This post looks at how to translate the names of the two* main types of public-form Spanish notarial acts, escrituras públicas and actas notariales. It also identifies handy language to use in translations of them. Escritura pública An escritura pública records an act executed before a notary. How you translate the name of an escritura […]

This post looks at the main public registers (registros) in Spain. It outlines what they are for and lists common translations and similar entities in English-speaking countries. Whether each registro is more a list or a place (or both) is also covered. This key distinction (described in this post) can affect the translation or at […]

El Diccionario de uso del español de María Moliner es una obra monumental. Son dos volúmenes que la autora iba elaborando pacientemente en el salón […]

Origen

E-mail spam is no more garbage but risk since it recently includes virus attachments and spyware agents which make the recipients' system ruined, therefore, there is an emerging need for spam detection. Many spam detection techniques based on machine learning techniques have been proposed. As the amount of spam has been increased tremendously using bulk mailing tools, spam detection techniques should counteract with it. To cope with this, parameters optimization and feature selection have been used to reduce processing overheads while guaranteeing high detection rates. However, previous approaches have not taken into account feature variable importance and optimal number of features. Moreover, to the best of our knowledge, there is no approach which uses both parameters optimization and feature selection together for spam detection. In this paper, we propose a spam detection model enabling both parameters optimization and optimal feature selection; we optimize two parameters of detection models using Random Forests (RF) so as to maximize the detection rates. We provide the variable importance of each feature so that it is easy to eliminate the irrelevant features. Furthermore, we decide an optimal number of selected features using two methods; (i) only one parameters optimization during overall feature selection and (ii) parameters optimization in every feature elimination phase. Finally, we evaluate our spam detection model with cost-sensitive measures to avoid misclassification of legitimate messages, since the cost of classifying a legitimate message as a spam far outweighs the cost of classifying a spam as a legitimate message. We perform experiments on Spambase dataset and show the feasibility of our approaches.

Spatial Hypertext Wiki (ShyWiki) is a wiki which represents knowledge using notes that are spatially distributed in wiki pages and have visual characteristics such as colour, size, or font type. The use of spatial and visual characteristics in wikis is important to improve human comprehension, creation and organization of knowledge. Another important capability in wikis is to allow machines to process knowledge. Wikis that formally structure knowledge for this purpose are called semantic wikis. This paper describes how ShyWiki can make use of spatial hypertext in order to be a semantic wiki. ShyWiki can represent knowledge at different levels of formality. Users of ShyWiki can annotate the content and represent semantic relations without being experts of semantic web data description languages. The spatial hypertext features make it suitable for users to represent unstructured knowledge and implicit graphic relations among concepts. In addition, semantic web and spatial hypertext features are combined to represent structured knowledge. The semantic web features of ShyWiki improve navigation and publish the wiki knowledge as RDF resources, including the implicit relations that are analyzed using a spatial parser.

Espagne : des problèmes sanitaires dans les zones sinistrées par les inondations

1. Long ago, Voyager 2 might have caught Uranus at a bad time  Space.com
2. The anomalous state of Uranus’s magnetosphere during the Voyager 2 flyby  Nature.com
3. Potential For Life Found On Uranus' Moons, Scientists Reveal  NDTV
4. New Uranus research suggests what’s known about the planet could be wrong  CNN
5. Uranus Might Have Experienced a Freak Event When Voyager 2 Visited  The New York Times

1. British writer Samantha Harvey wins Booker Prize for space novel Orbital  Al Jazeera English
2. Samantha Harvey’s ‘beautiful and ambitious’ Orbital wins Booker prize  The Guardian
3. Samantha Harvey wins the Booker prize for “Orbital”  The Economist
4. British writer Samantha Harvey’s space-station novel ‘Orbital’ wins 2024 Booker Prize  CNN
5. Booker Prize Is Awarded to Samantha Harvey’s ‘Orbital’  The New York Times

Running and longevity: Sub-four-minute milers increase their lifespan by up to 9 years  Genetic Literacy Project

The problem of dispatching is key to management of shared bicycles. Considering the number of borrowing and returning events during the dispatching period, optimisation plans of shared bicycles dispatching are studied in this paper. Firstly, the dispatching model of shared bicycles is built, which regards the dispatching cost and lost demand as optimised objectives. Secondly, the solution algorithm is designed based on non-dominated Genetic Algorithm. Finally, a case is given to illustrate the application of the method. The research results show that the method proposed in the paper can get optimised dispatching plans, and the model considering borrowing and returning during dispatching period has better effects with a 39.3% decrease in lost demand.

