An enhanced mobile ambulatory assessment system for alcohol craving studies

Currently, most methods in clinical psychology research primarily rely on questionnaires and interviews with examiners instead of providing real-life subject behavioral and psychology data monitoring and collecting services. This thesis presents an android-OS-based mobile Ambulatory Assessment System, for psychology research -- especially alcohol craving studies -- to improve current methods and provide real-time data monitoring, collecting and processing. As current generation smartphones provide more powerful communication platform, embedded with robust built-in sensor suits and vigorous processing and storage capabilities, smartphones play an increasingly significant role in various sensing tasks such as activities monitoring personal health surveillance and environment. This system consists of four parts: a wearable sensor (Equivital EQ2 sensor) that measures physiological data, an Android smartphone, a web server and a data analysis module. The smartphone is responsible for collecting and recording physiological data from the wireless wearable sensor, interacting with the users to conduct various surveys, and uploading data to the web server. The server is responsible for data processing, computation, and visualization. Utilizing machine learning methods, data from the sensor and survey build models that predict how various psychological disorders cause alcohol or other substance cravings and emotion dysregulation. The system has been deployed in a field study of alcohol craving, and initial data collected from real subjects proved promising

A high energy output and low onset temperature nanothermite based on three-dimensional ordered macroporous nano-NiFe2O4

Three-dimensional ordered macroporous (3DOM) Al/NiFe2O4 nanothermite has been obtained by colloidal crystal templating method combined with magnetron sputtering processing. Owing to the superior material properties and unique 3DOM structural characteristics of composite metal oxides, the heat output of the Al/NiFe2O4 nanothermite is up to 2921.7 J g− 1, which is more than the values of Al/NiO and Al/Fe2O3 nanothermites in literature. More importantly, by comparison to the other two nanothermites, the onset temperature of 298.2 °C from Al/NiFe2O4 is remarkably low, which means it can be ignited more easily. Laser ignition experiment indicate that the synthesized Al/NiFe2O4 nanothermite can be easily ignited by laser. In addition, the preparation process is highly compatible with the MEMS technology. These exciting achievements have great potential to expand the scope of nanothermite applications

InCoder: A Generative Model for Code Infilling and Synthesis

Code is seldom written in a single left-to-right pass and is instead repeatedly edited and refined. We introduce InCoder, a unified generative model that can perform program synthesis (via left-to-right generation) as well as editing (via infilling). InCoder is trained to generate code files from a large corpus of permissively licensed code, where regions of code have been randomly masked and moved to the end of each file, allowing code infilling with bidirectional context. Our model is the first generative model that is able to directly perform zero-shot code infilling, which we evaluate on challenging tasks such as type inference, comment generation, and variable re-naming. We find that the ability to condition on bidirectional context substantially improves performance on these tasks, while still performing comparably on standard program synthesis benchmarks in comparison to left-to-right only models pretrained at similar scale. The InCoder models and code are publicly released. https://sites.google.com/view/incoder-code-modelsComment: 25 pages, 13 figures. v2: added NeoX-20B results & StackOverflow corpus inf

Fe controls the reproduction of zoogloea and sludge bulking in oil-in-iron wastewater

Following the final biological treatment, the oil wastewater is intended for reuse in factory floor cleaning. However, the presence of varying concentrations of oil-in-iron characteristic wastewater has led to a sudden surge in sludge SV to 90%, adversely affecting water treatment efficiency. In this study, we conducted an analysis of microbial community structure and selected pepA and 16S rRNA primers to assess the proportions of zoogloea and total bacteria in sludge bulking. Iron concentration plays a pivotal role, and it should be maintained at or 0.6 mgL−1. By selective discharging of sludge to maintain 1,700 mgL−1, we minimized iron enrichment, thereby enhancing the sludge settling performance. Maintaining dissolved oxygen (DO) at 3.5 mgL−1 supports the aerobic sludge's ability to replenish iron in its system, while the oil content should be controlled at 145.33 mgL−1 to reduce the release of iron into the water. The order of significance is as follows: sludge concentration > Fe amount > DO > oil content. Implementing this approach was applied in the field for 1 week and effectively reduced the SV from 90% to approximately 43%. The interaction between quorum sensing molecules related to sludge bulking and iron, leading to the formation of complexes, underscores the significance of controlling iron levels. This study offers a valuable case for practical application of quorum quenching technology in oil wastewater, presenting a rapid, efficient, and cost-effective solution to address the issue of sludge bulking

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries