data and its extensions including the multi-layer NMF, semi-NMF, sparse NMF, tri-NMF, symmetric NMF, orthogonal NMF, non-smooth NMF (nsNMF), overlapping NMF, convo-lutive NMF (CNMF), and large-scale NMF. Our particular emphasis is on NMF and semi-NMF models and their extensions to multi-way models (i.e., multi-linear models which perform multi-way array (tensor) decompositions) with nonnegativity and sparsity constraints, including, Nonnegative Tucker Decomposi-tions (NTD), Constrained Tucker Decompositions, Nonnegative and semi-nonnegative Tensor Factorizations (NTF) that are mostly based on a family of the TUCKER, PARAFAC and PARATUCK models. As the theory and applications of NMF, NTF and NTD are still being developed, our aim is to produce a unified, state-of-the-art framework for the analysis and development of efficient and robust algorithms. In doing so, our main goals are to: 1. Develop various working tools and algorithms for data decomposition and feature extraction based on nonnegative matrix factorization (NMF) and sparse component analysis (SCA) approaches. We thus integrate several emerging techniques in order to estimate physically, physiologically, and neuroanatomi-cally meaningful sources or latent (hidden) components with morphological constraints. These constraints include nonnegativity, sparsity, orthogonality, smoothness, and semi-orthogonality. 2. Extend NMF models to multi-way array (tensor) decompositions, factorizations, and filtering, and to derive efficient learning algorithms for these models. 3. Develop a class of advanced blind source separation (BSS), unsupervised feature extraction and clustering algorithms, and to evaluate their performance using a priori knowledge and morphological constraints. 4. Develop computational methods to efficiently solve the bi-linear system Y = AX + E for noisy data, where Y is an input data matrix, A and X represent unknown matrix factors to be estimated, and the matrix E represents error or noise (which should be minimized using suitably designed cost function). 1 A function in two or more variables is said to be multi-linear if it is linear in each variable separately. 2 Nonnegative Matrix and Tensor Factorizations 5. Describe and analyze various cost functions (also referred to as (dis)similarity measures or divergences) and apply optimization criteria to ensure robustness with …
Localized Smoothing for Multinomial Language Models

We explore a formal approach to dealing with the zero frequency problem that arises in applications of probabilistic models to language. In this report we introduce the zero frequency problem in the context of probabilistic language models, describe several popular solutions, and introduce localized smoothing, a potentially better alternative. We formulate localized smoothing as a two-step maximization process, outline the estimation details for both steps and present the experiments which show the technique to have potential for improving performance.
APPRIS WebServer and WebServices

This paper introduces the APPRIS WebServer (http://appris.bioinfo.cnio.es) and WebServices (http://apprisws.bioinfo.cnio.es). Both the web servers and the web services are based around the APPRIS Database, a database that presently houses annotations of splice isoforms for five different vertebrate genomes. The APPRIS WebServer and WebServices provide access to the computational methods implemented in the APPRIS Database, while the APPRIS WebServices also allows retrieval of the annotations. The APPRIS WebServer and WebServices annotate splice isoforms with protein structural and functional features, and with data from cross-species alignments. In addition they can use the annotations of structure, function and conservation to select a single reference isoform for each protein-coding gene (the principal protein isoform). APPRIS principal isoforms have been shown to agree overwhelmingly with the main protein isoform detected in proteomics experiments. The APPRIS WebServer allows for the annotation of splice isoforms for individual genes, and provides a range of visual representations and tools to allow researchers to identify the likely effect of splicing events. The APPRIS WebServices permit users to generate annotations automatically in high throughput mode and to interrogate the annotations in the APPRIS Database. The APPRIS WebServices have been implemented using REST architecture to be flexible, modular and automatic.
Web Document Clustering Research Based on Granular Computing

In this paper, a method of web document clustering based on granular computing (WDCGrc) is presented. The method computes the weight value of the words in documents by adopting the TF-IDF principle. Meanwhile, combinative ways defining documents threshold and average weight value are adopted to reduce dimensions and extract the keywords in each document. The paper establishes the transformation between the keywords in documents and the binary granules, and adopts the algorithm of association rules based on granular computing to obtain frequent item sets between documents. Bring in the set theory thought, numbers of the same word between documents as the document similarity and the clustering result is obtained. The experiment shows that the method is practical and feasible, with good quality of clustering.
Miscibility of Poly(hydroxybutyrate)/Poly(vinyl alcohol) Melt Blends Plasticized With Glycerol

Poly(hydroxybutyrate)/poly(vinyl alcohol) (PHB/PVA) blends plasticized with glycerol were prepared by melt blending of PHB and glycerol plasticized PVA. The PHB/PVA-glycerol compositions were 90:10, 75:25 and 50:50 w/w, being the concentration of glycerol in the PVA mixture of 10 wt %. The blends were characterized by infrared spectroscopy, dynamic-mechanical thermal analysis, and scanning electron microscope of the fragile fractured surface. The results showed one single phase blend, indicating miscibility corroborated by the presence of a single glass transition temperature. The blending method proved to be an efficient way to tune PHB properties keeping its biodegradable nature since both PVA and glycerol are fully biodegradable materials.
Subcellular Compartmentalization of P‐ERKs in the Lewy Body Disease Substantia Nigra

Extracellular signal–regulated kinases (ERKs) are involved in regulating neuronal survival, differentiation, and plasticity. Recent studies also indicate that ERKs can play a detrimental role in models of oxidative neuronal injury. 1,2 Our previous studies showed discrete cytoplasmic accumulations of phophorylated ERKs (P-ERKs) in Parkinson’s disease and other Lewy body diseases, and in 6-hydroxydopamine–treated neuronal cell cultures. 3 As the effects of ERK phosphorylation are critically dependent upon subcellular localization and access to downstream targets, we investigated the subcellular distribution of P-ERKs in Lewy body disease using double-label confocal microscopy. The association of P-ERK granules with a subset of (sometimes enlarged) mitochondria suggests a potential interaction between mitochondrial function and the ERK signaling pathway in degenerating dopaminergic neurons.
PiCam

We present PiCam (Pelican Imaging Camera-Array), an ultra-thin high performance monolithic camera array, that captures light fields and synthesizes high resolution images along with a range image (scene depth) through integrated parallax detection and superresolution. The camera is passive, supporting both stills and video, low light capable, and small enough to be included in the next generation of mobile devices including smartphones. Prior works [Rander et al. 1997; Yang et al. 2002; Zhang and Chen 2004; Tanida et al. 2001; Tanida et al. 2003; Duparré et al. 2004] in camera arrays have explored multiple facets of light field capture - from viewpoint synthesis, synthetic refocus, computing range images, high speed video, and micro-optical aspects of system miniaturization. However, none of these have addressed the modifications needed to achieve the strict form factor and image quality required to make array cameras practical for mobile devices. In our approach, we customize many aspects of the camera array including lenses, pixels, sensors, and software algorithms to achieve imaging performance and form factor comparable to existing mobile phone cameras. Our contributions to the post-processing of images from camera arrays include a cost function for parallax detection that integrates across multiple color channels, and a regularized image restoration (superresolution) process that takes into account all the system degradations and adapts to a range of practical imaging conditions. The registration uncertainty from the parallax detection process is integrated into a Maximum-a-Posteriori formulation that synthesizes an estimate of the high resolution image and scene depth. We conclude with some examples of our array capabilities such as postcapture (still) refocus, video refocus, view synthesis to demonstrate motion parallax, 3D range images, and briefly address future work.
The Toll of Stalking

Information on the psychological consequences of stalking on victims is scarce. The present study aimed to investigate whether stalking victims have a heightened prevalence of psychopathology and the extent to which symptom levels are associated with stalking features. Stalking victims (N = 241) completed the General Health Questionnaire and provided information on specific features of their stalking experiences. High levels of psychopathology were found among stalking victims. Symptom levels were comparable with those of psychiatric outpatients. The frequency, pervasiveness, duration, and cessation of stalking were associated with symptom levels but explained only 9% of the variance of the level of distress. It is concluded that stalking victims generally have many symptoms of psychopathology. The symptoms are largely independent of features of their stalking experience. These findings indicate that better therapy outcomes can be expected from therapies focusing on boosting general coping skills and on decreasing general vulnerability than from therapies focusing on specifically dealing with the stalking situation.
Performance Evaluation of Private Clouds Eucalyptus versus CloudStack

the number of open source cloud management platforms is increasing day-by-day. The features of these software vary significantly and this creates a difficulty for the cloud consumers to choose the software based on their business and scientific requirements. This paper evaluates Eucalyptus and CloudStack, the two most popular open source platforms used to build private Infrastructure as a service (IaaS) clouds. The performance of virtual machines (VMs) initiated and managed by Eucalyptus and CloudStack are evaluated in terms of CPU utilization, memory bandwidth, disk I/O access speed, and network performance using suitable benchmarks. Different VM management operations such as add, delete and live migration are also assessed to determine which cloud solution is more suitable than other to be adopted as a private cloud solution. As a further performance testing, a simple web application has been implemented on the both clouds to evaluate their suitability in web application hosting. Keywords—Cloud Computing; CloudStack; Eucalyptus;
Alternatives for Habitat Protection and Rural Income Generatio

The Eighth General Increase in the Financial Resources of the IDB contains a call to take advantage of "opportunities to aid in the conservation of biological diversity," but also cautions that forest-dwellers must share in the "benefits of sustainable forest management" (IDB Document AB-1704, 18 July 1994, page 34). One way to reconcile habitat protection and local economic well-being is to promote economic activities that are both remunerative and environmentally benign. It has been suggested that nature-based tourism, the extraction of nontimber forest products, environmentally sound timber production, and genetic prospecting might fit these two criteria. The key question the research in this paper tries to answer is whether those four activities truly represent a viable economic alternative in Latin America’s environmentally fragile hinterlands. Several cases in each line of activity are analyzed to determine the level and distribution of the net financial returns they generate. Special attention was devoted to examining the degree to which net returns flow to local populations, as opposed to other economic agents. In general, examination of the rewards local populations can expect to derive from ecotourism and the harvesting of nontimber forest products suggests that allocating time and effort to those activities is unlikely to be very remunerative since unskilled labor is not particularly scarce in rural areas. In addition, little is to be gained by controlling access to natural resources, which for the most part are abundant. Moreover, making the sector-specific human capital and other investments needed for forest dwellers to capture more of the net returns from ecotourism, genetic prospecting, and so forth would probably not benefit them very much. Instead, furnishing them with education and training that is broadly applicable across the entire economy makes more sense.
A compact servo drive: Five phase, air cooled, with highly integrated inverter for industrial use

A five-phase, permanent-magnet synchronous motor with smart stator teeth “SST concept” and without star point connection is presented. The whole power electronics is integrated in the motor housing. This servo drive is much more compact and powerful than the state-of-the-art compact servo drives shown in Fig. 1 and previously published air-cooled concepts, published in [1] or [2]. The drive realizes precise rotor positioning with a low-cost magnetic encoder. Thermal problems of the integrated inverter had been solved by distributing the heat intake of the power semiconductors. This report is based on the project “EMiLE” which is funded by the German Federal Ministry of Education and Research under promotional reference number 16EMO0007. The authors are responsible for the contents of this publication.
Field theory for biophysical neural networks

The human brain is a complex system composed of a network of hundreds of billions of discrete neurons that are coupled through time dependent synapses. Simulating the entire brain is a daunting challenge. Here, we show how ideas from quantum field theory can be used to construct an effective reduced theory, which may be analyzed with lattice computations. We give some examples of how the formalism can be applied to biophysically plausible neural network models.
Message Scheduling on a Wormhole-Switched Linear Client-Server Network

