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In the context of the internet of things, and particularly within distributed measurement systems that are subject to high privacy risks, it is essential to emphasize the need for increasingly effective privacy protections. The idea presented in this work involves managing critical traffic through an architectural proposal aimed at solving the problem of communications between nodes by optimizing both the confidentiality to be guaranteed to the payload and the transmission speed. Specifically, data such as a typical sensor on/off signal could be sent via a standard encrypted channel, while a sensitive aggregate could be transmitted through a dedicated private channel. Additionally, this work emphasizes the critical importance of optimizing message sizes to 5 k-bytes (small payload messages) for transmission over the reserve channel, enhancing both privacy and system responsiveness, a mandatory requirement in distributed measurement systems. By focusing on small, encrypted payloads, the study facilitates secure, timely updates and summaries of network conditions, maintaining the integrity and privacy of communications in even the most challenging and privacy-sensitive environments. This study provides a comprehensive performance analysis of IoT networks using Dark Net technologies and MQTT protocols, with a focus on privacy and anonymity. It highlights the trade-offs between enhanced security and performance, noting increased latency, reduced bandwidth, and network instability when using TOR, particularly with cipher suites like AES256-GCM-SHA384 and DHE-RSA-CHACHA20-POLY1305. The research emphasizes the need for further exploration of alternative protocols like LWM2M in secure IoT environments and calls for optimization to balance privacy with performance in Dark-Net-based IoT deployments. [ABSTRACT FROM AUTHOR]

Introduction: Plastics carried in the outflow of major rivers can be made available and subsequently ingested by marine fishes, causing lethal and sublethal effects. Highly abundant, vertically migrating myctophids play a crucial role in facilitating nutrient cycling between the epi- and mesopelagic zones. However, this diel movement may also make myctophids significant conduits for transporting ingested microparticles from surface waters to deeper food webs. Methods: We examined the gastrointestinal tracts of 340 myctophids caught at varying distances from the Columbia River mouth in the epipelagic zone of the northeast Pacific Ocean to determine if proximity to a presumed point source influences microparticle ingestion. Results: While we found no direct spatial connection with ingestion frequency, we discovered that (a) ~34% of myctophids had either synthetic or other anthropogenic particles retained in their GI tract, (b) microparticle ingestion was higher in an active-feeding species of myctophid (Tarletonbeania crenularis) than an inactive-feeding species (Stenobrachius leucopsarus), and (c) species and standard length were the most influential predictors of microparticle consumption in our best fit model. Discussion: Our failure to detect a significant relationship between distance from a source and ingestion by myctophids is likely due to the particles undergoing fluctuations in dispersal patterns once they enter the ocean, particularly for microfibers which can be transported across large distances. Biological factors like body size may be more relevant to understanding microparticle ingestion patterns in mesopelagic fishes. Overall, our study highlights the potential role myctophids serve as multidirectional transporters of microparticles in Northern California Current food webs, with potential impacts on fisheries and human food systems. [ABSTRACT FROM AUTHOR]

Among adolescents, HIV/AIDs remains a significant cause of death globally [1–4]. Given the unique stages in human development, adolescents have been shown to fall within a sexually active phase. Combined with other social and structural factors in their immediate environments, HIV prevention and care among adolescents can be filled with challenges for intervention. This paper outlines this protocol to systematically review peer-reviewed literature in prevention and care among adolescents 10–19 years. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) will be used to report this scoping review. The review will involve screening and extracting data using covidence as the primary tool. The review will encompass quantitative, qualitative, and mixed methods studies, utilizing a search strategy from electronic databases such as PubMed (NCBI), Web of Science Core Collection (Clarivate), Embase (Elsevier), and Scopus (Elsevier). Additionally, a search will be conducted for grey literature using Global Index Medicus (WHO), MedNar (Deep Web Technologies), and Central Register of Controlled Trials (Cochrane). Duplicate removal and selection of articles that meet the inclusion criteria for the study will be performed using Covidence. Once the screening process is complete, data will be extracted from the full-text screened articles in Covidence. We will pilot the extracted data in Covidence to ensure that all relevant information has been captured, making necessary changes if required. Data extraction will be carried out by at least two authors, with any conflicts resolved by the same authors. If a conflict cannot be resolved between the two, a third author will make a final determination. We aim to analyze data thematically by employing a grounded theory approach to generate codes pertinent to the research question. The team will review and discuss codes to create a cohesive set of codes that will be instrumental in identifying knowledge gaps and constructing themes that summarize the data. The proposed systematic review will be among the pioneering efforts to rigorously assess global data on HIV prevention and care, with a specific focus on adolescents 10–19 years. It will consider the diverse socio-economic factors and experiences shaping these adolescents' lives in HIV prevention and care. We expect this review to yield critical insights into the present landscape of HIV prevention and care for individuals aged 10–19. These findings will also play a pivotal role in shaping the development of a global framework that researchers and stakeholders can readily adopt and implement across socio-economic contexts. This framework will aim to address the unique needs of all adolescents concerning HIV prevention and care. [ABSTRACT FROM AUTHOR]

The Dark Web is a subset of the Deep Web, requiring special browsers, the Dark Net refers to encrypted networks, the Deep Web encompasses non-indexed online content, and darknet includes unused IP address networks. The Dark Net has become a hotbed of cybercrime, with individuals and groups using the anonymity and encryption provided by the network to carry out a range of criminal activities. One of the most concerning trends in recent years has been the weaponization of cybercrimes, as criminals use their technical skills to create tools and techniques that can be used to launch attacks against individuals, businesses, and governments. This paper examines the weaponization of cybercrimes on the Dark Net, focusing on the question of detection and application. This paper uses a Systematic Literature Review (SLR) method to appraise the Dark Web, examine the crimes and their consequences and identify future measures to reduce crime threats. Data from 88 relevant articles from 2011 to 2023 were extracted and synthesized, along with the latest data from 2024 to answer research questions, providing comprehensive knowledge on growing crimes; assessing social, economic, and ethical impacts; and analyzing established techniques and methods to locate and apprehend criminals. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the nonlinear structural behavior of concrete deep beams internally reinforced with glass fiber-reinforced polymer (GFRP) reinforcing bars and containing a web opening of various sizes and locations within the shear span. Three-dimensional (3D) numerical simulation models were developed for large-scale GFRP-reinforced concrete deep beams (300 mm × 1200 mm × 5000 mm) with a shear span-to-depth ratio (a/h) of 1.04. Predictions of the numerical models were validated against published experimental data. A parametric study was conducted to examine the effect of varying the opening size and location on the shear response. Results of the numerical analysis indicated that the strength of the deep beam models with an opening in the middle of the shear span decreased with an increase in either the opening width or height. The rate of the strength reduction caused by increasing the opening height was, however, more significant than that produced by increasing the opening width. Placing a web opening in the compression zone close to the load plate was very detrimental to the beam strength. Conversely, a negligible strength reduction was recorded when the web opening was placed in the tension side above the flexural reinforcement and away from the natural load path. Data of the parametric study were utilized to introduce simplified analytical formulas capable of predicting the shear capacity of GFRP-reinforced concrete deep beams with a web opening in the shear span. [ABSTRACT FROM AUTHOR]

The symbiotic relationship between the human digestive system and its intricate microbiota is a captivating field of study that continues to unfold. Comprising predominantly anaerobic bacteria, this complex microbial ecosystem, teeming with trillions of organisms, plays a crucial role in various physiological processes. Beyond its primary function in breaking down indigestible dietary components, this microbial community significantly influences immune system modulation, central nervous system function, and disease prevention. Despite the strides made in microbiome research, the precise mechanisms underlying how bacterial effector functions impact mammalian and microbiome physiology remain elusive. Unlike the traditional DNA-RNA-protein paradigm, bacteria often communicate through small molecules, underscoring the imperative to identify compounds produced by human-associated bacteria. The gut microbiome emerges as a linchpin in the transformation of natural products, generating metabolites with distinct physiological functions. Unraveling these microbial transformations holds the key to understanding the pharmacological activities and metabolic mechanisms of natural products. Notably, the potential to leverage gut microorganisms for large-scale synthesis of bioactive compounds remains an underexplored frontier with promising implications. This review serves as a synthesis of current knowledge, shedding light on the dynamic interplay between natural products, bacteria, and human health. In doing so, it contributes to our evolving comprehension of microbiome dynamics, opening avenues for innovative applications in medicine and therapeutics. As we delve deeper into this intricate web of interactions, the prospect of harnessing the power of the gut microbiome for transformative medical interventions becomes increasingly tantalizing. [ABSTRACT FROM AUTHOR]

Academic evaluation is a process of assessing and measuring researchers, institutions, or disciplinary fields. Its goal is to evaluate their contributions and impact in the academic community, as well as to determine their reputation and status within specific disciplinary domains. Web of Science (WOS), being the most renowned global academic citation database, provides crucial data for academic evaluation. However, due to factors such as institutional changes, translation discrepancies, transcription errors in databases, and authors' individual writing habits, there exist ambiguities in the institution names recorded in the WOS literature, which in turn affect the scientific evaluation of researchers and institutions. To address the issue of data reliability in academic evaluation, this paper proposes a WOS institution name synonym recognition framework that integrates multi-granular embeddings and multi-contextual information. [ABSTRACT FROM AUTHOR]

The choice of a good join order plays an important role in the query performance of databases. However, determining the best join order is known to be an NP-hard problem with exponential growth with the number of joins. Because of this, nonlearning approaches to join order optimization have a longer optimization and execution time. In comparison, the models of machine learning, once trained, can construct optimized query plans very quickly. Several efforts have applied machine learning to optimize join order for SQL queries outperforming traditional approaches. In this work, we suggest a reinforcement learning technique for join optimization for SPARQL queries, ReJOOSp. SPARQL queries typically contain a much higher number of joins than SQL queries and so are more difficult to optimize. To evaluate ReJOOSp, we further develop a join order optimizer based on ReJOOSp and integrate it into the Semantic Web DBMS Luposdate3000. The evaluation of ReJOOSp shows its capability to significantly enhance query performance by achieving high-quality execution plans for a substantial portion of queries across synthetic and real-world datasets. [ABSTRACT FROM AUTHOR]

How to efficiently find what you want from massive data has become a hot topic. It is precisely because network information is developing so fast that so many data-oriented software systems and pages are used to manage so much network information. Aiming at problems such as insufficient information mining of visual communication websites in ASPNET and poor visual communication effects, a design scheme for integrating high-dimensional data into visual communication websites is proposed. Its working architecture includes high-dimensional data integration, multi-type visual integration, and visual support services. The main functions of the website include comprehensive management, charts, data sources, projects, systems, etc. We have conducted specific design and Implementation of high-dimensional information integration on the website, completed the design and Implementation of integration of high-dimensional data, integration of multiple visualization types, and integrated access to visualization-supported functions. Use a deep web crawler to search the visual site. It uses a search-based approach to filter URLs and crawl valuable web pages. Practice has proved that the intelligent distribution network management page implemented by the solution proposed in this article has good performance. The system shows good performance in visualization implementation and the ability to discover information. The system achieved sound and visual communication effects. [ABSTRACT FROM AUTHOR]

More than tools for managing physical and digital objects, museum collection management systems (CMS) serve as platforms for structuring, integrating, and making accessible the rich data embodied by natural history collections. Here we describe Arctos, a scalable community solution for managing and publishing global biological, geological, and cultural collections data for research and education. Specific goals are to: (1) Describe the core features and implementation of Arctos for a broad audience with respect to the biodiversity informatics principles that enable high quality research; (2) Highlight the unique aspects of Arctos; (3) Illustrate Arctos as a model for supporting and enhancing the Digital Extended Specimen concept; and (4) Emphasize the role of the Arctos community for improving data discovery and enabling cross-disciplinary, integrative studies within a sustainable governance model. In addition to detailing Arctos as both a community of museum professionals and a collection database platform, we discuss how Arctos achieves its richly annotated data by creating a web of knowledge with deep connections between catalog records and derived or associated data. We also highlight the value of Arctos as an educational resource. Finally, we present the financial model of fiscal sponsorship by a nonprofit organization, implemented in 2022, to ensure the long-term success and sustainability of Arctos. [ABSTRACT FROM AUTHOR]

