bluuebunny/crossref_metadata_2025 huggingface dataset:
Lower, Wendy, La fosa. Una familia, una fotografía, una masacre desvelada, Almería, Confluencias, 2022, 301p. ISBN: 978841255946. 21,90€
Authors: Caspistegui Francisco-Javier
Published: November 2022

Book Review
Box, Zira y César Rina Simón (eds.), El franquismo en caleidoscopio. Perspectivas y estudios transdisciplinares sobre la dictadura, Granada, Comares, 2020, 268p. ISBN: 978-84-1369-070-4. 23,75€
Authors: Caspistegui Francisco-Javier
Published: November 2022

Book Review
Modelar el paisaje para conservar el hielo. Las casas y pozos de nieve de Murcia
Authors: Gil-Bautista Rafael , Gil-Huedo Carmen
Published: November 2022

La importancia de la nieve durante la época preindustrial es bien conocida. Para recogerla y disponer de ella se edificaron neveros o casas/pozos de nieve, que compendiaban el saber popular y la pericia de los alarifes que los excavaron. No fue casual que su periodo de construcción coincidiera con la Pequeña Edad del Hielo, como tampoco lo fue la adaptación y alteración del paisaje elegido para su emplazamiento. La necesidad y el uso del hielo para la salud pública, la conservación de alimentos, la fabricación de aguas heladas o los beneficios económicos a sus gestores y fiscales a la Hacienda, entre otros, no pasaron desapercibidos. Los archivos locales y regionales nos aproximarán a estos aspectos. En esta ocasión nos centraremos en los neveros murcianos, principalmente los de Sierra Espuña, donde se concentra un gran número de estas arquitecturas populares, hoy en desuso, pero entonces imprescindibles.
Menozzi, Daniele, Crociata. Storia di un’ideologia dalla Rivoluzione francese a Bergoglio, Roma, Carocci Editore, 2020. 234p. ISBN: ‎978-8829002917. 21,95€
Authors: Rina-Simón César
Published: November 2022

Book Review
Wireless Substitution: Early Release of Estimates From the National Health Interview Survey, January-June 2022
Authors: Blumberg Stephen , Luke Julian
Published: November 2022

Using National Health Interview Survey data from the first six months of 2022, this Early Release report provides preliminary estimates of the percentages of adults and children living in homes with only wireless telephones.
Developing in situ instrumentation to monitor anthropogenic change
Authors:   , Colson Beckett C.
Published: November 2022

To predict and mitigate anthropogenic impacts on the ocean, we must understand the underlying systems that govern the ocean’s response to inputs (e.g. carbon dioxide, pollutants). Analytical models can be used to generate predictions and simulate intervention strategies, but they must be grounded with empirical observations. Unfortunately, there exists a technological gap: in situ instrumentation is often lacking or nonexistent for key parameters influenced by anthropogenic inputs. While discrete bottle samples can be collected and analyzed for these parameters, their limited spatiotemporal resolution constrains scientific inquiry. To help fill the technological gap, this dissertation presents the development of instrumentation for the ocean inorganic carbon system and microplastics. The first few chapters present the development process of CSPEC, a deep-sea laser spectrometer designed to measure the ocean carbon system through alternating measurements of the partial pressure of carbon dioxide (pCO2) and dissolved inorganic carbon (DIC). CSPEC uses tunable diode laser absorption spectroscopy (TDLAS) to measure the CO2 content of dissolved gas extracted via a membrane inlet. Chapter 2 derives membrane equilibration dynamics from first principles, thus enabling informed design decisions. The analytical results showed that cross-sensitivity to other dissolved gases can be introduced by the equilibration method, regardless of the specificity of the gas-side instrumentation. A new method, hybrid equilibration, leverages the membrane equilibration dynamics to improve time response without incurring cross-sensitivity. Chapter 3 presents POCO, a surface pCO2 instrument that employs TDLAS and a depth-compatible membrane inlet. Through laboratory and field-testing, POCO demonstrated that hybrid equilibration overcame the gas flux limitation of deep-sea membrane inlets. Chapter 4 presents CSPEC, which successfully mapped the carbon system near different hydrothermal features at 2000 m in Guaymas Basin, becoming one of the first DIC instruments field-tested at depth. Chapter 5 introduces impedance spectroscopy for quantifying microplastics directly in water. Microplastics were successfully counted, sized, and differentiated from biology in the laboratory: a step toward in situ quantification. The analytical tools and measurement systems presented in this dissertation represent a significant step towards increasing the spatiotemporal resolution of carbon system and microplastic measurements, thus enabling broader scientific inquiry in the future.
Deep Mars: CNN Classification of Mars Imagery for the PDS Imaging Atlas
Authors: Wagstaff Kiri , Lu You , Stanboli Alice , Grimes Kevin , Gowda Thamme , Padams Jordan
Published: November 2022

NASA has acquired more than 22 million images from the planet Mars. To help users find images of interest, we developed a content-based search capability for Mars rover surface images and Mars orbital images. We started with the AlexNet convolutional neural network, which was trained on Earth images, and used transfer learning to adapt the network for use with Mars images. We report on our deployment of these classifiers within the PDS Imaging Atlas, a publicly accessible web interface, to enable the first content-based image search for NASA’s Mars images.
InspireMe: Learning Sequence Models for Stories
Authors: Fortuin Vincent , Weber Romann , Schriber Sasha , Wotruba Diana , Gross Markus
Published: November 2022