With the development of urban construction, its spatial evolution is also influenced by behavioural actors such as enterprises, residents, and environmental factors, leading to some decision-making behaviours that are not conducive to urban public space and environmental design. At the same time, some cities are vulnerable to various factors such as distance factors, transportation factors, and human psychological factors during the construction of public areas, resulting in a decline in the quality of urban human settlements. Urban public space is the guarantee of urban life. For this, in order to standardise urban public space and improve the quality of urban living environment, the standardisation of the environment of urban public space is required. The rapid development of intelligent algorithms and fuzzy control provides technical support for the environmental design of urban public spaces. Through the modelling of intelligent algorithms and the construction of fuzzy space, it can meet the diverse.

Elections hold immense significance in shaping the leadership of a nation or organisation, serving as a pivotal moment that influences the trajectory of the entity involved. Despite their centrality to modern democratic systems, elections face a significant hurdle: widespread mistrust in the electoral process. This pervasive lack of confidence poses a substantial threat to the democratic framework, even in the case of prominent democracies such as India and US, where inherent flaws persist in the electoral system. Issues such as vote rigging, electronic voting machine (EVM) hacking, election manipulation, and polling booth capturing remain prominent concerns within the current voting paradigm. Leveraging blockchain for electronic voting systems offers an effective solution to alleviate the prevailing apprehensions associated with e-voting. By incorporating blockchain into the electoral process, the integrity and security of the system could be significantly strengthened, addressing the current vulnerabilities and fostering trust in democratic elections.

In this paper, we study and provide algorithms for source-provenance of answers to extended SPARQL queries. Extended SPARQL queries are an extension of SPARQL 1.1 queries which support not only a single dataset but multiple datasets, each in a particular context. For example, normal subqueries, aggregate subqueries, (NOT) EXISTS filter subqueries may (optionally) have their own dataset. Additionally, GRAPH patterns can query multiple RDF graphs from the local FROM NAMED dataset and not just one. For monotonic queries, the source why provenance sets that we derive for an answer mapping are each the minimal set of sources appearing in the query that if we consider as they are while the rest of the sources are considered empty, we derive the same answer mapping. We show that this property does not hold for non-monotonic queries. Among others, knowing source why provenance is of critical importance for judging confidence on the answer, allow information quality assessment, accountability, as well as understanding the temporal and spatial status of information.

As more institutions continue to work with large and diverse type of content for their digital repositories, there is an inherent need to evaluate, prototype, and implement user-friendly websites -regardless of the digital files' size, format, location or the content management system in use. This article aims to provide an overview of the need and current development of Document Viewers for digitized objects in DSpace repositories -includign a local viewer developed for an newspaper collection and four other viewers currently implemented in DSpace repositories. According to the DSpace Registry, 22% of institutions are currently storing "Images" in their repositories and 21% are using DSpace for non-traditional IR content such as: Image Repository, Subject Repository, Museum Cultural, or Learning Resources. The combination of current technologies such as Djatoka Image Server, IIPImage Server, DjVu Libre, and the Internet Archive BookReader, as well as the growing number of digital repositories hosting digitized content, suggests that the DSpace community will probably benefit with an "out-of-the-box" Document Viewer, especially one for large, high-resolution, and multi-page objects.

