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Beyond PKI: a DNSSEC delegation approach for scalable dynamic credential management in IoT
Get PDFInternet of Things (IoT) systems that manage data
across cloud, fog, and edge environments—and the devices that
consume those services—face substantial challenges in confidentiality, privacy, and authentication. However, traditional Public
Key Infrastructure (PKI) is too rigid and costly for massive,
ephemeral IoT deployments. Moreover, device authentication is
often overlooked in favor of service authentication, neglecting
the security of the entire ecosystem. DNSSEC combined with
DANE introduces a new paradigm in which service authentication
can be managed globally, extending trust to locally generated,
type-agnostic credentials. This framework can accommodate
PKI certificates, self-signed credentials, and local keys, all of
which can be verified by any client, local or remote. However,
DNSSEC’s signature proofs grow linearly with the number of
secured records, inflating communication overhead and energy
consumption—an issue aggravated by the larger sizes of postquantum signatures. Additionally, current DNSSEC delegation
mechanisms lack the flexibility needed for secure load balancing and isolation. In this article, we present a collision-based
DNSSEC signature-delegation mechanism designed to overcome
these scalability limitations. By allowing a central DNS authority
to delegate signing responsibilities to local DNS servers, our
approach reduces certificate-management overhead and enables
a dynamic, hierarchical trust model. It supports both service
and device authentication in a unified DNS-name-based security
context. Our evaluation shows that the proposed mechanism
maintains a stable computational cost irrespective of credential
count, a critical benefit for large-scale, resource-constrained
IoT deployments. By leveraging existing DNS infrastructure
and standards, this solution enhances scalability and efficiency
compared to traditional PKI and DNSSEC, while promoting
interoperability and ease of deployment. It also opens the
adoption of future post quantum trapdoor systems still under
research and development
Structural basis of novel bile acid-based modulators of FXR
Get PDFFollowing its deorphanisation in the early 2000s, the farnesoid X receptor (FXR) attracted significant attention for regulating genes involved in bile acid, lipid and glucose metabolism and inflammation, pathways central to many liver diseases. As such, pharmaceutical efforts targeted FXR for their treatment. However, while FXR agonists, such as obeticholic acid, have been studied in clinical trials, many were associated with adverse effects arising from the promiscuity of systemic FXR activation, thus efforts to limit or selectively modulate the downstream effects of FXR are crucially important. In work here, two novel bile acid derivatives, previously identified via molecular docking and cell-based screening, were validated by X-ray crystallography and tested in LanthaScreen coactivator recruitment assays. Their effects on downstream FXR signalling were assessed in vitro in hepatocellular carcinoma cells, and in vivo in C57BL/6 mice, by RNA sequencing and RT-qPCR. The novel compounds exhibited potent and selective FXR agonist activity. Co-crystal structures of FXR LBD with both compounds, demonstrated distinctive binding modes for each, including occupancy of a receptor sub-pocket associated with allosteric activation, not observed with classic bile acids. Both compounds were up to four-fold more potent than obeticholic acid and demonstrated ligand-dependent differences in coactivator recruitment assays. In vitro, both compounds induced greater changes in the expression of FXR target genes, at lower doses than obeticholic acid. In vivo, compound-dependent differential gene expression was observed. These findings suggest that the novel compounds may enable gene-specific FXR regulation through differential coactivator usage and hold potential to overcome the shortcomings of current bile acid drugs, thus representing promising candidates for further research
The development of learners’ listening comprehension, self-efficacy, and anxiety within an informal digital learning of English listening (IDLEL) context: Examining the role of IDLEL engagement and self-regulation
Get PDFListening is a crucial language skill for L2 learners, as it is not only one of the most
frequently used skills but also plays a vital role in the development of other language skills. However, beyond these benefits, English listening proficiency can also be crucial for Chinese
university EFL learners’ academic success, career prospects, and global mobility. For
instance, it can impact learners’ exam performance, is essential for meeting job market
demands in an increasingly globalised economy, and is a key requirement for studying abroad, where strong listening skills are vital for both academic and daily life. However, Chinese EFL university learners often face numerous challenges in developing
their listening proficiency in formal classroom settings, such as limited instructional time, insufficient teaching resources, a lack of diverse teaching methods, and an exam-oriented
curriculum. These factors may hinder adequate listening development, leading many learners
to experience moderate to high levels of listening anxiety and low self-efficacy. One effective
solution is for students to actively engage in informal L2 listening practice outside the
classroom. With technological advancements, informal digital learning of English (IDLE) has