Societal Impact Statement: Madagascar's children are taught that their ancestors destroyed the vast ancient forest, giving rise to modern grasslands, a misleading myth that continues to undermine people's relationship with nature. Replacing this myth with a more nuanced and accurate narrative around grassy ecosystems is fundamental to building a more positive relationship between Madagascar's people and ecosystems, a process that is necessary to build modern conservation practice and environmental governance. The data we present are consistent with a pre‐human grass flora in the region, suggesting the local grassy ecosystems should not be written off as fully anthropogenic and undesirable but are instead in need of recognition and further research attention. Summary: Grassy ecosystems cover over a quarter of dry land, with mosaics of old‐growth and recently formed anthropogenic systems appearing superficially similar to an uninformed observer. Grasses are part of a deep web of historic relationships between grassy ecosystems and local people.We collect and compile the first list of grass species (Poaceae) in north‐west Madagascar in order to make an initial evidence assessment for a pre‐human grass flora. Field surveys and voucher specimen collections were carried out. Specimen identification was performed using morphological character comparison with reference specimens, literature and personal knowledge of grasses from other parts of Madagascar.Seventy species are recorded and assigned to 44 genera. The species list is compared with regional grass checklists from central and south‐central Madagascar. Thirty‐five grasses are unique to Mahajanga, comprising 19% of the multi‐region species pool analysed; the regional species richness is comparable to that of the highlands.The main subfamilies represented are the Panicoideae (64%) and Chloridoideae (29%). Seven species are endemic to Madagascar, reflecting their evolutionary origins on the island. Many of the species are found in multiple types of habitat and substrate, while others are restricted to limited areas and habitats, and local species richness varies significantly with habitat and soil. The main disturbance regimes driving species occurrence include fire and grazing, possibly partly reflecting similar disturbances prior to human arrival. The patterns observed in the grass flora of north‐western Madagascar are overall congruent with a pre‐human grass flora. [ABSTRACT FROM AUTHOR]

The use of malware in criminal investigations might be expanding. While "police hacking" is often publicized as used almost solely against pedophiles on the Dark Web, revelations from Israel on extensive police use of malware for a variety of criminal suspects might suggest that more intrusive forms of police hacking may emerge anywhere. Equipped with a wiretap warrant and malware, Israeli police forces can legally bypass encryption and directly obtain content and metadata from the device and its linked apps, turn on a suspect's camera or microphone, and essentially gain full access to the past and present of suspects. While the scope of police hacking in the U.S. is currently unknown, as this Article further argues, the legal framework that governs "search," access to stored communications and wiretaps could authorize such a practice much like in Israel, although it was never designed to do so. This obsolete framework to properly govern the use of malware by enforcement agencies must be updated and reconfigured. While reflecting on Frank Easterbrook's famous "law of the horse" argument, this Article suggests that trojan horses (malware) must be directly and individually regulated, especially in the realm of criminal law enforcement. This Article explores the history and legality of police hacking under the current legal framework. It then examines the impact of such practice on human rights, human liberties, and other externalities stemming from its use. It moves to propose a blueprint for policymakers on how to regulate police hacking properly, not before placing an almost absolute moratorium on its use until such regulation occurs. Police hacking should be allowed in some circumstances and under a rigorous, semi-technological oversight regime, as this Article suggests, but more importantly, such policymaking is crucial to draw a clear line for when it cannot be used. [ABSTRACT FROM AUTHOR]

The use of the unindexed web, commonly known as the deep web and dark web, to commit or facilitate criminal activity has drastically increased over the past decade. The dark web is a dangerous place where all kinds of criminal activities take place, Despite advances in web forensic techniques, tools, and methodologies, few studies have formally tackled dark and deep web forensics and the technical differences in terms of investigative techniques and artefact identification and extraction. This study proposes a novel and comprehensive protocol to guide and assist digital forensic professionals in investigating crimes committed on or via the deep and dark web. The protocol, named D2WFP, establishes a new sequential approach for performing investigative activities by observing the order of volatility and implementing a systemic approach covering all browsing-related hives and artefacts which ultimately resulted in improving the accuracy and effectiveness. Rigorous quantitative and qualitative research has been conducted by assessing the D2WFP following a scientifically sound and comprehensive process in different scenarios and the obtained results show an apparent increase in the number of artefacts recovered when adopting the D2WFP which outperforms any current industry or opensource browsing forensic tools. The second contribution of the D2WFP is the robust formulation of artefact correlation and cross-validation within the D2WFP which enables digital forensic professionals to better document and structure their analysis of host-based deep and dark web browsing artefacts. [ABSTRACT FROM AUTHOR]

The dark web is considered an expansion of the deep web, intentionally hidden from the surface web. It can only be accessed with a particular group of browsers that allow the user to stay anonymous while navigating the dark web. With the untraceable hidden layer of the Internet and the anonymity of the users associated with the dark web, several impressive cybercrimes have been reported. This paper aims to examine the impact of the dark web on society. The article systematically reviews relevant academic literature and books to understand how the dark web works and its societal effects. The study has found that the dark web is an enabler of several cybercrimes. Moreover, while governments and regulatory authorities have introduced strategic detection techniques on the dark web, cybercriminals are adaptive towards the strategies and, given time, will usually find ways to bypass such detection techniques. It is recommended that the regulatory authorities and cyber threat intelligence periodically review the detection techniques for effective monitoring. Furthermore, security agencies or forensic analysts should ensure that they are updated with the latest scientific knowledge on the safe management of the dark web by undertaking more training in cyber security. There is also a need for further research to focus on awareness campaigns about the dangers of the dark web. [ABSTRACT FROM AUTHOR]

