Torsion induces Gravity

In this work the Poincare-Chern Simons and Anti de Sitter Chern Simons gravities are studied. For both a solution that can be casted as a black hole with manifest torsion is found. Those solutions resemble Schwarzschild and Schwarzschild-AdS solutions respectively.Comment: 4 pages, RevTe

Photoelectrochemical properties of sol–gel obtained titanium oxide

The photoelectrochemical properties of a sol–gel prepared titanium oxide coating applied onto a Ti substrate were investigated. The oxide coating was formed from an inorganic sol thermally treated in air at 350 °C. The coating consisted of agglomerates of narrow size distribution around 100 nm. The photoelectrochemical characteristics were evaluated by investigating the changes in the open circuit potential, current transients and impedance characteristics of a Ti/TiO2 electrode upon illumination by UV light in H2SO4 solution and in the oxidation of benzyl alcohol. The electrode was found to be active for photoelectrochemical reactions in the investigated solutions

Selecting the most suitable classification algorithm for supporting assistive technology adoption for people with dementia: A multicriteria framework

The number of people with dementia (PwD) is increasing dramatically. PwD exhibit impairments of reasoning, memory, and thought that require some form of self‐management intervention to support the completion of everyday activities while maintaining a level of independence. To address this need, efforts have been directed to the development of assistive technology solutions, which may provide an opportunity to alleviate the burden faced by the PwD and their carers. Nevertheless, uptake of such solutions has been limited. It is therefore necessary to use classifiers to discriminate between adopters and nonadopters of these technologies in order to avoid cost overruns and potential negative effects on quality of life. As multiple classification algorithms have been developed, choosing the most suitable classifier has become a critical step in technology adoption. To select the most appropriate classifier, a set of criteria from various domains need to be taken into account by decision makers. In addition, it is crucial to define the most appropriate multicriteria decision‐making approach for the modelling of technology adoption. Considering the above‐mentioned aspects, this paper presents the integration of a five‐phase methodology based on the Fuzzy Analytic Hierarchy Process and the Technique for Order of Preference by Similarity to Ideal Solution to determine the most suitable classifier for supporting assistive technology adoption studies. Fuzzy Analytic Hierarchy Process is used to determine the relative weights of criteria and subcriteria under uncertainty and Technique for Order of Preference by Similarity to Ideal Solution is applied to rank the classifier alternatives. A case study considering a mobile‐based self‐management and reminding solution for PwD is described to validate the proposed approach. The results revealed that the best classifier was k‐nearest‐neighbour with a closeness coefficient of 0.804, and the most important criterion when selecting classifiers is scalability. The paper also discusses the strengths and weaknesses of each algorithm that should be addressed in future research

IntAct:intra-operative fluorescence angiography to prevent anastomotic leak in rectal cancer surgery: a randomized controlled trial

Aim Anastomotic leak (AL) is a major complication of rectal cancer surgery. Despite advances in surgical practice, the rates of AL have remained static, at around 10–15%. The aetiology of AL is multifactorial, but one of the most crucial risk factors, which is mostly under the control of the surgeon, is blood supply to the anastomosis. The MRC/NIHR IntAct study will determine whether assessment of anastomotic perfusion using a fluorescent dye (indocyanine green) and near‐infrared laparoscopy can minimize the rate of AL leak compared with conventional white‐light laparoscopy. Two mechanistic sub‐studies will explore the role of the rectal microbiome in AL and the predictive value of CT angiography/perfusion studies. Method IntAct is a prospective, unblinded, parallel‐group, multicentre, European, randomized controlled trial comparing surgery with intra‐operative fluorescence angiography (IFA) against standard care (surgery with no IFA). The primary end‐point is rate of clinical AL at 90 days following surgery. Secondary end‐points include all AL (clinical and radiological), change in planned anastomosis, complications and re‐interventions, use of stoma, cost‐effectiveness of the intervention and quality of life. Patients should have a diagnosis of adenocarcinoma of the rectum suitable for potentially curative surgery by anterior resection. Over 3 years, 880 patients from 25 European centres will be recruited and followed up for 90 days. Discussion IntAct will rigorously evaluate the use of IFA in rectal cancer surgery and explore the role of the microbiome in AL and the predictive value of preoperative CT angiography/perfusion scanning

