Miracle-dz/UniFAR-FTUs huggingface dataset:
Diabetes Self-management Apps: Systematic Review of Adoption Determinants and Future Research Agenda

Background Most diabetes management involves self-management. Effective self-management of the condition improves diabetes control, reduces the risk of complications, and improves patient outcomes. Mobile apps for diabetes self-management (DSM) can enhance patients’ self-management activities. However, they are only effective if clinicians recommend them, and patients use them. Objective This study aimed to explore the determinants of DSM apps’ use by patients and their recommendations by health care professionals (HCPs). It also outlines the future research agenda for using DSM apps in diabetes care. Methods We systematically reviewed the factors affecting the adoption of DSM apps by both patients and HCPs. Searches were performed using PubMed, Scopus, CINAHL, Cochrane Central, ACM, and Xplore digital libraries for articles published from 2008 to 2020. The search terms were diabetes, mobile apps, and self-management. Relevant data were extracted from the included studies and analyzed using a thematic synthesis approach. Results A total of 28 studies met the inclusion criteria. We identified a range of determinants related to patients’ and HCPs’ characteristics, experiences, and preferences. Young female patients were more likely to adopt DSM apps. Patients’ perceptions of the benefits of apps, ease of use, and recommendations by patients and other HCPs strongly affect their intention to use DSM apps. HCPs are less likely to recommend these apps if they do not perceive their benefits and may not recommend their use if they are unaware of their existence or credibility. Young and technology-savvy HCPs were more likely to recommend DSM apps. Conclusions Despite the potential of DSM apps to improve patients’ self-care activities and diabetes outcomes, HCPs and patients remain hesitant to use them. However, the COVID-19 pandemic may hasten the integration of technology into diabetes care. The use of DSM apps may become a part of the new normal.
A Deep Ensemble Neural Network with Attention Mechanisms for Lung Abnormality Classification Using Audio Inputs

Medical audio classification for lung abnormality diagnosis is a challenging problem owing to comparatively unstructured audio signals present in the respiratory sound clips. To tackle such challenges, we propose an ensemble model by incorporating diverse deep neural networks with attention mechanisms for undertaking lung abnormality and COVID-19 diagnosis using respiratory, speech, and coughing audio inputs. Specifically, four base deep networks are proposed, which include attention-based Convolutional Recurrent Neural Network (A-CRNN), attention-based bidirectional Long Short-Term Memory (A-BiLSTM), attention-based bidirectional Gated Recurrent Unit (A-BiGRU), as well as Convolutional Neural Network (CNN). A Particle Swarm Optimization (PSO) algorithm is used to optimize the training parameters of each network. An ensemble mechanism is used to integrate the outputs of these base networks by averaging the probability predictions of each class. Evaluated using respiratory ICBHI, Coswara breathing, speech, and cough datasets, as well as a combination of ICBHI and Coswara breathing databases, our ensemble model and base networks achieve ICBHI scores ranging from 0.920 to 0.9766. Most importantly, the empirical results indicate that a positive COVID-19 diagnosis can be distinguished to a high degree from other more common respiratory diseases using audio recordings, based on the combined ICBHI and Coswara breathing datasets.
Ultra-high-resolution time-frequency analysis of EEG to characterise brain functional connectivity with the application in Alzheimer’s disease

Objective. This study aims to explore the potential of high-resolution brain functional connectivity based on electroencephalogram, a non-invasive low-cost technique, to be translated into a long-overdue biomarker and a diagnostic method for Alzheimer’s disease (AD). Approach. The paper proposes a novel ultra-high-resolution time-frequency nonlinear cross-spectrum method to construct a promising biomarker of AD pathophysiology. Specifically, using the peak frequency estimated from a revised Hilbert–Huang transformation (RHHT) cross-spectrum as a biomarker, the support vector machine classifier is used to distinguish AD from healthy controls (HCs). Main results. With the combinations of the proposed biomarker and machine learning, we achieved a promising accuracy of 89%. The proposed method performs better than the wavelet cross-spectrum and other functional connectivity measures in the temporal or frequency domain, particularly in the Full, Delta and Alpha bands. Besides, a novel visualisation approach developed from topography is introduced to represent the brain functional connectivity, with which the difference between AD and HCs can be clearly displayed. The interconnections between posterior and other brain regions are obviously affected in AD. Significance. Those findings imply that the proposed RHHT approach could better track dynamic and nonlinear functional connectivity information, paving the way for the development of a novel diagnostic approach.
Interleukin 15 in murine models of colitis