Motivation Studying the genetic makeup of viruses and phages through genome analysis is crucial for comprehending their function in causing diseases, progressing medicine, tracing their evolutionary history, monitoring the environment, and creating innovative biotechnologies. However, accessing the necessary data can be challenging due to a lack of dedicated comparative genomic tools and viral and phage databases, which are often outdated. Moreover, many wet bench experimentalists may not have the computational proficiency required to manipulate large amounts of genomic data. Results We have developed VAPEX (Virus And Phage EXplorer), a web server which is supported by a database and features a user-friendly web interface. This tool enables users to easily perform various genomic analysis queries on all natural viruses and phages that have been fully sequenced and are listed in the NCBI compendium. VAPEX therefore excels in producing visual depictions of fully resolved synteny maps, which is one of its key strengths. VAPEX has the ability to exhibit a vast array of orthologous gene classes simultaneously through the use of symbolic representation. Additionally, VAPEX can fully analyze user-submitted viral and phage genomes, including those that have not yet been annotated. Availability and implementation VAPEX can be accessed from all current web browsers such as Chrome, Firefox, Edge, Safari, and Opera. VAPEX is freely accessible at https://archaea.i2bc.paris-saclay.fr/vapex/. [ABSTRACT FROM AUTHOR]

Due to the massive size of the hidden web, searching, retrieving and mining rich and high-quality data can be a daunting task. Moreover, with the presence of forms, data cannot be accessed easily. Forms are dynamic, heterogeneous and spread over trillions of web pages. Significant efforts have addressed the problem of tapping into the hidden web to integrate and mine rich data. Effective techniques, as well as application in special cases, are required to be explored to achieve an effective harvest rate. One such special area is atmospheric science, where hidden web crawling is least implemented, and crawler is required to crawl through the huge web to narrow down the search to specific data. In this study, an intelligent hidden web crawler for harvesting data in urban domains (IHWC) is implemented to address the relative problems such as classification of domains, prevention of exhaustive searching, and prioritizing the URLs. The crawler also performs well in curating pollution-related data. The crawler targets the relevant web pages and discards the irrelevant by implementing rejection rules. To achieve more accurate results for a focused crawl, ICHW crawls the websites on priority for a given topic. The crawler has fulfilled the dual objective of developing an effective hidden web crawler that can focus on diverse domains and to check its integration in searching pollution data in smart cities. One of the objectives of smart cities is to reduce pollution. Resultant crawled data can be used for finding the reason for pollution. The crawler can help the user to search the level of pollution in a specific area. The harvest rate of the crawler is compared with pioneer existing work. With an increase in the size of a dataset, the presented crawler can add significant value to emission accuracy. Our results are demonstrating the accuracy and harvest rate of the proposed framework, and it efficiently collect hidden web interfaces from large-scale sites and achieve higher rates than other crawlers. [ABSTRACT FROM AUTHOR]

Machine learning and deep learning models are commonly developed using programming languages such as Python, C++, or R and deployed as web apps delivered from a back-end server or as mobile apps installed from an app store. However, recently front-end technologies and JavaScript libraries, such as TensorFlow.js, have been introduced to make machine learning more accessible to researchers and end-users. Using JavaScript, TensorFlow.js can define, train, and run new or existing, pre-trained machine learning models entirely in the browser from the client-side, which improves the user experience through interaction while preserving privacy. Deep learning models deployed on front-end browsers must be small, have fast inference, and ideally be interactive in real-time. Therefore, the emphasis on development and deployment is different. This paper aims to review the development and deployment of these deep-learning web apps to raise awareness of the recent advancements and encourage more researchers to take advantage of this technology for their own work. First, the rationale behind the deployment stack (front-end, JavaScript, and TensorFlow.js) is discussed. Then, the development approach for obtaining deep learning models that are optimized and suitable for front-end deployment is then described. The article also provides current web applications divided into seven categories to show deep learning potential on the front end. These include web apps for deep learning playground, pose detection and gesture tracking, music and art creation, expression detection and facial recognition, video segmentation, image and signal analysis, healthcare diagnosis, recognition, and identification. [ABSTRACT FROM AUTHOR]

The untraceable part of the Deep Web, also known as the Dark Web, is one of the most used "secretive spaces" to execute all sorts of illegal and criminal activities by terrorists, cybercriminals, spies, and offenders. Identifying actions, products, and offenders on the Dark Web is challenging due to its size, intractability, and anonymity. Therefore, it is crucial to intelligently enforce tools and techniques capable of identifying the activities of the Dark Web to assist law enforcement agencies as a support system. Therefore, this study proposes four deep learning architectures (RNN, CNN, LSTM, and Transformer)-based classification models using the pre-trained word embedding representations to identify illicit activities related to cybercrimes on Dark Web forums. We used the Agora dataset derived from the DarkNet market archive, which lists 109 activities by category. The listings in the dataset are vaguely described, and several data points are untagged, which rules out the automatic labeling of category items as target classes. Hence, to overcome this constraint, we applied a meticulously designed human annotation scheme to annotate the data, taking into account all the attributes to infer the context. In this research, we conducted comprehensive evaluations to assess the performance of our proposed approach. Our proposed BERT-based classification model achieved an accuracy score of 96%. Given the unbalancedness of the experimental data, our results indicate the advantage of our tailored data preprocessing strategies and validate our annotation scheme. Thus, in real-world scenarios, our work can be used to analyze Dark Web forums and identify cybercrimes by law enforcement agencies and can pave the path to develop sophisticated systems as per the requirements. [ABSTRACT FROM AUTHOR]

Reconnaissance and monitoring activities of actors on the Internet are becoming indispensable security tools for governments around the world. The Deep Web as part of the Internet protects actors. However, cheap and reliable encryption and online identity protection have become attractive to state and non-state actors in the cyber domain. Unfortunately, part of the Deep Web, the Dark Web is now offering to training terrorists, and trading arms and illicit substances. The Dark Web represents a communication and information systems infrastructure where actors are anonymous and the services are adaptable to the demands of geopolitical circumstances. This paper analyzes the ways of using the Dark Web and its impact on the information environment since the global war on terrorism began, through a period when humanity struggled with Covid-19 pandemic to the war in Ukraine. [ABSTRACT FROM AUTHOR]

The medical-patient relationship is facing pollution of information all over the internet, for physician and patients is becoming tougher to keep updated with the highest quality of information. During the last 20 years multiple evaluation tools have been developed trying to find the best tool to assess high-quality information, to date DISCERN tool represents the most widely spread. Information can be found on the surface internet and in the deep web, constituting the biggest chunk of the internet, informing and controlling the quality of information is a formidable task. PubMed and Google Scholar are the most important tools for a physician to find information, although multiple others are available; awareness must be raised over improving current strategies for data mining high-quality information for the patients and the healthcare community. [ABSTRACT FROM AUTHOR]

Deep learning (DL) and machine learning contribute significantly to basic biology research and drug discovery in the past few decades. Recent advances in DL-based generative models have led to superior developments in de novo drug design. However, data availability, deep data processing, and the lack of user-friendly DL tools and interfaces make it difficult to apply these DL techniques to drug design. We hereby present ReMODE (Receptor-based MOlecular DEsign), a new web server based on DL algorithm for target-specific ligand design, which integrates different functional modules to enable users to develop customizable drug design tasks. As designed, the ReMODE sever can construct the target-specific tasks toward the protein targets selected by users. Meanwhile, the server also provides some extensions: users can optimize the drug-likeness or synthetic accessibility of the generated molecules, and control other physicochemical properties; users can also choose a sub-structure/scaffold as a starting point for fragment-based drug design. The ReMODE server also enables users to optimize the pharmacophore matching and docking conformations of the generated molecules. We believe that the ReMODE server will benefit researchers for drug discovery. ReMODE is publicly available at http://cadd.zju.edu.cn/relation/remode/. [ABSTRACT FROM AUTHOR]

In most cases, openings are made in the Web of deep beams for installations to pass through. These members require to be strengthened since the openings reduce load-bearing capacity. This study utilizes carbon fiber-reinforced polymer (CFRP) composites and steel protective frames (SPF) as strengthening configurations in reinforced concrete (RC) deep beams to improve the strength lost due to the square openings. To this end, eleven specimens with 10 × 50 × 120 cm in size were subjected to the three-point monotonic loading. In each beam, one or two square openings of 18 cm in each side are positioned either symmetrically or asymmetrically along the beam before it is strengthened with CFRP composites or SPFs. The strengthening composites were installed using externally bonded reinforcement (EBR) or externally bonded reinforcement on grooves (EBROG) techniques in two wrapped or inclined configurations. The obtained results indicate that specimens retrofitted by the SPF exhibited a superior performance as their loading capacity and energy absorption were enhanced by 115% and 337% in comparison with the reference beam, respectively, while these values for the specimens retrofitted by the EBROG technique were 58% and 182%, respectively, and 42% and 105% for those strengthened with the EBR technique. [ABSTRACT FROM AUTHOR]

Waste Glass Powder (WGP) could be used as a cement replacement additive to manufacture concrete and solving the problem of environmental pollution. The experimental program was made up of ten simply supported reinforced High-Strength Concrete (HSC) deep beams tested under static loadings. Five beams were with WGP, while the other five beams were without WGP. Eight beams had web openings while two reference beams were without openings. The principal studied parameters were the effect of using WGP, and the location and size of web openings. Using the three-dimensional finite element computer program ABAQUS, a numerical simulation for comparing the shear strength and behavior of tested deep beams has been suggested. The comparison between experimental failure loads of studied beams with that estimated by the Strut-and-Tie model was carried out. Three codes of practice were used to make this comparison: the American Concrete Institute (ACI 318-19), the New Zealand Code (NZS-06), and the Japan Society of Civil Engineering (JSCE-07). The results showed that using WGP in similar deep beams with web openings enhances the cracking shear strength (by about 17–25%) and the ultimate shear strength (by about 12–41%). The improvement in the ultimate failure load could be attributed to the developed concrete microstructures caused by WGP's very fine grains, producing further gel, and decreasing the number of voids in the concrete matrix. The suggested finite element simulation accurately predicts the behavior of HSC deep beams with and without WGP beams and with web openings. [ABSTRACT FROM AUTHOR]

Recently, various decentralized network web services are emerging. However, the decentralized network web service is not well exposed to general users because it is difficult to access it using a general portal search engine. This point is similar to the deep web, and in the case of Tor (The Onion Routing), a kind of deep web. It has been used for various online crimes such as distribution of child pornography and online drug dealing, and its usage is continuously increasing. Therefore, the decentralized network web service is also likely to be abused for crimes, and forensic investigation techniques are needed to respond to the crime of the decentralized network web service. This paper is about artifact analysis to identify traces of users accessing and actioned on ZeroNet, which is one of the decentralized network web services, and the digital forensic method for applying to forensic investigations for decentralized network web services. As a result, the method of acquiring artifacts for meaningful user access trace analysis and the storage structure of access record trace data were analyzed for a total of five platforms including Windows and macOS. As a result of analyzing the acquired data, it was able to identify users who distributed decentralized network web services through the illegal decentralized network web service address accessed by the user, a list of files downloaded to access the decentralized network web service and BitTorrent. In addition, it constructed a hypothetical scenario and presented a plan to use it from the perspective of forensic investigation. Through this thesis, when ZeroNet, a kind of decentralized network web service, is found on the user's PC during a forensic investigation, it contributes to the development of forensic investigation techniques by presenting a method to obtain a list of decentralized network web service addresses, downloaded files, and users sharing files. [ABSTRACT FROM AUTHOR]

The World Wide Web comprises of huge web databases where the data are searched using web query interface. Generally, the World Wide Web maintains a set of databases to store several data records. The distinct data records are extracted by the web query interface as per the user requests. The information maintained in the web database is hidden and retrieves deep web content even in dynamic script pages. In recent days, a web page offers a huge amount of structured data and is in need of various web-related latest applications. The challenge lies in extracting complicated structured data from deep web pages. Deep web contents are generally accessed by the web queries, but extracting the structured data from the web database is a complex problem. Moreover, making use of such retrieved information in combined structures needs significant efforts. No further techniques are established to address the complexity in data extraction of deep web data from various web pages. Despite the fact that several ways for deep web data extraction are offered, very few research address template-related issues at the page level. For effective web data extraction with a large number of online pages, a unique representation of page generation using tree-based pattern matches (TBPM) is proposed. The performance of the proposed technique TBPM is compared to that of existing techniques in terms of relativity, precision, recall, and time consumption. The performance metrics such as high relativity is about 17-26% are achieved when compared to FiVaTech approach. [ABSTRACT FROM AUTHOR]

The World Wide Web (www. consists of the surface web, deep web, and Dark Web, depending on the content shared and the access to these network layers. Dark Web consists of the Dark Net overlay of networks that can be accessed through specific software and authorization schema. Dark Net has become a growing community where users focus on keeping their identities, personal information, and locations secret due to the diverse population base and well-known cyber threats. Furthermore, not much is known of Dark Net from the user perspective, where often there is a misunderstanding of the usage strategies. To understand this further, we conducted a systematic analysis of research relating to Dark Net privacy and security on N = 200 academic papers, where we also explored the user side. An evaluation of secure end-user experience on the Dark Net establishes the motives of account initialization in overlaid networks such as Tor. This work delves into the evolution of Dark Net intelligence for improved cybercrime strategies across jurisdictions. The evaluation of the developing network infrastructure of the Dark Net raises meaningful questions on how to resolve the issue of increasing criminal activity on the Dark Web. We further examine the security features afforded to users, motives, and anonymity revocation. We also evaluate more closely nine user-study-focused papers revealing the importance of conducting more research in this area. Our detailed systematic review of Dark Net security clearly shows the apparent research gaps, especially in the user-focused studies emphasized in the paper. [ABSTRACT FROM AUTHOR]

Due to the fact that library catalogs are often hidden in the invisible web, the purpose of the present research has been increasing visibility and findability of bibliographic records of Online Public Access Catalog’s (OPAC) of the NLAI. Also, SEO components (i.e. visibility, ranking and click-through rate) were measured in Google before and after using the Google Search Console. The research method is action research. Bibliographic records of NLAI Sitemaps were submitted to Google Search Console. Lewin’s three steps (planning, execution and evaluation) were used to design the research steps. Less than four months from submission, a fivefold increase (from 17948 to 90330) in indexing records was observed. During this period, 4% of URL sitemaps submitted to Google Search Console were indexed. This number is increasing daily. From the perspective of other SEO components (ranking and click-through rate), the ranking decreased from 7.8 to 8.6. Also the click-through rate decreased from 12.5% to 11.1%. The highest click-through rate was for desktop with 19.3%. Click-through rate is calculated by dividing number of clicks by the number of impressions. As the number of impression of OPAC in Search Engine Results Pages increased due to the indexing of records, the number of clicks must also increase in order to achieve a high clickthrough rate. The click-through rate increases the OPAC’s NLAI ranking from eighth to first third. By improving the infrastructure and addressing the problems with tags and metatags, ranking could increase. Doubling the click-through rate on desktop compared to mobile phone is also a warning to the National Library of Iran to fundamental changes in its OPAC architecture. This structure was designed fifteen years ago and needs to be redesigned. Nowadays, to be mobile friendly is a highly important characteristic in Google rankings. The NLAI, like other OPACs in the world, needs strategic and continuous planning for high visibility and ranking on the web. [ABSTRACT FROM AUTHOR]

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From proactive detection of cyberattacks to the identification of key actors, analyzing contents of the Dark Web plays a significant role in deterring cybercrimes and understanding criminal minds. Researching in the Dark Web proved to be an essential step in fighting cybercrime, whether with a standalone investigation of the Dark Web solely or an integrated one that includes contents from the Surface Web and the Deep Web. In this review, we probe recent studies in the field of analyzing Dark Web content for Cyber Threat Intelligence (CTI), introducing a comprehensive analysis of their techniques, methods, tools, approaches, and results, and discussing their possible limitations. In this review, we demonstrate the significance of studying the contents of different platforms on the Dark Web, leading new researchers through state-of-the-art methodologies. Furthermore, we discuss the technical challenges, ethical considerations, and future directions in the domain. [ABSTRACT FROM AUTHOR]

Total digitalization of culture requires the extensive integration of Web 2.0 services and capabilities into music education. The penetration of digital technologies is not reduced to the technologies for fixing and distributing musical works or the means of their broadcasting but also dramatically transforms the process of creating musical works. Web 2.0 offers a new distributed creativity culture and provides musicians with specific opportunities to work and distribute creative products. The study is devoted to the integration of music education and the services and opportunities that Web 2.0 provides to the mass audience (free specialized and non-specialized services), its impact on the quality of music education, as well as on the most important psychological parameters of students of music universities. The study involved 150 students of R. Glier Kyiv Municipal Academy of Music (Kyiv, Ukraine); there were three groups of 50 participants: two experimental groups and a control one. In Experimental Group 1, training was partially integrated with Web 2.0 services; in Experimental Group 2, there was a more complete and structured integration. Based on the results of semester training and the objective test scores, a significant increase in the results of experimental groups was observed (an increase by 1.3 points in Group 1 and 2.84 points in Group 2 on a 5-point scale); Group 2 demonstrated a more significant improvement. The subjective assessment of the level of involvement, motivation and anxiety showed a statistically significant decrease in academic anxiety in the experimental groups (2.99 and 2.01 compared to 3.98 in the control group, respectively) and a statistically significant increase in motivation and involvement in the group with deep integration of Web 2.0 services (Experimental Group 2). The hypothesis of the study that deep integration of Web 2.0 services and capabilities into music education will increase objective academic results, motivation and student involvement has been fully confirmed. It has also been revealed that it helps students reduce academic anxiety. The research results can be used as a basis for further research and in the course of the development of music education curricula based on online learning, mobile learning and the integration of music learning into a digital environment. [ABSTRACT FROM AUTHOR]

