WiIID: Wi-Fi based intelligent indoor intrusion detection with tensor decomposition

Wi-Fi sensing has emerged as a promising paradigm for indoor intrusion detection, as it offers a robust and highaccuracy solution without the need for extra hardware deployment. However, existing schemes often compromise the inherent structure of channel state information (CSI) during feature extraction through lossy preprocessing, causing high false alarm rates and poor generalization. As a remedy, we propose a novel tensor-based framework for indoor intrusion detection, which enables reliable perception of fine-grained human activities through structured feature extraction, even in motion-ambiguous scenarios. Our approach integrates tensor-based feature extraction, multi-dimensional feature consolidation, and a modified deep learning (DL) network for accurate intrusion recognition. To validate our framework, we collected a comprehensive throughwall CSI dataset under the IEEE 802.11n standard, encompassing five common human activities in realistic scenarios. Extensive experimental results demonstrate the superior performance of our method compared to existing state-of-the-art schemes

Nanomechanics with electron beam: detection and control of motion

The study of nanomechanics using an electron beam has developed into an area of research, with recent works reporting on Brownian and ballistic motion detection, dynamic backaction,visualisation of sub-nm motion and mass sensing. It is important because the electron beam offers a platform for real-time observations of dynamics exhibited by nano- and microscale objects, with sub-nm scale displacement sensitivity and MHz bandwidth, as well as for controlling and characterising mechanical properties. In this study, I report the following yet unexplored aspects:• I have introduced a new technique for detecting and mapping the periodic motion of nano/microscale objects via cathodoluminescence, with nanometric displacement sensitivity and spatial resolution, and MHz bandwidth implemented in a modified scanning electron microscope. Its capability is demonstrated by detecting and mapping driven motion of nanomechanical cantilevers. The technique offers a noise equivalent displacement amplitude spectral density of 1 nm/√Hz.• I have observed the phenomenon of dependence of the frequency of oscillation of a cantilever on the presence of the electron beam. The repulsion between an electron beam and charge accumulated on a nanomechanical cantilever yields a stiffening that increases its resonance frequency, providing a mechanism for controlling resonators and sensing charge. For a cantilever of microscale length and nanoscale cross-section interacting with an electron beam, I observe a resonance shift on the order of 5% per nanocoulomb. The resonance frequency was expressed as a function of induced charge and electron beam parameters such as position, beam current and acceleration voltage. The model was tested experimentally by varying the current of an electron beam and its distance from the edge of grounded and isolated cantilevers.• Driving oscillations of a nanomechanical beam can lead to a bistable response related to the nonlinearity of the mechanical restoring force. I have observed for the first time that the nonlinear response of a nanowire and the regime of bistability can be controlled by the electron beam impinging on the oscillator. A nanowire that is fixed at both ends and driven to the nonlinear regime of bistable resonant oscillation was switched between its bistable states by changing the distance between a 10 kV, 1.3 nA electron beam and the nanowire. The control mechanism has been explained as a consequence of electronbeam-induced heating, leading to thermal expansion that affects stress in the nanowire, which controls its resonance frequency. Therefore, the electron beam can shift thenanowire's bistable resonance relative to a fixed frequency of driven oscillation, enabling it to switch between the bistable states.In summary this thesis reports on new ways for characterizing motion and controlling dynamics of nano- and microscale systems with electron beams

Advancing V estimation from CPTu for engineering practice: a data-driven approach

Shear wave velocity, V s, is a critical parameter for offshore site characterisation to estimate the small strain shear modulus, which is essential for subsequent geotechnical designs. Direct measurements of V s are often sparse due to time and resource constraints, while indirect estimations of V s based on empirical correlations can exhibit significant errors. This study presents the performance of 125 models with various combinations of standard piezocone tests (CPTu) input features (e.g., depth, z; sleeve friction resistance, f s; corrected cone tip resistance, q t; and pore pressure at the shoulder of the cone, u 2), CPTu and V s data pairing methods, and prediction techniques (support vector regression (SVR), random forest regression (RFR), extreme gradient boosting regression (XGBR), deep neural network (DNN) and multiple linear regression (MLR)). To do this, we compile a seismic piezocone test (SCPTu) database from onshore and offshore sites across the globe (Netherlands, Austria, Germany, Nepal, and Taipei) and consider five different methods for pairing CPTu data (resolution of 0.02 m) and V s data (resolution of 0.5 m and 1 m depending on the dataset). Two cases consider the more conventional downsampling of CPTu data to V s data. The remaining three methods consider augmented V s data to the resolution of CPTu measurements, to fully utilise all the CPTu data. Results indicate that data augmentation enhances predictive performance. Incorporating pore pressure as an input feature also improves model performance, particularly in cemented materials such as chalk. In contrast, the derived features have a negligible influence. The recommended model combines a DNN with four directly measured CPTu parameters (z,f s,q t,and u 2), and uses an augmentation method that assumes constant V s values within each V s interval. This model achieves a mean absolute error (MAE) of 37.3 m/s and a coefficient of determination (R 2) of 0.59.</p