Inflammatory bowel diseases (IBDs) are characterized by abnormal, non‐antigen specific chronic inflammation of unknown etiology. Genome‐wide association studies show that many IBD genetic susceptibility loci map to immune function genes and compelling evidence indicate that environmental factors play a critical role in IBD pathogenesis. Clinical and experimental evidence implicate the pro‐inflammatory cytokine IL‐15 in the pathogenesis of IBD. IL‐15 and IL‐15α expression is increased in the inflamed mucosa of IBD patients. IL‐15 contributes to the maintenance of different cell subsets in the intestinal mucosa. However, very few studies have addressed the role of IL‐15 in pre‐clinical models of colitis. In this study, we use three well‐characterized models of experimental colitis to determine the contribution of IL‐15 to pathological intestinal inflammation.
World Federation of Societies of Biological Psychiatry (WFSBP) guidelines for treatment of anxiety, obsessive-compulsive and posttraumatic stress disorders – Version 3. Part I: Anxiety disorders

Abstract Aim This is the third version of the guideline of the World Federation of Societies of Biological Psychiatry (WFSBP) Task Force for the Pharmacological Treatment of Anxiety, Obsessive–Compulsive and Posttraumatic Stress Disorders (published in 2002, revised in 2008). Method A consensus panel of 33 international experts representing 22 countries developed recommendations based on efficacy and acceptability of available treatments. In total, 1007 RCTs for the treatment of these disorders in adults, adolescents, and children with medications, psychotherapy and other non-pharmacological interventions were evaluated, applying the same rigorous methods that are standard for the assessment of medications. Result This paper, Part I, contains recommendations for the treatment of panic disorder/agoraphobia (PDA), generalised anxiety disorder (GAD), social anxiety disorder (SAD), specific phobias, mixed anxiety disorders in children and adolescents, separation anxiety and selective mutism. Selective serotonin reuptake inhibitors (SSRI) and serotonin-norepinephrine reuptake inhibitors (SNRIs) are first-line medications. Cognitive behavioural therapy (CBT) is the first-line psychotherapy for anxiety disorders. The expert panel also made recommendations for patients not responding to standard treatments and recommendations against interventions with insufficient evidence. Conclusion It is the goal of this initiative to provide treatment guidance for these disorders that has validity throughout the world.
Effectiveness and safety of weekly paclitaxel and cetuximab as a salvage chemotherapy following immune checkpoint inhibitors for recurrent or metastatic head and neck squamous cell carcinoma: A multicenter clinical study

Objectives The benefit of sequential therapy after immune checkpoint inhibitor (ICI) treatment for recurrent or metastatic head and neck squamous cell carcinoma (R/M HNSCC) has been recently reported. Furthermore, there is a growing interest in the impact of cetuximab (Cmab)-containing salvage chemotherapy (SCT) and the therapeutic efficacy and adverse events (AEs) of Cmab administration prior to ICI administration. Materials and methods We retrospectively reviewed the medical records of 52 patients with R/M HNSCC treated with SCT (weekly paclitaxel [PTX], n = 7, or weekly PTX and Cmab [PC], n = 45). Results The objective response rate (ORR) and a disease control rate (DCR) was 53.3% and 91.1% in the PC group and 42.9% and 57.1% in the PTX group, respectively. There was a significant difference in the DCR between the PC and PTX groups (p = 0.0143). The overall survival (OS) and progression-free survival were significantly better in the PC group than in the PTX group. On the other hand, the incidence of drug-induced interstitial pneumonia (DI-IP) in R/M HNSCC patients who received SCT was 21.2%. Patients in the PC group were divided according to whether they received Cmab (Group A) or did not receive Cmab (Group B) as palliative therapy prior to ICIs. Group B had a significantly better OS than Group A. Furthermore, our findings suggest that the incidence rate of DI-IP during SCT might be higher in Group B. Conclusion Although PC following ICIs shows dramatic efficacy, careful monitoring of AEs, including DI-IP, is recommended.
Antifibrinolytics in the treatment of traumatic brain injury