The unrivaled growth in e‐commerce of animals and plants presents an unprecedented opportunity to monitor wildlife trade to inform conservation, biosecurity, and law enforcement. Using the internet to quantify the scale of the wildlife trade (volume and frequency) is a relatively recent and rapidly developing approach that lacks an accessible framework for locating relevant websites and collecting data. We produced an accessible guide for internet‐based wildlife trade surveillance. We detailed a repeatable method involving a systematic internet search, with search engines, to locate relevant websites and content. For data collection, we highlight web‐scraping technology as an efficient way to collect data in an automated fashion at regularly timed intervals. Our guide is applicable to the multitude of trade‐based contexts because researchers can tailor search keywords for specific taxa or derived products and locations of interest. We provide information for working with the diversity of websites used in wildlife trade. For example, to locate relevant content on social media (e.g., posts or groups), each social media platform should be examined individually via the site's internal search engine. A key advantage of using the internet to study wildlife trade is the relative ease of access to an increasing amount of trade‐related data. However, not all wildlife trade occurs online and it may occur on unobservable sections of the internet. Article Impact Statement: The internet is a vast source of wildlife trade data; our generalizable framework allows researchers to explore new contexts of the trade. [ABSTRACT FROM AUTHOR]

This article describes STEM education with artificial intelligence (AI) learning, particularly for non-engineering undergraduate students. In the designed three-week learning activities, students were encouraged to put their ideas about AI into practice through two hands-on activities, utilizing a provided deep learning-based web service. This study designed pre-test and post-test surveys to investigate the performance of students in different aspects of AI. With 328 students involved in these learning activities, we discovered from the surveys that the proposed learning method can effectively improve AI literacy among non-engineering students. This study also found that students' AI literacy correlated significantly with their awareness of AI ethical issues and that the STEM-based AI curriculum increased the awareness of AI ethical issues among low-AI-literate learners. This article discusses the association between learning activities and different aspects of AI learning. The proposed method can be used by teachers who want to introduce AI knowledge into general education courses. [ABSTRACT FROM AUTHOR]

We argue that that the use of the Carnap - Bar-Hillel principle of indexed expressions provides a suitable cognitive model to undergo the spread of information processes in the Semantic Net. To understand the stratification of the net into the surface Web and the hidden Web, a model structure is proposed that provides navigation through the net as a whole. For logical expressions, a relativized evaluation map is given, which is parameterized by the indexing system. It is allowed to use concepts that are generated using partial functions, the variables of which run over the range of possible individual information processes. A generalized operator providing virtualization is presented for individuals. The process is accompanied with the dynamic generation of Web-pages, which triggers their indexing. This way they are thereby transferred to the surface layer of the network. A commutative diagram is proposed that establishes a cognitive model of semantic constructions of variable domains, the connection of virtual individuals with actual ones which corresponds to transitions over the stages of knowledge. The knowledge stages are modeled by indexing systems. [ABSTRACT FROM AUTHOR]

Our objective was to examine conflicts of interest between the UK's health-focused All-Party Parliamentary Groups (APPGs) and the pharmaceutical industry between 2012 and 2018. APPGs are informal cross-party groups revolving around a particular topic run by and for Members of the UK's Houses of Commons and Lords. They facilitate engagement between parliamentarians and external organisations, disseminate knowledge, and generate debate through meetings, publications, and events. We identified APPGs focusing on physical or mental health, wellbeing, health care, or treatment and extracted details of their payments from external donors disclosed on the Register for All-Party Parliamentary Groups. We identified all donors which were pharmaceutical companies and pharmaceutical industry-funded patient organisations. We established that sixteen of 146 (11%) health-related APPGs had conflicts of interest indicated by reporting payments from thirty-five pharmaceutical companies worth £1,211,345.81 (16.6% of the £7,283,414.90 received by all health-related APPGs). Two APPGs (Health and Cancer) received more than half of the total value provided by drug companies. Fifty APPGs also had received payments from patient organisations with conflicts of interest, indicated by reporting 304 payments worth £986,054.94 from 57 (of 84) patient organisations which had received £27,883,556.3 from pharmaceutical companies across the same period. In total, drug companies and drug industry-funded patient organisations provided a combined total of £2,197,400.75 (30.2% of all funding received by health-related APPGs) and 468 (of 1,177–39.7%) payments to 58 (of 146–39.7%) health-related APPGs, with the APPG for Cancer receiving the most funding. In conclusion, we found evidence of conflicts of interests through APPGs receiving substantial income from pharmaceutical companies. Policy influence exerted by the pharmaceutical industry needs to be examined holistically, with an emphasis on relationships between actors potentially playing part in its lobbying campaigns. We also suggest ways of improving transparency of payment reporting by APPGs and pharmaceutical companies. [ABSTRACT FROM AUTHOR]

Evidence-based STI (science, technology, and innovation) policy making requires accurate indicators of innovation in order to promote economic growth. However, traditional indicators from patents and questionnaire-based surveys often lack coverage, granularity as well as timeliness and may involve high data collection costs, especially when conducted at a large scale. Consequently, they struggle to provide policy makers and scientists with the full picture of the current state of the innovation system. In this paper, we propose a first approach on generating web-based innovation indicators which may have the potential to overcome some of the shortcomings of traditional indicators. Specifically, we develop a method to identify product innovator firms at a large scale and very low costs. We use traditional firm-level indicators from a questionnaire-based innovation survey (German Community Innovation Survey) to train an artificial neural network classification model on labelled (product innovator/no product innovator) web texts of surveyed firms. Subsequently, we apply this classification model to the web texts of hundreds of thousands of firms in Germany to predict whether they are product innovators or not. We then compare these predictions to firm-level patent statistics, survey extrapolation benchmark data, and regional innovation indicators. The results show that our approach produces reliable predictions and has the potential to be a valuable and highly cost-efficient addition to the existing set of innovation indicators, especially due to its coverage and regional granularity. [ABSTRACT FROM AUTHOR]