provided learners with greater access to resources and opportunities. While IDLE has gained
increasing research attention, little is known about Chinese EFL university learners’ L2
listening development within informal learning contexts. Moreover, unlike traditional teacher-centered language classrooms, where external
regulation is dominant, informal language learning contexts can provide learners with greater
autonomy and freedom. In the absence of external regulation, however, learners’ self-regulated learning (SRL) abilities become particularly crucial. While numerous models
have been developed to illustrate the mechanisms of SRL, models specifically constructed for
L2 listening remain absent. Furthermore, considering the significant impact of motivational
and affective factors on listening, regulation of motivation and affect should be incorporated
into SRL frameworks. However, few existing models simultaneously address both cognitive
(i.e., listening) and motivational/affective regulation. Additionally, SRL, self-efficacy, and
listening anxiety have a complex relationship; however, their joint predictive mechanism for
listening remains unclear. Therefore, addressing the research gaps above serves as the
primary aim of this study. This study employed a mixed-method research design. Based on an analysis of the
strengths and limitations of existing SRL models, the study proposed a five-phase, dual-level
SRL model targeted L2 listening, referred to as the Self-Regulated L2 Listening Model. To
validate the hypothesised structure of the model, a questionnaire was developed based on this
theoretical framework, namely the Self-Regulated L2 Listening Questionnaire (SRLLQ). A
total of 582 EFL learners from five universities in China were invited to complete the SRLLQ, and 523 valid responses were analysed using Confirmatory Factor Analysis (CFA), which
confirmed the five-phase, dual-level structure of the Self-Regulated L2 Listening Model. Additionally, the study proposed two hypothesised joint predictive mechanisms of SRL, self-efficacy, and listening anxiety on L2 listening. To test these mechanisms and explore
learners’ L2 listening development in an informal digital learning of English listening
(IDLEL) context, another 130 English majors from two of the five universities participated in
the IDLEL study. They completed three listening tests (pre, post, and delayed post-test) and
two questionnaires (pre, and post-test) measuring their self-regulation, self-efficacy, and
listening anxiety. Additionally, they participated in a four-week observational IDLEL study, during which they recorded their IDLEL engagement in their weekly E-logs. The Structural Equation Modeling (SEM) results confirmed the two hypothesised
predictive mechanisms: the first mechanism revealed the direct predictive effect of
self-efficacy on listening, as well as its indirect effect through SRL and listening anxiety; the
second mechanism focused on the direct predictive effect of SRL on listening and its indirect
effect, with self-efficacy and listening anxiety being the mediators. Together, these two
mechanisms illustrate a positive cycle that facilitates L2 learners’ listening development. Additionally, the multiple predictive pathways of SRL suggest that its influence on listening
is not only immediate but also potentially long-term. Moreover, descriptive analysis, thematic analysis, and cluster analysis of participants’
IDLEL E-logs provided insights into the quantity (i.e., frequency and duration of engagement)
and quality (i.e., diversity of activities engaged and SRL strategy use) of their IDLEL
engagement. Linear Mixed Models (LMMs) were then constructed to reveal the predictive
effects of SRL and IDLEL engagement on listening, self-efficacy, and listening anxiety. The
results showed that participants’ SRL (post-test) and the duration of their IDLEL activity
engagement significantly and positively predicted their listening improvement from pre-test
to post-test, but they were not found to have a significant predictive effect on the listening
post-test. Additionally, participants’ SRL (post-test) and the duration of their IDLEL
engagement significantly and positively predicted their listening self-efficacy at both the
pre-test and post-test, while the frequency of IDLEL engagement had a significant negative
predictive effect on their listening self-efficacy at both time points. Furthermore, participants’
SRL (post-test) was found to significantly negatively predict their listening anxiety at both
time points. Finally, the moderation analysis showed that SRL did not moderate the
relationship between IDLEL engagement and listening and self-efficacy, indicating that
IDLEL engagement may be universally beneficial to learners, regardless of their SRL
abilities
Legal cynicism in Men’s Rights discourses: using corpus linguistics to investigate how distrust in the legal system excuses and perpetuates sexual violence against women
Get PDFThe term legal cynicism refers to a type of legal disengagement which is associated with a lack of internal commitment to follow legal rules and a failure to acknowledge legal authority, typically stemming from perceived ongoing injustices and rights deprivations. This perception of the criminal justice system enables individuals in extremist communities to rationalise criminal actions, leading to an increased propensity for violent behaviour. Effectively identifying content such as this within online discourses has been argued to be the initial step in mitigating this propensity for violence and corpus linguistic methods, employed as entry points into these discourses, offer effective tools to do such analysis.