Aim/Purpose: Little is known of the cultural competence or leadership styles of a minority owned newspaper. This autoethnography serves to benchmark one early 1990s example. Background: I focused on a series of flashbacks to observe an African American weekly newspaper editor-in-chief for whom I reported to 25 years ago. In my reflections I sought to answer these questions: How do minorities in entrepreneurial organizations view their own identity, their cultural competence? What degree of this perception is conveyed fairly and equitably in the community they serve? Methodology: Autoethnography using both flashbacks and article artifacts applied to the leadership of an early 1990s African American weekly newspaper. Contribution: Since a literature gap of minority newspaper cultural competence examples is apparent, this observation can serve as a benchmark to springboard off older studies like that of Barbarin (1978) and that by examining the leadership styles and editorial authenticity as noted by The Chicago School of Media Theory (2018), these results can be used for comparison to other such minority owned publications. Findings: By bringing people together, mixing them up, and conducting business any other way than routine helped the Afro-American Gazette, Grand Rapids, proudly display a confidence sense of cultural competence. The result was a potentiating leadership style, and this style positively changed the perception of culture, a social theory change example. Recommendations for Practitioners: For the minority leaders of such publications, this example demonstrates effective use of potentiating leadership to positively change the perception of the quality of such minority owned newspapers. Recommendations for Researchers: Such an autoethnography could be used by others to help document other examples of cultural competence in other minority owned newspapers. Impact on Society: The overall impact shows that leadership at such minority owned publications can influence the community into a positive social change example. Future Research: Research in the areas of culture competence, leadership, within minority owned newspapers as well as other minority alternative publications and websites can be observed with a focus on what works right as well as examples that might show little social change model influence. The suggestion is to conduct the research while employed if possible, instead of relying on flashbacks.

Aim/Purpose: In this research, we examined the influence of the information system (IS) quality dimensions proposed by Wixom and Todd on reading satisfaction of online newspaper readers in Bangladesh, especially the readers’ intention to revisit and recommendations through electronic word-of-mouth (eWOM). Background: We identified the top 50 most visited websites, of which 13 were online newspapers, although their ranking among Bangladesh online newspapers varies from month to month. The literature illustrates that, despite the wide availability of online news portals and the fluctuations in frequency of visits, little is known about the factors that affect the satisfaction, word-of-mouth, and frequency of visits of readers. An understanding of reader satisfaction will help to gain richer insights into the phenomenon of readers’ intention to revisit and recommendation by eWOM. Stakeholders of online newspapers can then focus on those factors to increase visits to their websites, which will help them attract online advertisements from different organisations. Methodology: Data were collected using a structured questionnaire, from 217 people who responded to the survey. We used SmartPLS 3 to analyze the data collected, as it is based on second-generation analysis, which in turn is based on structural equation modeling (SEM). Contribution: This research explores the impacts of technological dimensions on readers’ satisfaction, as most of the previous research has focused on cultural or social dimensions. Findings: The results supported all of the hypothesized relationships between technological dimensions and reader satisfaction with online newspapers, except for one. The first, information, was predicted with accuracy and completeness, while the second object-based belief, system quality, was predicted by its accessibility, flexibility, reliability, and timeliness. Overall, quality factors influencing readers’ satisfaction were shown to lead to word-of-mouth revisit intentions. Our proposed model was empirically tested and has contributed to a nascent body of knowledge about readers’ revisit intentions and eWOM recommendations regarding online newspapers. It was also shown that strong satisfaction leads to higher revisit intention and eWOM. Recommendations for Practitioners: To keep the users satisfied, online newspapers need to focus on improving information quality (IQ) and system quality (SQ). If they do this well, they will be rewarded with higher revisit intention and recommendations by eWOM. Recommendation for Researchers: This study extends Oh’s customer loyalty model by integrating the Wixom-Todd model. This study reinforces an alternative rationale of the construct satisfaction. Future Research: We ignored negative stimulus like technostress, which can have an impact on satisfaction. In future, we will test the relationship between technostress and its impact on online newspaper reading.

Aim/Purpose: This study presents a novel deep learning-based framework designed to enhance spontaneous micro-expression recognition by effectively increasing the amount and variety of data and balancing the class distribution to improve recognition accuracy. Background: Micro-expression recognition using deep learning requires large amounts of data. Micro-expression datasets are relatively small, and their class distribution is not balanced. Methodology: This study developed a framework using a deep learning-based model to recognize spontaneous micro-expressions on a person’s face. The framework also includes several technical stages, including image and data preprocessing. In data preprocessing, data augmentation is carried out to increase the amount and variety of data and class balancing to balance the distribution of sample classes in the dataset. Contribution: This study’s essential contribution lies in enhancing the accuracy of micro-expression recognition and overcoming the limited amount of data and imbalanced class distribution that typically leads to overfitting. Findings: The results indicate that the proposed framework, with its data preprocessing stages and deep learning model, significantly increases the accuracy of micro-expression recognition by overcoming dataset limitations and producing a balanced class distribution. This leads to improved micro-expression recognition accuracy using deep learning techniques. Recommendations for Practitioners: Practitioners can utilize the model produced by the proposed framework, which was developed to recognize spontaneous micro-expressions on a person’s face, by implementing it as an emotional analysis application based on facial micro-expressions. Recommendation for Researchers: Researchers involved in the development of a spontaneous micro-expression recognition framework for analyzing hidden emotions from a person’s face are playing an essential role in advancing this field and continue to search for more innovative deep learning-based solutions that continue to explore techniques to increase the amount and variety of data and find solutions to balancing the number of sample classes in various micro-expression datasets. They can further improvise to develop deep learning model architectures that are more suitable and relevant according to the needs of recognition tasks and the various characteristics of different datasets. Impact on Society: The proposed framework could significantly impact society by providing a reliable model for recognizing spontaneous micro-expressions in real-world applications, ranging from security systems and criminal investigations to healthcare and emotional analysis. Future Research: Developing a spontaneous micro-expression recognition framework based on spatial and temporal flow requires the learning model to classify optimal features. Our future work will focus more on exploring micro-expression features by developing various alternative learning models and increasing the weights of spatial and temporal features.

Campus discovery is an important feature of a university student induction process. Approaches towards campus discovery differ from course to course and can comprise guided tours that are often lengthy and uninspiring, or self-guided tours that run the risk of students failing to complete them. This paper describes a campus self-discovery induction game (Geospatial Crypto Reconnaissance) which aims to make students aware of campus resources and facilities, whilst at the same time allowing students to make friends and complete the game in an enthusing and exciting way. In this paper we describe the game construct, which comprises of a location, message, and artefact, and also the gameplay. Geospatial Crypto Reconnaissance requires students to identify a series of photographs from around the campus, to capture the GPS coordinates of the location of the photograph, to decipher a ciphered message and then to return both the GPS coordinates and the message for each photograph, proving that the student has attended the location. The game had a very high satisfaction score and we present an analysis of student feedback on the game and also provide guidance on how the game can be adopted for less technical cohorts of students.

Aim/Purpose: As online video lectures rapidly gain popularity in formal and informal learning environments, one of their main challenges is student retention. This study investigates the influence of adding interactivity to online video lectures on students’ attention span. Background: Interactivity is perceived as increasing the attention span of learners and improving the quality of learning. However, interactivity may be regarded as an interruption, which distracts students. Furthermore, adding interactive elements to online video lectures requires additional investment of various resources. Therefore, it is important to investigate the impact of adding interactivity to online video lectures on the attention span of learners. Methodology: This study employed a learning analytics approach, obtained data from Google Analytics, and analyzed data of two Massive Open Online Courses (MOOCs) that were developed by the Open University of Israel in order to make English for academic purposes (EAP) courses freely accessible. Contribution: The paper provides important insights, based on quantitative empirical research, on: integrating interactive elements in online videos; the impact of video length; and differences between two groups of advanced and basic learners. Furthermore, it demonstrates how learning analytics may be used for improving instructional design. Findings: The findings suggest that interactivity may increase the attention span of learners, as measured by the average online video lecture viewing completion percentage, before and after the addition of interactivity. However, when the lecture is longer than about 15 minutes, the completion percentages decrease, even after adding interactive elements. Recommendations for Practitioners: Adding interactivity to online video lectures and controlling their length is expected to increase the attention span of learners. Recommendation for Researchers: Learning analytics is a powerful quantitative methodology for identifying ways to improve learning processes. Impact on Society: Providing practical insights on mechanisms for increasing the attention span of learners is expected to improve social inclusion. Future Research: Discovering further best practices to improve the effectiveness of online video lectures for diverse learners.

