First Measurements with NeXtRAD, a Polarimetric X/L Band Radar Network

NeXtRAD is a fully polarimetric, X/L Band radar network. It is a development of the older NetRAD system and builds on the experience gained with extensive deployments of NetRAD for sea clutter and target measurements. In this paper we will report on the first measurements with NeXtRAD, looking primarily at sea clutter and some targets, as well as early attempts at calibration using corner reflectors, and an assessment of the polarimetric response of the system. We also highlight innovations allowing for efficient data manipulation post measurement campaigns, as well as the plans for the coming years with this system

Peeking Inside the Schufa Blackbox: Explaining the German Housing Scoring System

Explainable Artificial Intelligence is a concept aimed at making complex algorithms transparent to users through a uniform solution. Researchers have highlighted the importance of integrating domain specific contexts to develop explanations tailored to end users. In this study, we focus on the Schufa housing scoring system in Germany and investigate how users information needs and expectations for explanations vary based on their roles. Using the speculative design approach, we asked business information students to imagine user interfaces that provide housing credit score explanations from the perspectives of both tenants and landlords. Our preliminary findings suggest that although there are general needs that apply to all users, there are also conflicting needs that depend on the practical realities of their roles and how credit scores affect them. We contribute to Human centered XAI research by proposing future research directions that examine users explanatory needs considering their roles and agencies.Comment: 7 pages, 3 figures, ACM CHI 2023 Workshop on Human-Centered Explainable AI (HCXAI

Removal of arsenic (V) from aqueous solutions using chitosan-red scoria and chitosan-pumice blends

In different regions across the globe, elevated arsenic contents in the groundwater constitute a major health problem. In this work, a biopolymer chitosan has been blended with volcanic rocks (red scoria and pumice) for arsenic (V) removal. The effect of three blending ratios of chitosan and volcanic rocks (1:2, 1:5 and 1:10) on arsenic removal has been studied. The optimal blending ratio was 1:5 (chitosan:volcanic rocks) with maximum adsorption capacity of 0.72 mg/g and 0.71 mg/g for chitosan:red scoria (Ch-Rs) and chitosan:pumice (Ch-Pu), respectively. The experimental adsorption data fitted well a Langmuir isotherm (R-2 > 0.99) and followed pseudo-second-order kinetics. The high stability of the materials and their high arsenic (V) removal efficiency (similar to 93%) in a wide pH range (4 to 10) are useful for real field applications. Moreover, the blends could be regenerated using 0.05 M NaOH and used for several cycles without losing their original arsenic removal efficiency. The results of the study demonstrate that chitosan-volcanic rock blends should be further explored as a potential sustainable solution for removal of arsenic (V) from water

Bioenergetic-active materials enhance tissue regeneration by modulating cellular metabolic state

Cellular bioenergetics (CBE) plays a critical role in tissue regeneration. Physiologically, an enhanced metabolic state facilitates anabolic biosynthesis and mitosis to accelerate regeneration. However, the development of approaches to reprogram CBE, towards the treatment of substantial tissue injuries, hasbeen limited thus far. Here, we show that induced repair in a rabbit model of weight-bearing bone defects is greatly enhanced using a bioenergetic-active material (BAM) scaffold, compared to commercialized poly (lactic acid) and calcium phosphate ceramic scaffolds. This material was composed of energy-active units that can be released in a sustained degradation-mediated fashion once implanted. By establishing an intramitochondrial metabolic bypass, the internalized energy-active units significantly elevatemitochondria membrane potential (ΔΨm) to supply increased bioenergetic levels and accelerate bone formation. The ready-to-use material developed here represents a highly efficient and easy-to-implement therapeutic approach toward tissue regeneration, withpromise for bench-to-bedside translation

Modeling biological age using blood biomarkers and physical measurements in Chinese adults