Using a 122,000-word corpus of online discourses produced by Men’s Right’s Activists (MRAs) on blogs and the subreddit r/MensRights, quantitative and qualitative approaches are used in this corpus-assisted discourse analysis to determine how legal cynicism is indexed and generated. The ways in which the criminal justice systems in both the United States and United Kingdom are contextualised and reframed to embed legal cynicism in MRA discourses, and the evidential and legal processes highlighted as problematic by MRAs, are explored. The paper discusses the impact of this reframing of the criminal justice system on the potential for violence through conspiracy theories and legal disengagement. It concludes with suggestions for addressing legal cynicism through prebunking and educational strategies designed to challenge misconceptions of criminal justice processes
Navigating image space
Get PDFNavigation means getting from here to there. Unfortunately, for biological navigation, there is no agreed definition of what we might mean by ‘here’ or ‘there’. Computer vision (‘Simultaneous Localisation and Mapping’, SLAM) uses a 3D world-based coordinate frame but that is a poor model for biological spatial representation. Another possibility is to use an image-based rather than a map-based representation. The image-based strategy is made simpler if the observer maintains fixation on a stationary point in the scene as they move. This strategy would require a system for relating different fixation points to one another as the observer moves through the environment. I describe how this can be done by, first, relating fixations to an egocentric representation of visual direction and, second, encoding egocentric representations in a coarse-to-fine hierarchy. The coarsest level of this hierarchy is, in some sense, a world-based frame as it does not vary with eye rotation or observer translation. This representation could be implemented as a ‘policy’, a term used in reinforcement learning to describe a set of states and associated actions, or a ‘graph’ that describes how images or sensory states can be connected by actions. I discuss some of the psychophysical evidence relating to these differing hypotheses about spatial representation and navigation. I argue that this evidence supports image-based rather than map-based representation
Tropical cyclones and associated environmental fields in CMIP6 models
No full textThe authors analyze the environmental fields associated with tropical cyclone (TC)
activity in the Coupled Model Intercomparison Project Phase 6 (CMIP6) models, as well as the
TC-like storms in those models. First, the model biases in the historical climatological means
of chosen environmental fields are evaluated against the fifth generation of the European Centre
for Medium-Range Weather Forecasting (ECMWF) atmospheric reanalysis (ERA5). Second, we
show that the interannual variability of these fields is typically much smaller in models than in
reanalysis. Applying a mean bias correction to these fields before calculating tropical cyclone
genesis indices improves the variability of the modeled indices compared to those in reanalysis,
as well as the means, due to the nonlinear dependence of the indices on these fields. The authors
consider how these environmental fields change in the CMIP6 models, using three future scenarios
separately as well as combining scenarios and times according to specific greenhouse warming
levels. Multiple proxies for TC activity are considered and we show that the signs of the future
changes are dependent on the choice of genesis index. The relationship between climate sensitivity
and potential intensity change across the multi-model ensemble is examined. The statistics of the
TC-like structures in the historical simulations are also examined, using the number of tropical
cyclones (NTC) and accumulated cyclone energy (ACE) as diagnostics, including calculations of
the percentage changes in NTC and ACE at the end of the 21C as compared with the 20C. Large
decreases in both of these quantities are found in the highest emission scenario
High stakes in the assessment arms race: a mixed-methods analysis of reducing assessment in an undergraduate psychology programme
Get PDFReducing assessment load has been identified as one practical way to allow space within programmes and modules for students to develop deeper learning practices and to increase student satisfaction. Yet despite the obvious benefits, both staff and students report preferring to maintain a high assessment load as a way to ensure student attention (staff), or to manage risk (students). This mixed-methods study looked at the reduction of the number of assessments across final year optional modules in the international branch campus of a UK university psychology programme on module grades and student perceptions. We found that module grades did not increase following reduction. Students reported anxiety about single-assessment module regimes, regardless of their experience of assessment reduction. Students overwhelmingly preferred two assessments per module, interestingly on the grounds of fairness from a diverse assessment portfolio. We suggest that a simple reduction in the number of assessments isn’t itself sufficient to meet the broad aims of slow scholarship, but that programme teams could consider how better as well as fewer assessments and the perceptions of workload might be more important to tackle
BLC and subordination in heritage speakers — towards a new research agenda: commentary on Hulstijn (2024)
Get PDFIn his update on Basic Language Cognition (BLC), Hulstijn formulates a number
of predictions derived from BLC Theory, and explains how BLC differs from Extended
Language Cognition (ELC). BLC is used to refer to an individual’s capacity to process
spoken language productively and receptively in everyday life, while ELC is defined as
control of the written standard language, as taught in school. In the literature on heritage
speakers, so far surprisingly little attention has been paid to the differences between BLC
and ELC, despite the relevance of the distinction between oral and written language for our understanding of heritage speakers’ language profiles. In this commentary, I argue that BLC Theory can be used to inform studies of heritage languages, and conversely,
how insights from heritage languages can be used to develop BLC Theory further. By way of example, I revisit some of the literature on subordination in Turkish as a heritage
language. I also point to issues that need to be clarified and future directions in the study of these phenomena
Development and assessment of capacity planning and energy management approaches of Virtual Power Plants in State-controlled electricity markets: A case study in Egypt
No full textThis research intends to explore the concept of Virtual Power Plants (VPP) on new residential
developments in Egypt, a country facing energy security problems and fast population growth.
VPPs, aggregating conventional, renewable power plants and energy storage systems, has
demonstrated effectiveness in providing more flexible control of solar and wind power, and
improves the energy trading profit of the aggregated plants. VPPs are widely studied in
“deregulated markets” in which power generators and suppliers are freely trading power on hourly
basis. The aggregated energy systems in VPPs could have several configurations of output,
accordingly the plants’ power dispatch is driven by profit maximization every hour given the
hourly varying prices and energy demand. On the other hand, VPPs’ concept has not been
presented in “regulated markets”, referring to energy markets that are largely under state control,
and in which energy prices are dictated. Egypt is still adopting a regulated market but recently
enabled an incentive to purchase power from Independent private power plants (IPPs) at their
dictated price under power purchase agreement (PPA). Based on that framework, this research
presents a novel VPP model for the Egyptian market and explore the economic and technical
insights from that model.
The proposed VPP aggregated rooftop solar PVs, gas-fired CCHP and energy storage units,
covering electricity, cooling and heating demand, and exchanging power with the grid. The hourly
varying power and thermal demand, as well as the existence of energy storage and grid integration,
could lead to several configurations of the output. Therefore, an energy management driven by
profit maximization is deemed necessary to ensure the optimal dispatch decision is taken. The
optimization is solved with GA on hourly resolution for a year (8760-time steps). An alternative
deep deterministic gradient policy (DDPG) model (a machine-learning method) is developed to
program the model to act optimally and respond faster to the varying input data compared to GA.
Eventually, an iterative method is developed to optimize both plants’ sizes and energy
management, driven by investment costs minimization and profit maximization.
The GA optimization yielded a payback period of 15 years in medium density (middle-income)
housing (Case-1) versus 11 years in low density (high income) housing (Case-2), while the DDPG
yielded 13 years and 10 years for medium and high-income housing, respectively. The
simultaneous sizing and energy management yielded a payback period of 10 years and 9 years for
medium and high-income housing, respectively. Energy storage systems, due to the flat pricing
structure of the market, seem not to be providing any significant profit advantage that compensates
for their investment and replacement costs, hence, causing economic infeasibility of the model. In
all scenarios, the VPP model reduces CO2 emissions by 47-57% in Case-1 and 45-55% in Case2, compared to the full grid dependency. The VPP model reduced dependency on the grid by 66-
78% in both case studies, helping to improve energy security. Finally, the sizing and energy
management demonstrated that the scenarios with the maximum solar PVs capacities yielded the
optimal lifecycle profit, highlighting the economic advantage that solar energy may bring to the
market. A one-at-a-time sensitivity analysis is performed to verify the robustness of the model
against electricity prices, fuel costs and energy demand. Eventually, the most influencing factor
is found to be the electricity prices, yielding +/-30% profit variation with +/-20% input variation