This essay looks at the use of vernacular web culture by the new right. Specifically it focuses on how, in recent years, the new right appropriated a genre of web aesthetics known as 'vapourwave' to create the sub-genre of 'fashwave'. Like vapourwave before it, fashwave taps into web cultural imaginary that is nostalgic for an imagined 'cyberpunk' past future -- but while the former has been the subject of a monograph (Tanner 2016), very little has yet been written on the latter. Largely ignored within mainstream popular culture, these '--wave' aesthetics flourish on the 'deep vernacular web' (de Zeeuw & Tuters 2019) of imageboards and web fora. As trivial as many fashwave memes may appear, this paper argues that they can be understood as the aesthetic manifestations of a contemporary renaissance in esoteric "traditionalism" -- a discourse that posits an alternative theory of western culture, and which was influential on 20th century ideologues. The essay argues that fashwave transposes traditionalism's fantasy of imagined past glories into an imagined future -- one that is informed by the vapourwave's distinctly vernacular nostalgia for masculine cyberpunk aesthetics. [ABSTRACT FROM AUTHOR]

Recently, online black markets and anonymous virtual currencies have become the subject of academic research, and we have gained a certain degree of knowledge about the dark web. However, as terms such as deep web and dark net, which have different meanings, have been used in similar contexts, discussions related to the dark web tend to be confusing. Therefore, in this paper, we discuss the differences between these concepts in an easy-to-understand manner, including their historical circumstances, and explain the technology known as onion routing used on the dark web. [ABSTRACT FROM AUTHOR]

The use of ultrasonic tools in paper forming results in highly dynamic mechanical alternating stress, which causes a changed material load. This work aimed to determine the influence of the ultrasonic process parameters of amplitude, ultrasonic time, and static contact pressure and to characterize the material compression during the ultrasonic-assisted forming of paperboard. To achieve this, a method was developed to determine the static, dynamic, and irreversible material compression during the gap-controlled forming of paper. The results showed that the ultrasonic amplitude, the gap pressure, and their second-order interactions had an important influence on the irreversible material compression. With the new method, the irreversible material compression could be increased up to 480% compared to the equivalent static load case. [ABSTRACT FROM AUTHOR]

In this paper, we consider the problem of full schema induction from either multiple list pages or singleton pages with the same template. Existing approaches do not work well for this problem because they use fixed abstraction schemes that are suitable for data-rich detection, but they are not appropriate for small records and complex data found in other sections. We propose an unsupervised full schema web data extraction via Divide-and-Conquer Alignment with Dynamic Encoding (DCADE for short). We define the Content Equivalence Class (CEC) and Typeset Equivalence Class (TEC) based on leaf node content. We then combine HTML attributes (i.e., id and class) in the paths for various levels of encoding, so that the proposed algorithm can align leaf nodes by exploring patterns at various levels from specific to general. We conducted experiments on 49 real-world websites used in TEX and ExAlg. The proposed DCADE achieved a 0.962 F1 measure for non-recordset data extraction (denoted by FD), and a 0.936 F1 measure for recordset data extraction (denoted by FS), which outperformed other page-level web data extraction methods, i.e., DCA (FD= 0.660), TEX (FD= 0.454 and FS= 0.549), RoadRunner (FD= 0.396 and FS= 0.330), and UWIDE (FD= 0.260 and FS= 0.081). [ABSTRACT FROM AUTHOR]

The Deep Web and Dark Web are legitimate tools for use in the field of information science, adding to the discussion of patron privacy. The American Library Association policies on privacy and confidentiality combined with the advancement of internet technology necessitate that library professionals become fluent in Dark Web usability in libraries. [ABSTRACT FROM AUTHOR]

Present-day television, Internet, and radio advertisements portray the deep and dark web as an underground place where nefarious and frightening activities occur. A place where drug lords reign and credit card information flows like mighty rivers. Research finds that the general population in the United States tends to understand very little about what the deep web and dark web actually are and that most people access the dark web in some form almost daily. The purpose of this exploratory study is to examine the existing literature to understand more of what information is currently published related to the public's knowledge of the dark web as a base for a future publication. From this research, the authors propose two training scenarios: one for university students and another for law enforcement. The results of future studies on this topic will serve to fortify both of those courses. [ABSTRACT FROM AUTHOR]

• A tailor-made steel reinforcing method was found effective in shear strength improvement. • Fibre adoption enhanced crack-opening resistance, ultimate shear strength and shear deformation. • It is essential to provide sufficient web reinforcement above and below web openings. • The simplified analytical model yielded safe predictions. Application of fibre-reinforced concrete or novel web reinforcement detailing could be an effective way to enhance structural behaviour of continuous deep beams with web openings. However, there are very few experimental works studying the synergistic effects of these two methods. Therefore, an experimental programme is introduced in this paper to study synergistic effects of shear reinforcement and hybrid fibres on shear strength of nine double-span deep beams with unsymmetrical web openings (denoted as pierced span). The test specimens were designed to consist of a pierced beam span with a web opening and an adjacent solid beam span. The spans with openings were designed with different shear reinforcement configurations. It was experimentally shown that provision of sufficient web steels above and below web openings has the most important and beneficial effect on ultimate shear strength of the pierced spans. Besides, a tailored steel reinforcing method was also proposed that is capable of improving strut capacity near the web opening. In addition, adoption of hybrid fibre reinforcement led to enhanced crack-opening resistance, ultimate shear strength and shear deformation. Based on the research outcomes, it was recommended to adopt the proposed detailing method or fibre reinforcement dosage for shear strength enhancement of continuous deep beams with web openings. Furthermore, an analytical model was adopted to the shear strength of continuous deep beams accounting for web openings, steel stirrups, and hybrid fibres, which yielded safe predictions. [ABSTRACT FROM AUTHOR]