The advantage of wormhole switching in interconnection networks is its distance insensitivity of communication latency under light traffic. However, this property vanishes when traffic is heavy. We consider the performance of a linear wormhole-switched network used as a real-time client-server network. Messages generated by client hosts are periodically transmitted to a central server within a predicatable delivery time. We present two algorithms for generating feasible message transmission schedules and compare their performances. It is shown that trade-off exists between quality of schedules and the network utilization. Several open problems are posed.
Placing Constructive Journalism in Context

This article describes how the social context of professional journalism has changed in the twenty-first century and why this has strengthened the need to redefine the function of journalism in this new era. Pivotal questions for journalism are: How to stay relevant for the public? How to redefine the public service function? How to deal with the increased competition? How to deal with a negative focus in the news that might offer people disillusion instead of hopeful perspectives? These questions are addressed within technological, social-cultural and economic developments that have a huge impact on the information supply. In this context, constructive journalism emerge. As a movement, it is indebted to civic journalism but takes it to the next level. Constructive journalism reconsiders the goals and values of professional journalism and cherishes a form of journalism that is public-oriented, solution-oriented, future-oriented and action-oriented, trying to avoid a bias towards negativity in the news. The break-through of the twenty-first century network model implies that journalism needs to move into a new direction, fostering cooperation, transparency and constructiveness.
Anti-Sulfoglucuronosyl Paragloboside Antibody

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by progressive degeneration of upper and lower motor neurons. Although the etiology of ALS is obscure, genetic studies of familiar ALS suggest a multifactorial etiology for this condition. Similarly, there probably are multiple causes for sporadic ALS. Autoimmune-mediated motor neuron dysfunction is one proposed etiology for sporadic ALS. In the present study, anti-glycolipid antibodies including GM1, GD1b, GD3, and sulfoglucuronosyl paragloboside (SGPG) were investigated in the sera of a large number of patient samples, including 113 ALS patients and 50 healthy controls, by means of enzyme-linked immunosorbent assay with affinity parametric complex criterion evaluation and thin-layer chromatography immunooverlay (immuno-TLC). Anti-SGPG antibodies were found in the sera of 13.3% ALS patients (15 out of 113). The highest titer reached 1:1600. The presence of anti-SGPG antibodies in the serum samples was also confirmed by immuno-TLC. Importantly, a multiple logistic regression analysis showed that the presence of anti-SGPG antibody was positively correlated with age (p < .01) and negatively correlated with ALS Functional Rating Scale score (p < .05). Moreover, the localization of SGPG-immunoreactivity on the motor neurons of rat spinal cord and a mouse motor neuronal cell line, NSC-34 was observed by an immunofluorescence method. These data suggest that SGPG could represent a specific pathogenic antigen in those ALS patients. The presence of anti-SGPG antibodies in the serum of ALS patients should represent a diagnostic biomarker of ALS, and it could reflect the severity of the disease.
Neuro-Fuzzy Quantification of Personal Perceptions of Facial Images Based on a Limited Data Set

Artificial neural networks are nonlinear techniques which typically provide one of the most accurate predictive models perceiving faces in terms of the social impressions they make on people. However, they are often not suitable to be used in many practical application domains because of their lack of transparency and comprehensibility. This paper proposes a new neuro-fuzzy method to investigate the characteristics of the facial images perceived as Iyashi by one hundred and fourteen subjects. Iyashi is a Japanese word used to describe a peculiar phenomenon that is mentally soothing, but is yet to be clearly defined. In order to gain a clear insight into the reasoning made by the nonlinear prediction models such as holographic neural networks (HNN) in the classification of Iyashi expressions, the interpretability of the proposed fuzzy-quantized HNN (FQHNN) is improved by reducing the number of input parameters, creating membership functions and extracting fuzzy rules from the responses provided by the subjects about a limited dataset of 20 facial images. The experimental results show that the proposed FQHNN achieves 2-8% increase in the prediction accuracy compared with traditional neuro-fuzzy classifiers while it extracts 35 fuzzy rules explaining what characteristics a facial image should have in order to be classified as Iyashi-stimulus for 87 subjects.