Purpose of review Traumatic brain injury (TBI) is a leading cause of trauma-related deaths, and pharmacologic interventions to limit intracranial bleeding should improve outcomes. Tranexamic acid reduces mortality in injured patients with major systemic bleeding, but the effects of antifibrinolytic drugs on outcomes after TBI are less clear. We therefore summarize recent evidence to guide clinicians on when (not) to use antifibrinolytic drugs in TBI patients. Recent findings Tranexamic acid is the only antifibrinolytic drug that has been studied in patients with TBI. Several recent studies failed to conclusively demonstrate a benefit on survival or neurologic outcome. A large trial with more than 12 000 patients found no significant effect of tranexamic acid on head-injury related death, all-cause mortality or disability across the overall study population, but observed benefit in patients with mild to moderate TBI. Observational evidence signals potential harm in patients with isolated severe TBI. Summary Given that the effect of tranexamic acid likely depends on a variety of factors, it is unlikely that a ‘one size fits all’ approach of administering antifibrinolytics to all patients will be helpful. Tranexamic acid should be strongly considered in patients with mild to moderate TBI and should be avoided in isolated severe TBI.
Endoscopic activity in inflammatory bowel disease: clinical significance and application in practice

Endoscopy is vital for diagnosis, assessing treatment response, monitoring and surveillance in patients with inflammatory bowel disease (IBD). With the growing importance of mucosal healing as a treatment target, the assessment of disease activity by endoscopy has been accepted as the standard of care for IBD. There are many endoscopic activity indices for facilitating standardized reporting of the gastrointestinal mucosal appearance in IBD, and each index has its strengths and weaknesses. Although most endoscopic indices do not have a clear-cut validated definition, endoscopic remission or mucosal healing is associated with favorable outcomes, such as a decreased risk of relapse. Therefore, experts suggest utilizing endoscopic indices for monitoring disease activity and optimizing treatment to achieve remission. However, the regular monitoring of endoscopic activity is limited in practice owing to several factors, such as the complexity of the procedure, time consumption, inter-observer variability, and lack of a clear-cut, validated definition of endoscopic response or remission. Although experts have recently suggested consensus-based definitions, further studies are needed to define the values that can predict long-term outcomes.
A Catalogue of Symbiotic Stars

Abstract Mare than 100 symbiotic stars are now known. A catalogue of them, complete to 1984 January 1, is presented. Finding charts are given for all examples, and optical spectra for the majority. A table summarises the observational material at X-ray, ultraviolet, infrared and radio wavelengths.
Micromagnetic simulation with three models of FeCo/L10 FePt exchange-coupled particles for bit-patterned media

Compositing soft and hard materials is a promising method to decrease the coercivity of L10 FePt, which is considered to be a suitable material for bit-patterned media. This paper reports the simulation of three models of FeCo/L10 FePt exchange-coupled composite particles for bit patterned media by the OOMMF micromagnetic simulation software: the enclosed model, the side-enclosed model, and the top-covered model. All of them have the same volumes of the soft and hard parts but different shapes. Simulation results show that the switching fields for the three models can be reduced to about 10 kOe (1 Oe = 79.5775 A/m) and the factor gain can be improved to 1.4 when the interface exchange coefficient has a proper value. Compared to the other models, the enclosed model has a wider range of interface exchange coefficient values, in which a low switching field and high gain can be obtained. The dependence of the switching fields on the angle of the applied field shows that none of the three models are easily affected by the stray field of a magnetic head.
Some applications of matching theorems

