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Circular Solutions: Assessing the Viability of Photovoltaic Waste Recycling in the United Kingdom
Get PDFThe demand for the generation of energy using photovoltaics (PV) has risen exponentially in recent times all over the world. The United Kingdom (UK) has also made a rapid increase in PV installations and is implementing more developing plans in the future as it is focusing on generating significant amount of electricity using photovoltaics. These PV installations will become waste in future. Hence, it is important to plan the end-of-life management of PV waste. This paper gives an insight into the current and future scenarios of PV waste recycling in the UK with literature reviews, discussions on recycling methods and cost benefit analysis. It shows a projection of PV waste in future, by exploring the installation of a recycling facility based on Full Recovery End of Life Photovoltaic (FRELP) method of recycling in Cornwall, UK. From the analysis, it was calculated that the recycling facility could generate total yearly revenue of £5,852,745.80 approximately with a profit of £92,435.14
A Novel Multi-Sensor Nonlinear Tightly-Coupled Framework for Composite Robot Localization and Mapping
Get PDFComposite robots often encounter difficulties due to changes in illumination, external disturbances, reflective surface effects, and cumulative errors. These challenges significantly hinder their capabilities in environmental perception and the accuracy and reliability of pose estimation. We propose a nonlinear optimization approach to overcome these issues to develop an integrated localization and navigation framework, IIVL-LM (IMU, Infrared, Vision, and LiDAR Fusion for Localization and Mapping). This framework achieves tightly coupled integration at the data level using inputs from an IMU (Inertial Measurement Unit), an infrared camera, an RGB (Red, Green and Blue) camera, and LiDAR. We propose a real-time luminance calculation model and verify its conversion accuracy. Additionally, we designed a fast approximation method for the nonlinear weighted fusion of features from infrared and RGB frames based on luminance values. Finally, we optimize the VIO (Visual-Inertial Odometry) module in the R3LIVE++ (Robust, Real-time, Radiance Reconstruction with LiDAR-Inertial-Visual state Estimation) framework based on the infrared camera’s capability to acquire depth information. In a controlled study, using a simulated indoor rescue scenario dataset, the IIVL-LM system demonstrated significant performance enhancements in challenging luminance conditions, particularly in low-light environments. Specifically, the average RMSE ATE (Root Mean Square Error of absolute trajectory Error) improved by 23% to 39%, with reductions from 0.006 to 0.013. At the same time, we conducted comparative experiments using the publicly available TUM-VI (Technical University of Munich Visual-Inertial Dataset) without the infrared image input. It was found that no leading results were achieved, which verifies the importance of infrared image fusion. By maintaining the active engagement of at least three sensors at all times, the IIVL-LM system significantly boosts its robustness in both unknown and expansive environments while ensuring high precision. This enhancement is particularly critical for applications in complex environments, such as indoor rescue operations
Downhill running does not alter blood C1q availability or complement-dependent cytotoxicity of therapeutic monoclonal antibodies against haematological cancer cell lines in vitro
Get PDFComplement-dependent cytotoxicity (CDC) is a primary mechanism-of-action of monoclonal antibody (mAb) immunotherapies used to treat haematological cancers, including rituximab and daratumumab. However, mAb efficacy may be limited by reduced bioavailability of complement C1q – which activates the complement classical pathway following interactions with mAb-opsonised target cells. C1q is secreted by phagocytes upon recruitment to sites of muscle damage to facilitate muscular repair, hence we hypothesised that muscle damaging exercise may increase C1q ‘spill-over’ into blood. Additionally, other complement proteins (e.g., C1s) have been reported to increase following ultra-endurance and resistance exercise. Taken together, we hypothesised that muscle damaging exercise could be harnessed to enhance mAb-mediated CDC. In this study, n = 8 healthy males (28 ± 5-years) completed two 45-minute treadmill running protocols: (1) a flat running protocol at a speed 15% above anaerobic threshold, and (2) a downhill running protocol (− 10% slope) at the same speed. Blood samples were collected before, immediately after, and 1-hour, 24-hours, 2-days, and 4-days after exercise. Isolated serum was assessed for C1q by ELISA, and used to measure mAb (rituximab, daratumumab) mediated CDC against two haematological cancer cell lines (Raji, RPMI-8226) in vitro. Isolated plasma was assessed for markers of