Miracle-dz/UniFAR-FTUs huggingface dataset:
Exact learning of tree patterns

Tree patterns are natural candidates for representing rules and hypotheses in many tasks such as information extraction and symbolic mathematics. A tree pattern is a tree with labeled nodes where some of the leaves may be labeled with variables, whereas a tree instance has no variables. A tree pattern matches an instance if there is a consistent substitution for the variables that allows a mapping of subtrees to matching subtrees of the instance. A finite union of tree patterns is called a forest. In this thesis, we study the learnability of tree patterns from queries when the subtrees are ordered or unordered. The learnability is determined by the semantics of matching as defined by the types of mappings from the pattern subtrees to the instance subtrees. Angluin's exact supervised learning model is used, in which the learner has to exactly identify the target from a polynomial number of queries and in polynomial time. We first show that ordered tree patterns and forests, with an infinite label alphabet (or equivalent condition), are learnable from equivalence and membership queries. Ordered forests and similar classes with bounded alphabet and branching factor are shown to be as hard to learn as DNF. We next show that unordered tree patterns and forests are not exactly learnable from equivalence and subset queries when the mapping between subtrees is one-to-one onto, regardless of the computational power of the learner. On the other hand, tree and forest patterns are learnable from equivalence and membership queries for the one-to-one into mapping. Finally, we connect the problem of learning tree patterns to inductive logic programming by describing a class of tree patterns called “clausal trees” that includes non-recursive single-predicate Horn clauses and show that this class is learnable from equivalence and membership queries.
Keep Hypoxia-Inducible Factor α and Stay Cool

Hypoxia-inducible factor 2α (HIF2α)-dependent thermogenic regulation upon temperature changes. Upon cold exposure, HIF2α is stabilized and fine-tunes thermogenic activity via PKA Cα (protein kinase A catalytic subunit α) regulation. HIF2α also coordinates beige adipocyte plasticity to actively respond to temperature shift.
Epigenetic modulation of visceral nociception

Epigenetics is a process that alters gene activity or phenotype without any changes in the underlying DNA sequence or genotype. These biological changes may have deleterious effects and can lead to various human diseases. Ongoing research is continuing to illuminate the role of epigenetics in a variety of pathophysiologic processes. Several categories of epigenetic mechanisms have been studied including chromatin remodeling, DNA methylation, histone modification, and non‐coding RNA mechanisms. These epigenetic changes can have a long‐term effect on gene expression without any underlying changes in the DNA sequences. The underlying pathophysiology of disorders of brain‐gut interaction and stress‐induced visceral pain are not fully understood and the role of epigenetic mechanisms in these disorders are starting to be better understood. Current work is underway to determine how epigenetics plays a role in the neurobiology of patients with chronic visceral pain and heightened visceral nociception. More recently, both animal models and human studies have shown how epigenetic regulation modulates stress‐induced visceral pain. While much more work is needed to fully delineate the mechanistic role of epigenetics in the neurobiology of chronic visceral nociception, the current study by Louwies et al., in Neurogastroenterology and Motility provides additional evidence supporting the involvement of epigenetic alterations in the central nucleus of the amygdala in stress‐induced visceral hypersensitivity in rodents.
Assembly of complex 3D structures and electronics on curved surfaces

Electronic devices with engineered three-dimensional (3D) architectures are indispensable for frictional-force sensing, wide-field optical imaging, and flow velocity measurement. Recent advances in mechanically guided assembly established deterministic routes to 3D structures in high-performance materials, through controlled rolling/folding/buckling deformations. The resulting 3D structures are, however, mostly formed on planar substrates and cannot be transferred directly onto another curved substrate. Here, we introduce an ordered assembly strategy to allow transformation of 2D thin films into sophisticated 3D structures on diverse curved surfaces. The strategy leverages predefined mechanical loadings that deform curved elastomer substrates into flat/cylindrical configurations, followed by an additional uniaxial/biaxial prestretch to drive buckling-guided assembly. Release of predefined loadings results in an ordered assembly that can be accurately captured by mechanics modeling, as illustrated by dozens of complex 3D structures assembled on curved substrates. Demonstrated applications include tunable dipole antennas, flow sensors inside a tube, and integrated electronic systems capable of conformal integration with the heart.
The Role of Fit in the Decision Making Process for Head Principal Recruitment, Hiring, and Placement