Aim/Purpose: Personal Knowledge Management (PKM) has been envisaged as a crucial tool for the growing creative class of knowledge workers, but adequate technological solutions have not been forthcoming. Background: Based on former affordance-related publications (primarily concerned with communication, community-building, collaboration, and social knowledge sharing), the common and differing narratives in relation to PKM are investigated in order to suggest further PKM capabilities and affordances in need to be conferred. Methodology: The paper follows up on a series of the author’s PKM-related publications, firmly rooted in design science research (DSR) methods and aimed at creating an innovative PKM concept and prototype system. Contribution: The affordances presented offer PKM system users the means to retain and build upon knowledge acquired in order to sustain personal growth and facilitate productive collaborations between fellow learners and/or professional acquaintances. Findings: The results call for an extension of Nonaka’s SECI model and ‘ba’ concept and provide arguments for and evidence supporting the claims that the PKM concept and system is able to facilitate better knowledge traceability and KM practices. Recommendations and Impact on Society: Together with the prior publications, the paper points to current KM shortcomings and presents a novel trans-disciplinary approach offering appealing opportunities for stakeholders engaged in the context of curation, education, research, development, business, and entrepreneurship. Its potential to tackle opportunity divides has been addressed via a PKM for Development (PKM4D) Framework. Future DSR Activities: After completing the test phase of the prototype, its transformation into a viable PKM system and cloud-based server based on a rapid development platform and a noSQL-database is estimated to take 12 months.

This paper presents a novel deep learning technique called quantum dilated convolutional neural network-DenseNet (Q-DenseNet) for prediction of heart disease in spark framework. At first, the input data taken from the database is allowed for data partitioning using fast fuzzy C-means clustering (FFCM). The partitioned data is fed into spark framework, where pre-processed by missing data imputation and quantile normalisation. The pre-processed data is further allowed for selection of suitable features. Then, the selected features from the slave nodes are merged and fed into master node. The Q-DenseNet is used in master node for the prediction of heart disease. The performance improvement of the designed Q-DenseNet model is validated by comparing with traditional prediction models. Here, the Q-DenseNet method achieved superior performance with maximum of 92.65% specificity, 91.74% sensitivity, and 90.15% accuracy.

Zhigang WU,Yaohui ZHU, Vol.E107-D, No.11, pp.1385-1395
This article focuses on improving the BiSeNet v2 bilateral branch image segmentation network structure, enhancing its learning ability for spatial details and overall image segmentation accuracy. A modified network called “BiconvNet” is proposed. Firstly, to extract shallow spatial details more effectively, a parallel concatenated strip and dilated (PCSD) convolution module is proposed and used to extract local features and surrounding contextual features in the detail branch. Continuing on, the semantic branch is reconstructed using the lightweight capability of depth separable convolution and high performance of ConvNet, in order to enable more efficient learning of deep advanced semantic features. Finally, fine-tuning is performed on the bilateral guidance aggregation layer of BiSeNet v2, enabling better fusion of the feature maps output by the detail branch and semantic branch. The experimental part discusses the contribution of stripe convolution and different sizes of empty convolution to image segmentation accuracy, and compares them with common convolutions such as Conv2d convolution, CG convolution and CCA convolution. The experiment proves that the PCSD convolution module proposed in this paper has the highest segmentation accuracy in all categories of the Cityscapes dataset compared with common convolutions. BiConvNet achieved a 9.39% accuracy improvement over the BiSeNet v2 network, with only a slight increase of 1.18M in model parameters. A mIoU accuracy of 68.75% was achieved on the validation set. Furthermore, through comparative experiments with commonly used autonomous driving image segmentation algorithms in recent years, BiConvNet demonstrates strong competitive advantages in segmentation accuracy on the Cityscapes and BDD100K datasets.
Publication Date: 2024/11/01

Studies suggest that category-spanning organizations receive lower evaluation and perform worse than organizations focused on a single category. We propose that (1) these effects are contingent on clients' theory of value and that as clients expect more sophisticated services, they tend to value category spanners more positively and (2) the evaluation of producers mediates the relationship between category spanning and performance. We test our hypotheses using original data on corporate legal services in three markets (London, New York City, and Paris) over the decade 2000-2010. We find that (1) category spanners receive a better evaluation, and more so when their categorical combination is more inclusive and (2) evaluation mediates significantly the relationship between category spanning and performance. This study enriches our understanding of how audiences apprehend a whole market category system and why organizations span categories.