Background This study aimed to: 1) assess the associations of biological age acceleration based on Klemera and Doubal's method (KDM-AA) with long-term risk of all-cause mortality; and 2) compare the association of KDM-AA with all-cause mortality among participants potentially at different stages of the cardiovascular disease (CVD) continuum. Methods The present study was based on a subpopulation of the China Kadoorie Biobank, with baseline survey during 2004–08. A total of 12,377 participants free of ischemic heart disease, stroke, or cancer at baseline were included, in which 8180 participants were identified to develop major coronary event (MCE), ischemic stroke (IS), intracerebral hemorrhage (ICH) or subarachnoid hemorrhage (SAH), and 4197 remained free of these cardiovascular diseases before 1 January 2014. These participants were followed up until 1 Jan 2018. KDM-AA was calculated by regressing biological age measurement, which was constructed based on baseline 16 physical and 9 biochemical markers using Klemera and Doubal's method, on chronological age. We estimated the associations of KDM-AA with the mortality risk using the hazard ratio (HR) and 95% confidence interval (CI) from Cox proportional hazard models. We assessed discrimination performance by Harrell's C-index and net reclassification index (NRI). Findings The participants who developed MCE (mean KDM-AA = 0.1 year, standard deviation [SD] = 1.6 years) or ICH/SAH (0.3 ± 1.5 years) during subsequent follow-up showed accelerated aging at baseline compared to those of IS (0.0 ± 1.2 years) and control (−0.3 ± 1.3 years) groups. The KDM-AA was positively associated with long-term risk of all-cause mortality (HR = 1.20; 95% CI: 1.17, 1.23), and the association was robust for participants potentially at different stages of the CVD continuum. Adding KDM-AA improved mortality prediction compared to the model only with sociodemographic and lifestyle factors in whole participants, with the Harrell's C-index increasing from 0.813 (0.807, 0.819) to 0.821 (0.815, 0.826) (NRI = 0.011; 95% CI: 0.003, 0.019). Interpretation In this middle-aged and elderly Chinese population, the KDM-AA is a promising measurement for biological age, and can capture the difference in cardiovascular health and predict the risk of all-cause mortality over a decade. Funding This work was supported by National Natural Science Foundation of China (82192904, 82192901, 82192900, 81941018). The CKB baseline survey and the first re-survey were supported by a grant from the Kadoorie Charitable Foundation Hong Kong. The long-term follow-up is supported by grants from the UK Wellcome Trust (212946/Z/18/Z, 202922/Z/16/Z, 104085/Z/14/Z, 088158/Z/09/Z), grants (2016YFC0900500) from the National Key R&D Program of China, National Natural Science Foundation of China (81390540, 91846303), and Chinese Ministry of Science and Technology (2011BAI09B01)

The impacts of COVID-19 restrictions on care-givers of people with cognitive impairment and their support needs: A mixed-methods systematic review

The COVID-19 pandemic and ensuing restrictions/lockdowns have caused significant physical and psychological consequences for people with cognitive impairment who are heavily dependent on their care-givers. However, little is known about the impact on care-givers, the factors that exacerbate their situation and what supports they need. The aims of this paper are threefold: (a) to examine the impact of COVID-19 physical restrictions on both formal and informal care-givers of people with cognitive impairment; (b) to identify attributing factors influencing this impact; and (c) to recognise their support needs. Further, this paper informs future research, policy and practice. Guided by the Joanna Briggs Institute framework, a systematic review was conducted using a mixed-methods convergent integrated approach. Eight databases were searched using keywords related to COVID-19 restriction, dementia care-givers, impacts and care settings, followed by a manual search. The study was limited to primary research published in English between January 2020 and December 2021. Of the 840 records identified, 30 met the inclusion criteria. Service withdrawal and social distancing has effectively led to the reprivatisation of care to the family, particularly women. Care-givers experienced negative impacts including reduced psychological wellbeing and physical health, increased care burden and financial difficulties. A number of clinical attributes and socio-demographic factors influenced the COVID-19 impact on care-givers. Consequently, counselling services, assistance with care and financial support were identified as support needs. Implementation of new support and the strengthening of existing services are recommended to enhance resilience, build capacity to support care-givers in any given situation and mitigate the effects of future outbreaks