Newly defined clinical obesity versus BMI-defined obesity: differential risks of overall death and adverse events in a population-based cohort

Aims: to compare the prognostic implications of the newly proposed clinical obesity classification against traditional body mass index (BMI)-defined obesity in a population-based cohort.Materials and Methods: using UK Biobank, we compared the impact of newly defined obesity, including clinical obesity (obesity status with obesity-related comorbidities) and pre-clinical obesity (obesity status with preserved organ function), with traditional BMI-defined obesity on death, cardiovascular disease (CVD), chronic kidney disease (CKD), and liver-related events (LREs). To further delineate heterogeneity within the clinical obesity group, we performed stratified analyses based on comorbidity burden (number of comorbidities), severity of adiposity, and presence of diabetes or hypertension.Results: a total of 502 129 participants were enrolled. About 375 585 (74.8%) had non-obesity, 126 544 (25.2%) had BMI-defined obesity (including 93 410 [73.8%] with clinical obesity and 13 875 [11.0%] with pre-clinical obesity). During a median follow-up of 15.8 years, clinical obesity was associated with significantly higher risks of death (HR = 1.097, 95% CI: 1.071–1.125, p &lt; 0.001), LRE (HR = 1.103, 95% CI: 1.040–1.169, p &lt; 0.001), CVD (HR = 1.118, 95% CI: 1.091–1.146, p &lt; 0.001), and CKD (HR = 1.111, 95% CI: 1.081–1.141, p &lt; 0.001) compared to BMI-based obesity. Conversely, pre-clinical obesity showed significantly lower risks across these outcomes. High-risk clinical obesity subgroups with multiple comorbidities or severe adiposity showed particularly increased risks.Conclusion: the clinical obesity classification helps to define a high-risk phenotype with substantially increased risks of mortality and major comorbidities, while pre-clinical obesity defines a distinct subgroup with more favourable outcomes

Testing methods of initiating inter-generational interactions on energy in the home

For the UK to reach the strict emissions targets set within the 2008 Climate Change Act, significant reductions in energy consumption and emissions must be made across every sector. Whilst many new energy initiatives aimed at improving existing homes have been launched (and closed) over the years, the fact remains that the UK now has amongst the worst-performing homes in Europe. To add to this, the rising cost of living, particularly of utilities, is putting ever-increasing strain on residents. To address these issues, alternative solutions that are affordable and achievable are being explored. Improving occupant energy literacy and environmental awareness could be an approach to achieving reductions in home energy consumption. A potentially influencing factor in the home is children. As agents of change, children may disseminate environmental knowledge to older generations. This could be an effective way of improving their parents’ energy literacy and in turn their energy behaviour decisions.This research tested four different methods of initiating inter-generational interactions on energy in the home. It investigated what topics and content would support improvements in energy literacy, for both children and adults, as well as how to teach this content to children. Interventions tested the differences between teaching online at home or teaching in person within the school environment. Differing types of home activities, each intended to create a potential for the interaction to take place, were tested, ranging from simple ’Snakes and ladders’ style games for children to play with their parents, to gamified continuous data logging of home energy behaviour by the participating children. A re-playable longitudinal intervention was also testedResults overall suggested that children learnt more effectively within the school environment compared to the online home environment. It also highlighted that just one single lesson is enough to improve the energy literacy of children about ‘energy in the home’ – although an ‘Eco Day’, comprising of several lessons and varying environmental topics, seemed to have a longer-lasting effect on the children. When considering the intergeneration interactions, all methods showed promising results when gathering feedback from parents about interactions and conversations with their children. Parents reported that they intended to sustain behavioural changes that they had made due to the intervention.Method one reinforced the rationale behind the need for inter-generational influences as it showed homes with children consumed more energy than both those without and those with elderly dependants.Method two (in the school context) found that primary-aged children responded well to scientific topics traditionally not taught until secondary school such as energy sources and embodied carbon. Participating parents stated knowledge was passed on to them through the interactions created by the intervention’s home activities.Method three (in the home context) utilised gas meter readings before, during and after an intervention and showed that as the number of interactions with the intervention’s ’Kids4climate website’ increased, rates of gas consumption decreased. Having said that, several significant outside factors affected this study; namely the outbreak of COVID-19, war between Russia and Ukraine and most influentially, the UK price cap on energy being increased several times.Method four (in the school context) reported that "concern for climate change" and "Consideration of environmental impacts of decisions" both declined throughout the study for the control group. Whereas the intervention group maintained their high levels of concern and consideration, suggesting a positive influence from the intervention.This research has successfully shown that several methods can be used to initiate intergenerational energy interactions in the home. Although their effectiveness varied, both ‘online’ and ‘in-person’ interventions can be used to increase and improve child-to-adult interactions and in turn positively influence energy decisions in the home. In terms of the practical applications of this research, it has been shown that at the small scale of this research, improving the energy literacy levels of children and providing the opportunity for inter-generational interaction to take place can lead to better energy decisions being made by the main occupants in the home. It is a recommendation from this research that energy literacy should be incorporated into the next edition of the National Curriculum