We present a novel approach to modeling stories using recurrent neural networks. Different story features are extracted using natural language processing techniques and used to encode the stories as sequences. These sequences can be learned by deep neural networks, in order to predict the next story events. The predictions can be used as an inspiration for writers who experience a writer's block. We further assist writers in their creative process by generating visualizations of the character interactions in the story. We show that suggestions from our model are rated as highly as the real scenes from a set of films and that our visualizations can help people in gaining deeper story understanding.
Optimal Pricing for Distance-Based Transit Fares
Authors: Hoshino Richard , Beairsto Jeneva
Published: November 2022

Numerous urban planners advocate for differentiated transit pricing to improve both ridership and service equity. Several metropolitan cities are considering switching to a more "fair fare system," where passengers pay according to the distance travelled, rather than a flat fare or zone boundary scheme that discriminates against various marginalized groups. In this paper, we present a two-part optimal pricing formula for switching to distance-based transit fares: the first formula maximizes forecasted revenue given a target ridership, and the second formula maximizes forecasted ridership given a target revenue. Both formulas hold for all price elasticities. Our theory has been successfully tested on the SkyTrain mass transit network in Metro Vancouver, British Columbia, with over 400,000 daily passengers. This research has served Metro Vancouver's transportation authority as they consider changing their fare structure for the first time in over 30 years.
Bandit-Based Solar Panel Control
Authors: Abel David , Williams Edward , Brawner Stephen , Reif Emily , Littman Michael
Published: November 2022

Solar panels sustainably harvest energy from the sun. To improve performance, panels are often equipped with a tracking mechanism that computes the sun’s position in the sky throughout the day. Based on the tracker’s estimate of the sun’s location, a controller orients the panel to minimize the angle of incidence between solar radiant energy and the photovoltaic cells on the surface of the panel, increasing total energy harvested. Prior work has developed efficient tracking algorithms that accurately compute the sun’s location to facilitate solar tracking and control. However, always pointing a panel directly at the sun does not account for diffuse irradiance in the sky, reflected irradiance from the ground and surrounding surfaces, power required to reorient the panel, shading effects from neighboring panels and foliage, or changing weather conditions (such as clouds), all of which are contributing factors to the total energy harvested by a fleet of solar panels. In this work, we show that a bandit-based approach can increase the total energy harvested by solar panels by learning to dynamically account for such other factors. Our contribution is threefold: (1) the development of a test bed based on typical solar and irradiance models for experimenting with solar panel control using a variety of learning methods, (2) simulated validation that bandit algorithms can effectively learn to control solar panels, and (3) the design and construction of an intelligent solar panel prototype that learns to angle itself using bandit algorithms.
Upping the Game of Taxi Driving in the Age of Uber
Authors: Jha Shashi Shekhar , Cheng Shih-Fen , Lowalekar Meghna , Wong Nicholas , Rajendram Rishikeshan , Tran Trong Khiem , Varakantham Pradeep , Trong Nghia Truong , Abd Rahman Firmansyah
Published: November 2022

In most cities, taxis play an important role in providing point-to-point transportation service. If the taxi service is reliable, responsive, and cost-effective, past studies show that taxi-like services can be a viable choice in replacing a significant amount of private cars. However, making taxi services efficient is extremely challenging, mainly due to the fact that taxi drivers are self-interested and they operate with only local information. Although past research has demonstrated how recommendation systems could potentially help taxi drivers in improving their performance, most of these efforts are not feasible in practice. This is mostly due to the lack of both the comprehensive data coverage and an efficient recommendation engine that can scale to tens of thousands of drivers. In this paper, we propose a comprehensive working platform called the Driver Guidance System (DGS). With real-time citywide taxi data provided by our collaborator in Singapore, we demonstrate how we can combine real-time data analytics and large-scale optimization to create a guidance system that can potentially benefit tens of thousands of taxi drivers. Via a realistic agent-based simulation, we demonstrate that drivers following DGS can significantly improve their performance over ordinary drivers, regardless of the adoption ratios. We have concluded our system designing and building and have recently entered the field trial phase.
DiSAN: Directional Self-Attention Network for RNN/CNN-Free Language Understanding
Authors: Shen Tao , Zhou Tianyi , Long Guodong , Jiang Jing , Pan Shirui , Zhang Chengqi
Published: November 2022

Recurrent neural nets (RNN) and convolutional neural nets (CNN) are widely used on NLP tasks to capture the long-term and local dependencies, respectively. Attention mechanisms have recently attracted enormous interest due to their highly parallelizable computation, significantly less training time, and flexibility in modeling dependencies. We propose a novel attention mechanism in which the attention between elements from input sequence(s) is directional and multi-dimensional (i.e., feature-wise). A light-weight neural net, "Directional Self-Attention Network (DiSAN)," is then proposed to learn sentence embedding, based solely on the proposed attention without any RNN/CNN structure. DiSAN is only composed of a directional self-attention with temporal order encoded, followed by a multi-dimensional attention that compresses the sequence into a vector representation. Despite its simple form, DiSAN outperforms complicated RNN models on both prediction quality and time efficiency. It achieves the best test accuracy among all sentence encoding methods and improves the most recent best result by 1.02% on the Stanford Natural Language Inference (SNLI) dataset, and shows state-of-the-art test accuracy on the Stanford Sentiment Treebank (SST), Multi-Genre natural language inference (MultiNLI), Sentences Involving Compositional Knowledge (SICK), Customer Review, MPQA, TREC question-type classification and Subjectivity (SUBJ) datasets.
Large Scaled Relation Extraction With Reinforcement Learning
Authors: Zeng Xiangrong , He Shizhu , Liu Kang , Zhao Jun
Published: November 2022

Sentence relation extraction aims to extract relational facts from sentences, which is an important task in natural language processing field. Previous models rely on the manually labeled supervised dataset. However, the human annotation is costly and limits to the number of relation and data size, which is difficult to scale to large domains. In order to conduct largely scaled relation extraction, we utilize an existing knowledge base to heuristically align with texts, which not rely on human annotation and easy to scale. However, using distant supervised data for relation extraction is facing a new challenge: sentences in the distant supervised dataset are not directly labeled and not all sentences that mentioned an entity pair can represent the relation between them. To solve this problem, we propose a novel model with reinforcement learning. The relation of the entity pair is used as distant supervision and guide the training of relation extractor with the help of reinforcement learning method. We conduct two types of experiments on a publicly released dataset. Experiment results demonstrate the effectiveness of the proposed method compared with baseline models, which achieves 13.36\% improvement.
Generating Sentences Using a Dynamic Canvas
Authors: Shah Harshil , Zheng Bowen , Barber David
Published: November 2022

We introduce the Attentive Unsupervised Text (W)riter (AUTR), which is a word level generative model for natural language. It uses a recurrent neural network with a dynamic attention and canvas memory mechanism to iteratively construct sentences. By viewing the state of the memory at intermediate stages and where the model is placing its attention, we gain insight into how it constructs sentences. We demonstrate that AUTR learns a meaningful latent representation for each sentence, and achieves competitive log-likelihood lower bounds whilst being computationally efficient. It is effective at generating and reconstructing sentences, as well as imputing missing words.
Context Aware Conversational Understanding for Intelligent Agents With a Screen
Authors: Naik Vishal , Metallinou Angeliki , Goel Rahul
Published: November 2022

We describe an intelligent context-aware conversational system that incorporates screen context information to service multimodal user requests. Screen content is used for disambiguation of utterances that refer to screen objects and for enabling the user to act upon screen objects using voice commands. We propose a deep learning architecture that jointly models the user utterance and the screen and incorporates detailed screen content features. Our model is trained to optimize end to end semantic accuracy across contextual and non-contextual functionality, therefore learns the desired behavior directly from the data. We show that this approach outperforms a rule-based alternative, and can be extended in a straightforward manner to new contextual use cases. We perform detailed evaluation of contextual and non-contextual use cases and show that our system displays accurate contextual behavior without degrading the performance of non-contextual user requests.
Fact Checking in Community Forums
Authors: Mihaylova Tsvetomila , Nakov Preslav , Màrquez Lluís , Barrón-Cedeño Alberto , Mohtarami Mitra , Karadzhov Georgi , Glass James
Published: November 2022

Community Question Answering (cQA) forums are very popular nowadays, as they represent effective means for communities around particular topics to share information. Unfortunately, this information is not always factual. Thus, here we explore a new dimension in the context of cQA, which has been ignored so far: checking the veracity of answers to particular questions in cQA forums. As this is a new problem, we create a specialized dataset for it. We further propose a novel multi-faceted model, which captures information from the answer content (what is said and how), from the author profile (who says it), from the rest of the community forum (where it is said), and from external authoritative sources of information (external support). Evaluation results show a MAP value of 86.54, which is 21 points absolute above the baseline.
Learning to Extract Coherent Summary via Deep Reinforcement Learning
Authors: Wu Yuxiang , Hu Baotian
Published: November 2022

Coherence plays a critical role in producing a high-quality summary from a document. In recent years, neural extractive summarization is becoming increasingly attractive. However, most of them ignore the coherence of summaries when extracting sentences. As an effort towards extracting coherent summaries, we propose a neural coherence model to capture the cross-sentence semantic and syntactic coherence patterns. The proposed neural coherence model obviates the need for feature engineering and can be trained in an end-to-end fashion using unlabeled data. Empirical results show that the proposed neural coherence model can efficiently capture the cross-sentence coherence patterns. Using the combined output of the neural coherence model and ROUGE package as the reward, we design a reinforcement learning method to train a proposed neural extractive summarizer which is named Reinforced Neural Extractive Summarization (RNES) model. The RNES model learns to optimize coherence and informative importance of the summary simultaneously. The experimental results show that the proposed RNES outperforms existing baselines and achieves state-of-the-art performance in term of ROUGE on CNN/Daily Mail dataset. The qualitative evaluation indicates that summaries produced by RNES are more coherent and readable.
IMS-DTM: Incremental Multi-Scale Dynamic Topic Models
Authors: Chen Xilun , Candan K. Selcuk , Sapino Maria Luisa
Published: November 2022

Dynamic topic models (DTM) are commonly used for mining latent topics in evolving web corpora. In this paper, we note that a major limitation of the conventional DTM based models is that they assume a predetermined and fixed scale of topics. In reality, however, topics may have varying spans and topics of multiple scales can co-exist in a single web or social media data stream. Therefore, DTMs that assume a fixed epoch length may not be able to effectively capture latent topics and thus negatively affect accuracy. In this paper, we propose a Multi-Scale Dynamic Topic Model (MS-DTM) and a complementary Incremental Multi-Scale Dynamic Topic Model (IMS-DTM) inference method that can be used to capture latent topics and their dynamics simultaneously, at different scales. In this model, topic specific feature distributions are generated based on a multi-scale feature distribution of the previous epochs; moreover, multiple scales of the current epoch are analyzed together through a novel multi-scale incremental Gibbs sampling technique. We show that the proposed model significantly improves efficiency and effectiveness compared to the single scale dynamic DTMs and prior models that consider only multiple scales of the past.
Few Shot Transfer Learning BetweenWord Relatedness and Similarity Tasks Using A Gated Recurrent Siamese Network
Authors: O' Neill James , Buitelaar Paul
Published: November 2022

Word similarity and word relatedness are fundamental to natural language processing and more generally, understanding how humans relate concepts in semantic memory. A growing number of datasets are being proposed as evaluation benchmarks,however, the heterogeneity and focus of each respective dataset makes it difficult to draw plausible conclusions as to how a unified semantic model would perform. Additionally, we want to identify the transferability of knowledge obtained from one task to another, within the same domain and across domains. Hence, this paper first presents an evaluation and comparison of eight chosen datasets tested using the best performing regression models. As a baseline, we present regression models that incorporate both lexical featuresand word embeddings to produce consistent and competitive results compared to the state of the art.We present our main contribution, the best performing model across seven of the eight datasets - a Gated Recurrent Siamese Networkthat learns relationships between lexical word definitions.A parameter transfer learning strategy is employed for theSiamese Network. Subsequently, we present a secondary contribution which is the best performing non-sequential model:an Inductive and Transductive Transfer Learning strategy fortransferring decision trees within a Random Forest to a target task that is learned from only few instances. The method involves measuring semantic distance between hidden factored matrix representations of decision tree traversal matrices.
Slim Embedding Layers for Recurrent Neural Language Models
Authors: Li Zhongliang , Kulhanek Raymond , Wang Shaojun , Zhao Yunxin , Wu Shuang
Published: November 2022

Recurrent neural language models are the state-of-the-art models for language modeling. When the vocabulary size is large, the space taken to store the model parameters becomes the bottleneck for the use of recurrent neural language models. In this paper, we introduce a simple space compression method that randomly shares the structured parameters at both the input and output embedding layers of the recurrent neural language models to significantly reduce the size of model parameters, but still compactly represent the original input and output embedding layers. The method is easy to implement and tune. Experiments on several data sets showthat the new method can get similar perplexity and BLEU score results whileonly using a very tiny fraction of parameters.
Proposition Entailment in Educational Applications using Deep Neural Networks
Authors: Bulgarov Florin , Nielsen Rodney
Published: November 2022

The next generation of educational applications need to significantly improve the way feedback is offered to both teachers and students. Simply determining coarse-grained entailment relations between the teacher's reference answer as a whole and a student response will not be sufficient. A finer-grained analysis is needed to determine which aspects of the reference answer have been understood and which have not. To this end, we propose an approach that splits the reference answer into its constituent propositions and two methods for detecting entailment relations between each reference answer proposition and a student response. Both methods, one using hand-crafted features and an SVM and the other using word embeddings and deep neural networks, achieve significant improvements over a state-of-the-art system and two alternative approaches.
T-SLOT RECONFIGURABLE MICRO-STRIP PATCH ANTENNA WITH CAPACITIVE LOADING TECHNIQUE FOR WIMAX AND S-BAND APPLICATION
Authors: Sarsamba Mallikarjun C. , Sangulagi Prashant
Published: November 2022

A lightweight, reconfigurable frequency T-slot S-band antenna (2.01 GHz) and WiMAX (3.5 GHz) implementations are suggested in this document. The T-slot is inserted into the center of the square micro-strip patch antenna. In the T-slot antenna, a 10 pF capacitor is used with the help of the capacitor frequency and a configurable antenna is obtained. This design has an advantage of size reduction up to 70.50% for the resonant frequency compared to a conventional square patch antenna. HFSS software is used for design and simulation of the proposed antenna.
Review of Smuggling in Syntax, by Adriana Belletti and Chris Collins (Eds.). Oxford: Oxford University Press
Authors: Wang Yihan , Zhou Yong
Published: November 2022

This edited volume, Smuggling in Syntax, comprises eleven chapters which delineate a wide range of interesting applications of a smuggling approach in syntactic derivations cross-linguistically. The languages treated in this volume include the Germanic languages (English) and the Romance languages (French, Italian, and Northern Italian dialects). After summarising the contributions of different syntacticians to smuggling derivations in ten chapters, it is acknowledged that smuggling could be seen as a strategy for circumventing locality constraints on movement under the framework of the Minimalist Program, which is not only conducive to optimizing the process of syntactic derivation, but also in agreement with the economic principle of language. Though many derivations yielding smuggling need further investigation, this book indeed opens up a new perspective for the in-depth study of syntactic derivation.
Traditional and Conservative Molar Endodontic Access Cavity Designs: A Classification and Overview
Authors: Vorster Martin , Van der Vyver Peet J , Markou George
Published: November 2022

Minimally invasive endodontics' specific focus on dentine preservation is gaining popularity. Before deciding on the appropriate endodontic access cavity design, clinicians should investigate the advantages and disadvantages associated with different treatment modalities. The purpose of this article is to provide a summary of possible advantages and disadvantages of different endodontic access cavity designs with the focus on traditional, conservative and ultra-conservative endodontic access cavities, specifically in molar teeth. No conclusive evidence is found in the literature favouring one access cavity design above another and clinicians are advised to evaluate each case individually when deciding on the appropriate access cavity design for that specific case. Fracture resistance, proper shaping in order to facilitate irrigation and disinfection, as well as canal location and orifice detection are some of the contributing factors in selecting an appropriate access cavity design that will be highlighted in this article.
What’s new for the clinician– summaries of recently published papers
Authors: Yengopal V
Published: November 2022

There is substantial published literature describing the relationship between systemic health and oral, particularly periodontal health1. To list a few, periodontal diseases have been linked to cardiovascular diseases, high blood pressure, stroke, diabetes, dementia, respiratory diseases, and mortality, where an inflammatory pathway was depicted.1 Another line of research has examined the association between the number of teeth, severe dental caries, and general health among older adults and children, suggesting a nutritional pathway.1 In the United Kingdom (UK), DEPPA, the Denplan PreViser Patient Assessment, is used an online tool that assesses patients’ risk of developing future oral disease and their current oral health status is recorded using the composite 'Oral Health Score' (OHS) . Online questionnaires are completed by patient and practitioner using data collected in a routine examination.
‘‘Voicing the Voiceless’’: The Significance of the Fictional Journalist in Jamal Mahjoub’s Travelling With Djinns (2004)
Authors: Fadla Raja , Shaheen Mohammed
Published: November 2022

The present article emphasizes the role of the fictional journalist as a representative of his nation in Jamal Mahjoub’s Travelling with Djinns (2004).It equally ventures into establishing a connection between the characterization of the journalist and the postcolonial and cultural analyses, shedding light on the role of the ‘‘fourth estate’’ in giving voice to the silenced nations. The paper specifically examines how the British- Sudanese protagonist Yasin and his father committed themselves to journalism and took the responsibility to speak on behalf of their nation. Additionally, it stresses the importance of history and identity resistance to write back in the fiction of exile. Because of the journalistic restrictions and mass media dominance, Yasin turned to literature as an alternative to write back and state his counter narrative based on historical knowledge. The study bases its analysis on different postcolonial theories such as Said’s theorization on post colonialism in order to validate the significant role of the fictional journalist in voicing the voiceless.
Between Ecology and Economics: A Critical Discourse Analysis of Putri Mandalika Folklore
Authors: Hilmiyatun  , Suwandi Sarwiji , Waluyo Herman J. , Wardani Nugraheni Eko
Published: November 2022

The purpose of this article is to discuss the positioning of the Mandalika folklore, between ecology and economics. This folklore text is described by combining Norman Fairclough’s theory and methods of critical discourse analysis (CDA) with an ecocritical perspective. In his analysis, Norman Fairclough uses a three-dimensional CDA model, namely text analysis, discursive practice, and socio-cultural practice. The results showed that in text analysis related to the analysis of language features in the form of vocabulary analysis (words and meanings) that represent the nobility, women, and the ecological system, the analysis of discursive practice interpreting the story text of Putri Mandalika is interpreted as a story text that produces tradition bau nyale. Furthermore, socio-cultural practices are related to the social relations of the people in relation to the bau nyale event being a cultural event, tourism event, and ecological event. The folklore text of Putri Mandalika presents the bau nyale festival. This celebration has an ecological and economic impact. Economically, the bau nyale festival is able to improve the people’s economy, but ecologically, the bau nyale festival can damage environmental sustainability due to the lack of public awareness of environmental care, as evidenced by leaving trash everywhere.
The Types of Adposition and Their Conjunctive Use in Chinese Minority Languages
Authors: Shang Yan
Published: November 2022

From the perspective of linguistic typology, this paper investigates and analyzes the types of adposition in 38 minority languages and their conjunctive use with location words, attempts to summarize the relationship between the basic word order, the types of adposition, and the word order between adposition and location words in different languages. Then, it seeks the motives that restrict the types of adposition and their conjunctive word order, and finally analyzes the external motives of the combination of such circumpositions (Prep + Noun + Location Words) in Chinese.
Investigating the Impact of Obstacles on English Speaking Score
Authors: Alruzzi Kamal Ahmad , Yunus Kamariah , Habib Munthir M. , Sadeq Ala Eddin , Alqaryouti Marwan Harb
Published: November 2022

In the past decades, English language is considered the most popular spoken language worldwide. English for second language learners aims to develop speaking skill abilities and it is a challenging task. This study aims to investigate the perceived obstacles on the English-speaking score of Zarqa University (ZU) students majoring in English language and literature through the impact of various factors on the speaking score. This study adopts a quantitative method using a survey. Therefore, a questionnaire is designed to understand the students’ perception of the factors that may have an impact on the speaking score. A sample of (147) students, for whom English is a foreign language, from ZU from different nationalities are selected. The results indicate that academic and conversational English skill has a significant impact on the speaking score. However, linguistic obstacles, speech processing difficulties, speaking confidence, and access to speaking opportunities do not have significant impact on speaking score. This study provides insights to the academic institutes to focus on the improvement of their curricula and academic plans to further enhance the English speaking skill as second language learners.
Development and Validation of a Bioanalytical Method for the Quantification of Clopidogrel in Human Plasma by LC-MS/MS using the Accuracy Profiles
Authors:   Laboratory of Materials Nanotechnologies and Environment, Faculty of Science, Mohammed V University, Rabat, Morocco, El Khabbaz Choukri , El Orche Aimen ,   Team of Analytical and Computational Chemistry, Nanotechnology and Environment, Faculty of Science and Techniques, University of Sultan Moulay, Slimane, Beni Mellal-Morocco, Bouatia Mustapha ,   Laboratory of Analytical Chemistry, Faculty of Medicine and Pharmacy, Mohammed V University, Rabat, Morocco, Cheikhǁ Amine ,   Department of Pharmacy, Faculty of Pharmacy, Abulcasis University, Rabat, Morocco, Faouzi My El Abbes ,   Laboratory of Pharmacology and Toxicology, Faculty of Medicine and Pharmacy, Mohammed V University, Rabat, Morocco, Cherrah Yahia ,   Department of Pharmacy, Faculty of Pharmacy, Abulcasis University, Rabat, Morocco, Boussen Ratiba ,   Laboratory of Materials Nanotechnologies and Environment, Faculty of Science, Mohammed V University, Rabat, Morocco, Bouchafra Houda ,   Laboratory of Drug Sciences, Biomedical and Technological Research, Faculty of Medicine and Pharmacy, Hassane II University, Casablanca, Morocco
Published: November 2022

A basic bio-analytical method using liquid chromatography-tandem mass spectrometry (LC-MS/MS) has been developed for the determination of clopidogrel in human plasma. Clopidogrel-d3 was used as an internal standard (IS). Protein precipitation with acetonitrile for extraction of clopidogrel and it IS was used. Chromatographic separation of clopidogrel and IS was performed on a Synergi reverse phase C18 column (150 mm × 2 mm, 4 μm) using an isocratic mode. The mobile phase contained a mixture of 0.1% formic acid and acetonitrile (25 : 75) applying a flow rate of 0.4 mL/min. Ionization was performed by an electrospray ionization source (ESI), in positive MRM (Multiple Reaction Monitoring) mode. This method was validated by accuracy profiles approach using tolerance intervals limits. The calibration curve ranged from 0.0156 ng/mL to 8 ng/mL. This method can be employed effectively in bioequivalence and/or pharmacokinetics. In this method we have avoided the use of methanol in all steps of bioanalysis of clopidogrel to avert the back-conversion of clopidogrel metabolite.
Multi-wavelet analysis of three-component seismic arrays: Application to measure effective anisotropy at Piñon Flats, California
Authors: Bear Lorie K. , Pavlis Gary L. , Bokelmann Götz H. R.
Published: November 2022

We develop and apply a new technique to determine array-averaged particle motions from three-component seismic array data. The method is based on multi-wavelets, which are an extension of multi-taper spectral methods, and is a hybrid of Fourier and time-domain methods of array processing. Particle motions are determined by a time-domain principal-component method. A complex singular value decomposition is used on wavelet transformed signals assembled into multiple matrices (one for each wavelet). The eigenvector of the largest singular value of each matrix is used to estimate the phase between individual signals. We determine the relative phase between components to estimate an average particle motion ellipse for the array. The estimation procedure is made more stable by the redundancy inherent in the multi-wavelets and by M-estimators applied to individual phase factors in the complex plane. The method is applied to data from three-component array experiments conducted at Piñon Flats, California, in 1990 and 1991. We find remarkable departures of P-wave particle motions from the pure longitudinal motion expected for an isotropic media. Anomalies as large as 40° are measured from some azimuths. The azimuthally varying particle-motion anomalies are frequency dependent, generally increasing in magnitude as frequency increases. Borehole measurements from sensors at 153 and 274 m depth below the array show a pattern indistinguishable from the surface sensors. The data are fit with a dipping, transversely isotropic medium with a symmetry plane having a strike of 70° and a dip of 30° to the northwest. We attribute our results to three superimposed effects: (1) an anisotropy of the near surface induced by preferential weathering of the grandiorite bedrock along joints, (2) a larger scale anisotropy induced by structural and intrinsic anisotropy related to the Santa Rosa mylonite, and (3) near-surface scattering.
A Comprehensive Study of Current and Future Trends in Cloud Forensics
Authors: Achar Sandesh
Published: November 2022