Experimental and numerical study of globe valve housing

Complex structure experimental analysis has always been a huge challenge for researchers. Conventional experimental methods (e.g., strain gauges) give only limited data sets regarding measurement on critical areas with high geometrical discontinuities. A 3D Digital Image Correlation method is an optical method that overcomes the limitations of conventional methods and enables full-field displacement and strain measurement of geometrically complex structures. System Aramis, based on Digital Image Correlation method, is used for experimental analysis and numerical model verification in this paper. Investigated complex structure is sphere/cylinder junction on globe valve housing subjected to axial loading. The highest experimentally measured von Mises strain values around 0.15% are recorded on cylinder/sphere intersection. Von Mises strain values on cylindrical and spherical part are several times smaller than on intersection itself. It is important to emphasize that, to the authors best knowledge, this is the first paper showing experimental results of 3D full and strain field of geometrically complex structure (sphere/cylinder intersection) on the intersection itself on pressure equipment. It is proven that 3D Digital Image Correlation method is fast and versatile method for recording strain during loading of complex structures

Gravity duals for logarithmic conformal field theories

Logarithmic conformal field theories with vanishing central charge describe systems with quenched disorder, percolation or dilute self-avoiding polymers. In these theories the energy momentum tensor acquires a logarithmic partner. In this talk we address the construction of possible gravity duals for these logarithmic conformal field theories and present two viable candidates for such duals, namely theories of massive gravity in three dimensions at a chiral point.Comment: 15 pages, 1 figure, invited plenary talk at the First Mediterranean Conference on Classical and Quantum Gravity, v2: published version, corrected typo in left eq. (5

Cross-frequency coupling of brain oscillations in studying motivation and emotion

Research has shown that brain functions are realized by simultaneous oscillations in various frequency bands. In addition to examining oscillations in pre-specified bands, interactions and relations between the different frequency bandwidths is another important aspect that needs to be considered in unraveling the workings of the human brain and its functions. In this review we provide evidence that studying interdependencies between brain oscillations may be a valuable approach to study the electrophysiological processes associated with motivation and emotional states. Studies will be presented showing that amplitude-amplitude coupling between delta-alpha and delta-beta oscillations varies as a function of state anxiety and approach-avoidance-related motivation, and that changes in the association between delta-beta oscillations can be observed following successful psychotherapy. Together these studies suggest that cross-frequency coupling of brain oscillations may contribute to expanding our understanding of the neural processes underlying motivation and emotion

Timing of Intervention Affects Brain Electrical Activity in Children Exposed to Severe Psychosocial Neglect

Background: Early psychosocial deprivation has profound effects on brain activity in the young child. Previous reports have shown increased power in slow frequencies of the electroencephalogram (EEG), primarily in the theta band, and decreased power in higher alpha and beta band frequencies in infants and children who have experienced institutional care. Methodology/Principal Findings: We assessed the consequences of removing infants from institutions and placing them into a foster care intervention on brain electrical activity when children were 8 years of age. We found the intervention was successful for increasing high frequency EEG alpha power, with effects being most pronounced for children placed into foster care before 24 months of age. Conclusions/Significance: The dependence on age of placement for the effects observed on high frequency EEG alpha power suggests a sensitive period after which brain activity in the face of severe psychosocial deprivation is less amenabl

Artificial intelligence for predictive biomarker discovery in immuno-oncology: a systematic review

Background: The widespread use of immune checkpoint inhibitors (ICIs) has revolutionised treatment of multiple cancer types. However, selecting patients who may benefit from ICI remains challenging. Artificial intelligence (AI) approaches allow exploitation of high-dimension oncological data in research and development of precision immuno-oncology. Materials and methods: We conducted a systematic literature review of peer-reviewed original articles studying the ICI efficacy prediction in cancer patients across five data modalities: genomics (including genomics, transcriptomics, and epigenomics), radiomics, digital pathology (pathomics), and real-world and multimodality data. Results: A total of 90 studies were included in this systematic review, with 80% published in 2021-2022. Among them, 37 studies included genomic, 20 radiomic, 8 pathomic, 20 real-world, and 5 multimodal data. Standard machine learning (ML) methods were used in 72% of studies, deep learning (DL) methods in 22%, and both in 6%. The most frequently studied cancer type was non-small-cell lung cancer (36%), followed by melanoma (16%), while 25% included pan-cancer studies. No prospective study design incorporated AI-based methodologies from the outset; rather, all implemented AI as a post hoc analysis. Novel biomarkers for ICI in radiomics and pathomics were identified using AI approaches, and molecular biomarkers have expanded past genomics into transcriptomics and epigenomics. Finally, complex algorithms and new types of AI-based markers, such as meta-biomarkers, are emerging by integrating multimodal/multi-omics data. Conclusion: AI-based methods have expanded the horizon for biomarker discovery, demonstrating the power of integrating multimodal data from existing datasets to discover new meta-biomarkers. While most of the included studies showed promise for AI-based prediction of benefit from immunotherapy, none provided high-level evidence for immediate practice change. A priori planned prospective trial designs are needed to cover all lifecycle steps of these software biomarkers, from development and validation to integration into clinical practice