Discovery and target identification of SICLOPPS-derived antibacterial cyclic peptides

The rise and rapid spread of antibiotic resistance is one of the great challenges facing modern medicine, creating an urgent need for novel and innovative antibiotics. Synthetic small molecule screens have historically yielded few antibiotics used clinically, but synthetic cyclic peptide libraries may revolutionise antibiotic discovery, as they can engage a greater breadth of challenging targets than small molecule compounds. Split-intein circular ligation of peptides and proteins (SICLOPPS) is a method of generating genetically encoded cyclic peptide libraries which can be expressed and screened intracellularly. In this work, a 3.2-million-membered CXXXXX library (where X = any of the 20 canonical amino acids) was created using SICLOPPS and screened for inhibitors of the bacterial Rod system. The Rod system contains both a validated antibiotic target and potential new targets and is an attractive focus for antibiotic discovery. The Rod system is essential in E. coli and other rod-shaped bacteria, but not in E. coli exhibiting upregulation of the cell division protein FtsZ (termed FtsZUP cells). Mecillinam is an antibiotic which causes toxic malfunction of the Rod system. Therefore, Rod system inhibition confers mecillinam resistance in FtsZUP E. coli but is lethal to wild-type E. coli. The CXXXXX library was screened in FtsZUP E. coli DH5α for cyclic peptides which suppress mecillinam toxicity. NGS analysis and motif discovery identified 13 cyclic peptides of interest from the screen. One of these cyclic peptides, cyclo-CVKYKP, was found to cause modest growth inhibition of E. coli DH5α. Cyclo-CVKYKP rescued growth of FtsZUP E. coli DH5α treated with mecillinam and failed to block the growth of FtsZUP E. coli DH5α in which the Rod system is non-essential. Scanning electron microscopy found that cyclo-CVKYKP-treated FtsZUP E. coli DH5α cells exhibit morphological defects and frequently grow as spheres instead of rods. These observations indicate that cyclo-CVKYKP is a Rod system inhibitor.Cyclo-SMDIKG is a previously reported SICLOPPS-derived antibacterial cyclic peptide with an unknown mode of action. To shed light on its mode of action, eight E. coli proteins were tested for their ability to suppress cyclo-SMDIKG toxicity when overexpressed. This led to the identification of ErpA, an iron-sulfur cluster protein essential for aerobic and anaerobic respiration in E. coli, as a candidate cyclo-SMDIKG target. Microscale thermophoresis (MST) analysis of cyclo-SMDIKG binding to apo-ErpA found a likely very weak binding interaction. However, MST analysis of cyclo-SMDIKG binding to holo-ErpA suggested preferential binding to holo-ErpA with much higher affinity. Further work is needed to confirm this observation.This study showcases SICLOPPS as a promising and flexible approach to synthetic library screening for antibiotic discovery, yielding antibacterial cyclic peptides with putative novel targets to guide future innovative antibiotic development.<br/

Cross-Cultural Consortium on Irritability (C3I): An International Network for Research on Cultural Similarities and Differences in Irritability

ObjectiveIrritability is among the top reasons for youth mental health referrals worldwide. Cultural factors may affect how irritability manifests and develops; how it is experienced by youth and responded to by their caregivers; and how it is treated. However, the influences of cultural context on irritability have received little systematic investigation.MethodThe Cross-Cultural Consortium on Irritability (C3I; https://m.yale.edu/c3i) is an international research network created to increase the limited evidence base on cross-cultural similarities and differences in irritability. By bringing together researchers worldwide, C3I provides an innovative and collaborative approach to address unmet needs and explore novel research questions regarding cultural variation in irritability. Additionally, combining resources and data across the globe helps produce robust, reproducible, and generalizable results using large mega-data. One important initiative involves pooling existing datasets to support manuscript collaborations. The first three such projects focus on cross-cultural comparisons of the following irritability-related topics: boundaries of normative behavior; association with suicidality and self-harm; and informant effects. Another ongoing effort involves conceptualization of irritability across cultures. Other efforts include promoting projects of primary data collection using qualitative and quantitative methods, harmonization across measures, and facilitating/supporting community-based participatory research and engagement.DiscussionC3I is an innovative, collaborative research structure to build a robust, reproducible, and generalizable evidence base on irritability and its characteristics, including socio-cultural influences. This evidence base will facilitate recognition and assessment of irritability and, ultimately, inform development of effective, culturally informed prevention and intervention to benefit the largest possible number of youth and their families