Organizations are increasingly turning to cloud computing, which offers convenience and provides services based on virtualization technology. Some benefits of cloud computing include accessibility, availability, flexibility, vast storage capacity, speed, flexibility, and on-demand network connectivity. Significant potential security dangers are associated with this new technology, and digital forensics cannot keep up with the rapid adoption of cloud computing solutions. This study gives an overview of cloud forensics to offer better prospects, highlighting the existing problems and difficulties. It also suggests actions that can be taken to address these difficulties.
Enterprise SaaS Workloads on New-Generation Infrastructure-as-Code (IaC) on Multi-Cloud Platforms
Authors: Achar Sandesh
Published: November 2022

Cloud Computing has become the primary model used by DevOps practitioners and researchers to provision infrastructure in minimal time. But recently, the traditional method of using a single cloud provider has fallen out of favor due to several limitations regarding performance, compliance rules, geographical reach, and vendor lock-in. To address these issues, industry and academia are implementing multiple clouds (i.e., multi-cloud). However, managing the infrastructure provisioning of enterprise SaaS applications faces several challenges, such as configuration drift and the heterogeneity of cloud providers. This has seen Infrastructure-as-Code (IaC) technologies being used to automate the deployment of SaaS applications. IaC facilitates the rapid deployment of new versions of application infrastructures without degrading quality or stability. Therefore, this work presents a vision of uniformly managing the infrastructure provisioning of enterprise SaaS applications that utilize multiple cloud providers. Hence, we introduce an initial design for the IaC-based Multi-Cloud Deployment pattern and discuss how it addresses the relative challenges.
Propiedades psicométricas para medir factores del trabajo remoto: un análisis exploratorio en colaboradores estudiantes
Authors: Uribe Kajatt Justina , Geraldo-Campos Luis Alberto , Rey de Castro Hidalgo Daniel Enrique , Vargas Dávila José Gerardo , Jiménez de Aliaga Kelly Myriam
Published: November 2022

El objetivo de este trabajo fue analizar las propiedades psicométricas de la escala de factores que intervienen en el trabajo remoto. Se realizó un estudio de tipo instrumental de corte transversal, el cual implicó un proceso de revisión de literatura, construcción del instrumento y validación por especialistas. Se realizó una prueba piloto conformada por 20 participantes, después se contó con 148 trabajadores estudiantes, cuyas respuestas permitieron realizar un análisis de discriminación de ítems, y por último se realizó un análisis factorial exploratorio. Se encontró pertinencia en las propiedades psicométricas del instrumento, conformadas por tres factores: soporte laboral tecnológico, jornada de trabajo y bienestar social. Se concluye que el instrumento propuesto se puede aplicar a cualquier organización laboral para identificar los factores que intervienen en el trabajo remoto.
An Analysis of Marketing Strategy in Small-and-Medium-sized Colombian Enterprises
Authors: Franco-Ángel Mónica , Awad Urbano Mariam Rabih
Published: November 2022

This study analyses the marketing strategy implemented in SMEs. A case study is carried out with eight Colombian manufacturing companies with more than ten years of creation and more than fifty employees. The results show that these companies do not follow traditional marketing models, nor do they have formal and structured processes. Instead, their marketing strategy is based on understanding their customers, with whom they have a close relationship, by developing innovative products that meet their needs, structuring their costs to offer a competitive price, and constantly communicating the value they generate to the market. This article concludes that these companies follow a marketing strategy that allows them to be sustainable and competitive with the available resources.
Atlas de infraestructuras de integración de América Latina y el Caribe: mapeando infraestructuras de transporte y logística de alto impacto en las cadenas de valor regionales
Authors: Granda Isabel , Landaverde Osvaldo , Pinto Ayala Ana María , Peña Mariam
Published: November 2022

En los últimos 30 años, la integración regional de América Latina y el Caribe ha sido un tema fundamental en la agenda de desarrollo y una prioridad para el Banco Interamericano de Desarrollo y sus países miembro. La vinculación de las cadenas de valor regionales y globales se ha intensificado de forma considerable en las últimas décadas y por ello la infraestructura, en combinación con los servicios logísticos, se pone de relieve como principal habilitante para el aprovechamiento de las sinergias de mercado. En especial, en el contexto del COVID-19, el trinomio de infraestructura, inversión e integración adquiere una dimensión preponderante, pues a través de la reconfiguración y relocalización de las cadenas de valor globales hacia América Latina y el Caribe (“nearshoring”), tiene el potencial de detonar la recuperación de los países, así como de cerrar las brechas y desigualdades preexistentes entre y dentro de las economías.
Innovative and Entrepreneurial Universities in Latin America
Authors:   Organization for Economic Cooperation and Development,   Inter American Development Bank
Published: November 2022

The review examines how higher education institutions are supporting innovation and entrepreneurship in their surrounding communities. The study focuses on eleven universities located in six countries in Latin America: Chile, Colombia, Mexico, Brazil, Argentina and Uruguay. The study finds that selected institutions are actively supporting entrepreneurs (university students, but also local entrepreneurs) through courses, incubation and acceleration activities. It also shows that universities are actively engaging with external stakeholders in their surrounding communities, to spur innovation through joint-research, organisation of events (such as festivals, competition). It finds that that while COVID-19 pandemic brought about some challenges, universities managed to stay afloat and keep a steady stream of support to entrepreneurs and partners. The review also illustrates the challenges that universities face when developing these activities (lack of funding, unclear regulation for intellectual property development, etc.) and highlights some opportunities that universities should leverage, particularly in the current context.
The Material and Living Conditions Problems of NKVD– MVD Camps in Western Siberia and their Solutions
Authors:   International Innovative University, Markdorf N. M.
Published: November 2022

In this article discusses the basic material and conditioners problems of NKVD–MVD camps in Western Siberia and their solutions in World War II and the postwar period and their influence on the dynamics of the employment fund war prisoners and interned civilians in the Western Siberian region. The author concludes that the unresolved these issues were result of increased health losses, reduced labor fund, low profitability of the camps.
Cultural and Intellectual Life of an English City of an Epoch of Restoration in Perception of Contemporaries
Authors:   Saratov State University, Mosolkina T. V.
Published: November 2022

In article there is a speech about level of cultural requirements of Englishmen of an epoch of Restoration, about an emotional climate, interests and predilections of English townspeople of second half XVII century.
«Golden Age» of Meschanstvo: Urban Daily Routine of Meschanstvo Estate in the 50–60s of the XIX Century
Authors:   Saratov State University, Kobozeva Z. M.
Published: November 2022

The article provides the analysis of the meschanstvo estate daily routine in the provincial Samara town in the 50–60s of the XIX century. The period of time which precedes the City Reform of 1870 is considered to be “the Golden age” of the meschanstvo estate identity due to the fact that in this very period of time meschanstvo acted especially actively within the town community.
Generalidades del ambiente de cabina de la Estación Espacial Internacional como análogo para misiones de tipo exploración: una visión desde la medicina aeroespacial
Authors: Malpica Hincapie Diego Leonel
Published: November 2022

La salud y la seguridad de los astronautas en misiones de exploración espacial dependen del ambiente donde habitan, y la supervivencia en ambientes extremos requiere sistemas robustos que provean protección y les ofrezcan una atmósfera que les permita tener un desempeño normal en un entorno hostil. Es importante, entonces, conocer la cercana relación de los sistemas de soporte de vida, y el impacto en el bienestar de aquellos que trabajan en un espacio confinado con mínima utilización de recursos y energía.

El objetivo de esta revisión es describir los sistemas de control ambiental y de soporte de vida de la Estación Espacial Internacional, y relatar el impacto en la salud y el rendimiento psicofísico de los astronautas si estos no funcionan normalmente. Se hacen búsquedas en las bases de datos Scopus, Ovid, arXiv.org, SAGE, BioMed, ClincalKey, ProQuest, EBSCP, SpringerLink, Web of Science, Google Scholar y Pubmed, que integren el sistema de control ambiental y soporte de vida con los fenómenos fisiopatológicos en caso de emergencia. Se recopilan 649 referencias con las estrategias de búsqueda y se restan aquellas repetidas (445) y cuyo texto completo no se consiguió (133), con un total de 71 referencias para análisis. Se discuten las características habitacionales de la Estación Espacial Internacional en términos de calidad y cantidad de aire disponible, la composición de los gases, la producción de oxígeno y nitrógeno, el barrido del dióxido de carbono y sus efectos en el astronauta bajo condiciones de microgravedad. Además, se exploran efectos toxicológicos, del ambiente microbiológico, acústica y vigilancia de la exposición a radiación electromagnética. Las futuras misiones de tipo exploración espacial necesitarán sistemas de control ambiental robustos con bajo riesgo de fallo y probable uso de recursos in situ.
La negación de área, posibilidad para Colombia como empleo de una estrategia
Authors: Parra Hernandez Nelson Giovanni , Salgado Luzia Ilmar Ubiratan
Published: November 2022

El surgimiento del concepto de negación de área trajo al pensamiento académico una serie de conceptos teórico-estratégicos que pueden ser utilizados por los países que los quieran emplear, a fin de defender sus áreas de interés. En este sentido, el objetivo de este artículo de reflexión es formular las condiciones de empleo más idóneas de la negación de área de las que dispone Colombia para posicionar el interés nacional y construir o proyectar su poder.

El propósito es despertar el interés de los lectores acerca de los conceptos de negación de área y cómo pueden ser útiles en el ámbito estratégico, pero también desde un enfoque académico a modo de referente para el uso de los recursos de defensa. Es necesario entender esta estrategia de negación de área para la defensa y la seguridad nacional en Colombia y en otros países dentro del hemisferio.  Como resultado, tenemos que esa estrategia debe priorizar las amenazas a los objetivos e intereses nacionales de Colombia. Se concluye que es evidente la necesidad de reestructuración y modernización de la defensa aérea, antiaérea y terrestre para la seguridad nacional, es decir, en todos los dominios.