inflammation (C-reactive protein [CRP]), and muscle damage (creatine kinase [CK]) by turbidimetry. C1q and CDC activity were not different between running protocols and did not change over time (p > 0.05). Significantly greater perceived muscle soreness (p < 0.001) and fluctuations observed from baseline to 24-hours post-exercise in the downhill running trial in CK (+ 171%) and CRP (+ 66%) suggests some degree of muscle damage was present. It is possible that any increase in C1q post-exercise may have been masked by the increase and subsequent interaction with CRP, which utilises C1q to facilitate muscular repair. This is the first study to investigate whether exercise can increase circulating C1q and improve mAb-mediated CDC and our findings show that downhill running exercise does not increase circulating C1q nor improve CDC in vitro
From a place of silence: Articulations of the unspoken
No full textThis article discusses two albums of freely improvised music in duo settings recorded during the year following the height of the COVID-19 pandemic. A reflection thereupon takes the form of a paper presented informally as work in progress at the International Network for Artistic Research in Jazz held in Graz, Austria in February 2023, and is included here for subsequent critical correlation and expansion. The 2020–21 pandemic is an important event in the telling of the story in that for the author, and the music community as a whole, it represented a time of limited opportunity in which to work collaboratively in-person with others or in front of live audiences. The eventual lifting of social distancing measures provided impetus and scope for a reawakening and the refocusing of creative identity and purpose through reconnecting with music and musicians. In response, this article concerns itself chiefly with the nature and role of interpersonal relationships in the improvisational setting and how these manifest in acts of creative interplay and embodied action. At the heart of these relationships, space is given to musings around notions of positionality, trust, empathy and love as they relate to the improvisational setting, with attention paid to how these are entwined in the construction of narrative around process and actualization in creative endeavour
Chasing noise in the stock market: an inquiry into the dynamics of investor sentiment and asset pricing
Get PDFThis study explores the inclusion of sentiment measures as a risk factor in asset pricing. Using UK market data for the period January 1993 to December 2020, we create a new sentiment variable, and construct both raw and clean sentiment indices from a principal component analysis of a variety of literature-acknowledged sentiment proxies. Essentially, the model estimations are categorized into two: first, the study documents the performance of the traditional pricing models on portfolios formed on different characteristics. Second, the study augments the first category by iterating sentiment variables into the model specification. The findings reveal that sentiment-augmented asset pricing models outperform the traditional models in explaining the excess returns of the portfolios. Furthermore, using Hansen & Jagannathan (1997) non-parametric model performance technique, we observe that the sentiment-induced models produce a small distance error compared to the traditional models, thus validating the use of sentiment measures in our pricing mechanism. It is therefore opined that extant asset pricing models may not be sufficient to explain market or pricing anomalies. Investors’ sentiment is an important systematic risk factor that possesses useful information, and by implication, market analysts and stakeholders must take serious cognizance of its propensities when forecasting risk-adjusted returns
Assessing the potential of acoustic telemetry to underpin the regional management of basking sharks (Cetorhinus maximus)
Get PDFAcoustic telemetry can provide valuable space-use data for a range of marine species. Yet the deployment of species-specific arrays over vast areas to gather data on highly migratory vertebrates poses formidable challenges, often rendering it impractical. To address this issue, we pioneered the use of acoustic telemetry on basking sharks (Cetorhinus maximus) to test the feasibility of using broadscale, multi-project acoustic receiver arrays to track the movements of this species of high conservation concern through the coastal waters of Ireland, Northern Ireland, and Scotland. Throughout 2021 and 2022, we tagged 35 basking sharks with acoustic transmitters off the west coast of Ireland; 27 of these were detected by 96 receiver stations throughout the study area (n = 9 arrays) with up to 216 detections of an individual shark (mean = 84, s.d. 65). On average, sharks spent ~ 1 day at each acoustic array, with discrete residency periods of up to nine days. Twenty-one sharks were detected at multiple arrays with evidence of inter-annual site fidelity, with the same individuals returning to the same locations in Ireland and Scotland over 2 years. Eight pairs of sharks were detected within 24 h of each other at consecutive arrays, suggesting some level of social coordination and synchronised movement. These findings demonstrate how multi-project acoustic telemetry can support international, cost-effective monitoring of basking sharks and other highly mobile species. Decision support tools such as these can consolidate cross-border management strategies, but to achieve this goal, collaborative efforts across jurisdictions are necessary to establish the required infrastructure and secure ongoing support
Information leakage prior to market switches and the importance of Nominated Advisers
No full textThis study tests the information leakage hypothesis prior to the public announcement of firms switching between the Alternative Investment Market (AIM) and the Main Market (MM) in the UK. We find significant abnormal stock returns 60 trading days prior to the announcement of these switches. The results are robust after controlling for switching anticipation, rumors, other major corporate announcements, and firm performance a year prior to the switch. We also show that having a reputable Nominated Adviser (Nomad) significantly moderates the abnormal stock returns prior to market switches. However, this effect does not hold when Nomads also act as brokers in firms that switch markets. Overall, these findings provide novel evidence about abnormal stock returns prior to the announcement of market switches in the UK and the role of Nomads. As such, we shed light on the significance and the limits of decentralized regulation on informed trading activity
Predation on Live and Artificial Insect Prey Shows Different Global Latitudinal Patterns
Get PDFAim: Long‐standing theory predicts that the intensity of biotic interactions increases from high to low latitudes. Studies addressing geographic variation in predation on insect prey have often relied on prey models, which lack many characteristics of live prey. Our goals were to explore global latitudinal patterns of predator attack rates on standardised live insect prey and to compare the patterns in predation on live insects with those on plasticine prey models. Location: Global forested areas. Time Period: 2021–2023. Major Taxa: Arthropods, birds. Methods: We measured predation rates in 43 forested locations distributed across five continents from 34.1° S to 69.5° N latitude. At each location, we exposed 20 sets of three bait types, one set per tree. Each set included three live fly larvae (maggots), three live fly puparia and three plasticine models of the puparia. We used glue rings to isolate half of the sets from non‐flying predators. Results: Arthropod attack rates on plasticine prey decreased linearly from low to high latitudes, whereas attack rates on maggots had a U shaped distribution, with the lowest predation rates at temperate latitudes and the highest rates at tropical and boreal latitudes. This difference emerged from intensive predator attacks on live maggots, but not on plasticine models, in boreal sites. Site‐specific attack rates of arthropod predators on live and plasticine prey were not correlated. In contrast, bird attack rates on live maggots and plasticine models were positively correlated, but did not show significant latitudinal changes. Main Conclusions: Latitudinal patterns in predation differ between major groups of predators and between types of prey. Poleward decreases in both arthropod and combined arthropod and bird predation on plasticine models do not mirror patterns of predation on our live prey, the latter likely reflecting real patterns of predation risk better than do patterns of attack on artificial prey
Unveiling machine learning strategies and considerations in intrusion detection systems: a comprehensive survey
Get PDFThe advancement of communication and internet technology has brought risks to network security. Thus, Intrusion Detection Systems (IDS) was developed to combat malicious network attacks. However, IDSs still struggle with accuracy, false alarms, and detecting new intrusions. Therefore, organizations are using Machine Learning (ML) and Deep Learning (DL) algorithms in IDS for more accurate attack detection. This paper provides an overview of IDS, including its classes and methods, the detected attacks as well as the dataset, metrics, and performance indicators used. A thorough examination of recent publications on IDS-based solutions is conducted, evaluating their strengths and weaknesses, as well as a discussion of their potential implications, research challenges, and new trends. We believe that this comprehensive review paper covers the most recent advances and developments in ML and DL-based IDS, and also facilitates future research into the potential of emerging Artificial Intelligence (AI) to address the growing complexity of cybersecurity challenges
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