This thesis contains the results of two investigations. The first concerns the 1factorizability of regular graphs of high degree. Chetwynd and Hilton proved in 1989 that all regular graphs of order 2n and degree 2nλ where λ > 1 2 ( √ 7− 1) ≈ 0.82288 are 1-factorizable. We show that all regular graphs of order 2n and degree 2nλ where λ is greater than the second largest root of 4x − 28x − 71x + 54x + 88x − 62x+ 3 (≈ 0.81112) are 1-factorizable. It is hoped that in the future our techniques will yield further improvements to this bound. In addition our study of barriers in graphs of high minimum degree may have independent applications. The second investigation concerns partial latin squares that satisfy Hall’s Condition. The problem of completing a partial latin square can be viewed as a listcolouring problem in a natural way. Hall’s Condition is a necessary condition for such a problem to have a solution. We show that for certain classes of partial latin square, Hall’s Condition is both necessary and sufficient, generalizing theorems of Hilton and Johnson, and Bobga and Johnson. It is well-known that the problem of deciding whether a partial latin square is completable is NP-complete. We show that the problem of deciding whether a partial latin square that is promised to satisfy Hall’s Condition is completable is NP-hard.
Cosmological tests of general relativity

Understanding the apparent accelerating expansion rate of the universe is a challenge for modern cosmology. One category of explanations is that we are using the wrong gravitational physics to study the observations. Our paradigmatic theory of gravity – Einstein’s theory of General Relativity – may be subsumed by a larger theory. This thesis develops a selection of tools for testing General Relativity and the numerous alternative theories of gravity that have been put forward. I advocate that an elegant and efficient way to test this space of theories is through the use of parameterized frameworks. Inspired by the Parameterized Post-Newtonian framework I develop a new formalism, the Parameterized Post-Friedmann formalism, that aims to unify the linear cosmological perturbation theory of many alternatives to General Relativity. Having introduced the Parameterized Post-Friedmann formalism and demonstrated its application via a suite of examples, I examine several issues surrounding parameterized tests of gravity. I first consider how the structure of a parameterization can influence the constraints obtainable from a given set of data. I then consider how to describe the growth of the large-scale structure of the universe in a parameterized manner. This leads to a convenient tool for calculating corrections to the growth rate of structure in modified theories, which can be used both with the Parameterized Post-Friedmann formalism or independently of it. I present forecasts for how well generalized deviations from General Relativity will be constrained by the next generation of galaxy surveys. Throughout, this thesis aims to take a synoptic approach to theories of modified gravity, rather than focussing on specific models. A question yet to be answered is whether this approach is realistic in practical terms. The final part of this thesis takes the first steps towards an answer.
Wavelet PID and Wavenet PID: Theory and Applications

We introduce in this chapter a new area in PID controllers, which is called multiresolution PID (MRPID). Basically, a MRPID controller uses wavelet theory for the decomposition of the tracking error signal. We present a general error function in terms of partial errors which gives us the various frequencies appearing in the general errors. Once we obtain the spectrum of the error signal, we divide the error at frequencies that are weighted by gains proposed by the designer. We can say that the MRPID is a generalization of conventional PID controller in the sense that the error decomposition is not only limited to three terms.
Uncovering road traffic crashes typologies using multiple correspondence analysis in low-resource settings

: The main focus of this study was to investigate self-reported road traffic crashes (RTC) among drivers from Loja, Ecuador, and to illustrate the applicability of multiple correspondence analysis (MCA) in detecting and representing typologies of individuals who have experienced an RTC as well as the typology of RTC events, upon information collected through a web-based survey carried in 2021. Overall, 754 drivers were investigated, and we estimated a life prevalence (LP) of RTC of 41.5% (95% CI 36.9 to 46.2). The typology of drivers who reported involvement in an RTC is characterized by a predominance of people between 25 to 40 years of age, who drive mainly cars and frequently
Soundscape quality in suburban green areas and city parks.

According to guidelines proposed in Sweden, at least 80% of the visitors in quiet areas should perceive the sound environment as good. This was the starting point for a questionnaire study on "soundscape quality" in four suburban green areas and in four city parks. The soundscapes in the suburban areas were completely dominated by sounds from nature (e.g., bird song and sounds from water), whereas traffic noise was a main component of the city-park soundscapes. Measured equivalent sound levels (from all sources) ranged from 42 to 50 dBA in the suburban green areas, and from 49 to 60 dBA in the city parks (L Aeq,15min ). "Soundscape quality" was assessed by a five-point bipolar category scale. Among the respondents, 84-100% in the suburban green areas and 53-65% in the city parks assessed the soundscape as "Good" or "Very good". Thus, all suburban green areas but none of the city parks reached the stipulated goal (at least 80%). The soundcape quality was confirmed by attribute profiling using a set of 12 adjectives. Based on the visitor's responses, it is concluded that good soundscape quality can only be achieved if the traffic noise exposure in suburban green areas and city parks during day time is below 50 dBA.
Ferromagnetic resonant tunneling diodes as spin polarimeters

A method for measuring the degree of spin polarization of magnetic materials based on spin-dependent resonant tunneling is proposed. The device we consider is a ballistic double-barrier resonant structure consisting of a ferromagnetic layer embedded between two insulating barriers. A simple procedure, based on a detailed analysis of the differential conductance, allows one to accurately determine the polarization of the ferromagnet. The spin-filtering character of such a system is furthermore addressed. We show that a 100% spin selectivity can be achieved under appropriate conditions. This approach is believed to be well suited for the investigation of diluted magnetic semiconductor heterostructures.
Stochastic processes and functional analysis : in celebration of M.M. Rao's 65th birthday

Some problems of real and stochastic analysis arising from applications quasi-periodic solutions of Hamiltonian evolution equations scaling limits for lattice gas models multivariate distributions with Gaussian conditional structure the minimal projection from L1 onto Pi-n proofs and proofs of the Eckart-Young theorem an analytic semigroup associated to a degenerate evolution equation degenerate nonlinear parabolic problems - the influence of probability theory an application of measure theory to perfect competition dilations of Hilbert-Schmidt class operator-valued measures and applications transient solution of the M/M/1 queueing system via randomization a characterization of Hida measure new results in the simplex method in linear programming an estimate of the semi stable measure of small balls in Banach spaces nonsquare constants of Orlicz spaces recursive multiple Wiener expansion for nonlinear filtering of diffusion processes a Berry-Esseen type estimate for Hilbert space valued U-statistics and on Bootstrapping Von Mises statistics on the strong form of the Faber theorem nonlinear filtering theory for stochastic reaction-diffusion equations an operator characterization of oscillatory harmonizable processes operator algebraic aspects for sufficiency nonlinear parabolic equations, Favard classes and regularity.
Linking number obstructions to satellite homomorphisms

We prove that satellite operations that satisfy a certain positivity condition and have winding number other than one are not homomorphisms. The argument uses the $d$-invariants of branched covers. In the process, we prove a technical result relating $d$-invariants and the Torelli group which may be of independent interest.
Modelling non-reinforced preferences using selective attention

How can artificial agents learn non-reinforced preferences to continuously adapt their behaviour to a changing environment? We decompose this question into two challenges: ($i$) encoding diverse memories and ($ii$) selectively attending to these for preference formation. Our proposed \emph{no}n-\emph{re}inforced preference learning mechanism using selective attention, \textsc{Nore}, addresses both by leveraging the agent's world model to collect a diverse set of experiences which are interleaved with imagined roll-outs to encode memories. These memories are selectively attended to, using attention and gating blocks, to update agent's preferences. We validate \textsc{Nore} in a modified OpenAI Gym FrozenLake environment (without any external signal) with and without volatility under a fixed model of the environment -- and compare its behaviour to \textsc{Pepper}, a Hebbian preference learning mechanism. We demonstrate that \textsc{Nore} provides a straightforward framework to induce exploratory preferences in the absence of external signals.