Many online are raising questions about a recent spate of public violence, as officials continue to censor discussion.

Spain's Civil Protection Agency sent a mass alert to phones warning of an "extreme risk of rainfall".

MADRID: Schools in flood-hit towns in eastern Spain will be closed on Wednesday as the region braces for more torrential rains, officials said.

National weather office AEMET on Tuesday placed parts of Valencia as well as Catalonia in the northeast and Andalusia in the south and the Balearic Islands on orange alert -- the second highest level -- for strong or torrential rains until Thursday.

The alert comes two weeks after an exceptional Mediterranean storm caused Spain's deadliest floods in decades.

The October 29 storm killed 223 people, the bulk of them in the Valencia region, according to the latest official tally.

Dozens of town halls in Valencia, including Chiva, one of the worst-hit sites, suspended classes and closed public gyms because of the threats of more heavy rain.

“In response to the information provided by the emergency services, school and sports activities will be SUSPENDED from tomorrow until further notice,“ Chiva town hall wrote on X.

A military vehicle drove through towns in Valencia using a megaphone to warn of the expected storms and urge people not to make “unnecessary trips,“ images broadcast on Spanish public television TVE showed,

While the amount of rain that is forecast to fall in Valencia is less than what fell two weeks ago, local officials warned sewage systems are clogged with mud and could struggle to cope with significant precipitation making more flooding possible.

Outrage at the authorities for their perceived mismanagement before and after the floods triggered mass protests on Saturday, the largest in Valencia city which drew 130,000 people.

Classes were also suspended on Wednesday in parts of southern Catalonia as well as some towns and cities in Andalusia, inclusing Malaga.

Have you ever been browsing a website and then later received an email from the company even though you didn’t provide your email address? Or maybe you added items to your cart on a shopping website but decided not to follow through with the purchase. Then you get an email asking whether you forgot to […]

The post How Spammers Get Your Email Address appeared first on Clark Howard.

Mehwish’s sequin skirt was perfectly complemented by a matching silk button-down that whispered "class"

John McFall becoming the first person with a physical disability to be effectively cleared for future missions by ESA

Mission Polaris Dawn sees two private astronauts step into orbit, paving the way for future space missions to Mars

Meghan Markle sparked another controversy after she wore a poppy that slightly differed from that of Prince Harry's in a recent video addressing children's digital safety.

A journalist has pointed out that the Duchess of Sussex’s poppy lacked leaves on the stalk, resembling...

Prince Harry sparks frenzy because of his ‘terrorizing' plans for Christmas

Prince Harry’s terrifying effect on Christmas in 2024, for the Windsors has just become a point of conversation.

So much so that one expert has even stepped forward to offer his thoughts on the...

Our bro Miguel Smajli was together with Jiri Blabol, Simone Barraco, Mo Nussbaumer, Teammanager Ryan Sher and Saul Vilar for one week out in the streets of Madrid. Despite the bad weather, some injuries for Simo, Jiri and Ryan, the guys made the best out of it and campe up with a video full of technical street riding. Healing vibes to Ryan who brokes his ellbow during a gap to wallride. Lean back and enjoy some incredible clips. Have fun watching the video, your kunstform BMX Shop Team!

A worshipper holds up a cross during the Good Friday procession at the Via Dolorosa in Jerusalem's Old City, March 29. — Reuters

A 76-year-old monk died on Monday after being attacked by a man shouting "I am Jesus Christ" in a monastery in southeastern Spain, the religious order...

The White House should not overlook the complex opportunities and challenge of space now and in the future, according to a new "Presidential Transition: Priority Topic Memo" released by Mitre, a nonprofit group established in 1958 and focused on national security, aerospace, artificial intelligence and more.

China's military forces are rapidly building up space warfare capabilities for use in a future conflict, two top American generals said on Wednesday.

Activist investor Elliott Investment Management has taken a more than $5 billion stake in Honeywell International and is calling for the conglomerate to split into two separate companies.

Alexander Zverev was imperious in dispatching Frenchman Ugo Humbert 6-2, 6-2 to win the Paris Masters on Sunday.