The purpose of this study was to examine the role that fit may play in recruiting, hiring, and placing head principals, both from the perspective of the principals and from the perspective of the hiring bodies. District personnel, particularly superintendents and human resource directors, have been surveyed in previous research to ascertain general traits they look for in a head principal candidate (Kwan, 2012; Kwan & Walker, 2009; Pijanowski, Hewitt, & Brady, 2009). Little research exists, however, gathering in-depth qualitative data on the role of fit in the principal placement process. Data were collected from ten principals in the first 3 years of their current placement as head principal and 6 district personnel (superintendents and human resource directors) responsible for hiring and placing head principals. The data were analyzed, and three themes emerged: the applicant, the school, and the relationships. Data indicated that both principals and those responsible for hiring and placing them gave significant consideration to the fit, or match, between a candidate for a head principal position and the school environment itself. While these considerations affected the final decisions regarding principal placement for district personnel, principals indicated a trust in and support for decisions about placement made by district personnel, even when they did not perceive a positive fit. The findings from this study will likely benefit candidates for head principal positions and district personnel who recruit, hire, and place them. The findings also add to the body of knowledge on fit and support the theoretical frame used to examine the
Accelerated shelf life modeling of appearance change in drug products using ASAPprime ®

Abstract An accelerated stability model approach was demonstrated to accurately predict the long-term shelf life of example drug substances and drug products (indigo carmine tablets and L-ascorbic acid powder) where appearance changes were shelf life–limiting. The products were exposed outside of packaging to conditions from 50 to 90 °C and 0–80% relative humidity for up to one month to accelerate appearance changes. The appearance changes of stressed samples were quantitated using the CIELAB color scale (calculated ΔE*), where a visual assessment of appearance changes likely to be noticeable was used to assign a ΔE* specification limit. ASAPprime ® software was employed to create an isoconversion paradigm, modeled in packaging by the moisture-modified Arrhenius equation, that predicted the color changes of the products within the error bars of the model to nine months at 25 °C/60% RH, 30 °C/65% RH, and 40 °C/75% RH. Overall, these case studies indicate that the ASAPprime ® approach for accelerated stability studies are a fast, accurate approach to modeling appearance changes.
Stakeholder perspectives on a patient-centred intervention (DIALOG+) for adolescents with common mental disorders in Colombia: A qualitative study

Background Patient and stakeholders’ involvement in the development of mental health interventions is a central part of the research process as end-user’s input can improve the design of patient-centered interventions. This is particularly important when developing interventions directed towards improving the mental health of children and adolescents. The rising prevalence of mental health disorders in this population requires special attention and the development of interventions that include them as active participants is crucial. Objective Our aim is to explore the perspectives and opinions of adolescents, parents, educators/youth workers, and clinicians regarding the appeal and usability of an existing patient-centered digital intervention (DIALOG+), which aims to improve quality of life. Methods As part of a broader study aiming to adapt and test DIALOG+, we conducted Online Focus Groups (OFGs) with adults and adolescents in two cities in Colombia. The existing DIALOG+ intervention was introduced to participants, followed by a structured discussion regarding the opinions and views of stakeholders. A framework approach was used to identify the main themes followed by content analysis to aid adaptation. Results We conducted 10 OFGs with a total of 45 participants. A positive feature highlighted by all groups was the innovation of including a digital intervention in a traditional medical visit. Additionally, participants considered that the active role that adolescents have when using the intervention empowers them. Barriers identified included concerns from clinicians related to the time required during consultations and confusion with terminology. Furthermore, additional domains that are particularly relevant for the adolescent population were suggested. Conclusions Data obtained suggest that overall, the DIALOG+ intervention and supporting app are seen as innovative and appealing to adolescents as well as adult stakeholders. However, concerns raised about the availability of time to apply the intervention, the app interface and the language and terminology require modification.
C*-pseudo-multiplicative unitaries, Hopf C*-bimodules and their Fourier algebras

Abstract We introduce C*-pseudo-multiplicative unitaries and concrete Hopf C*-bimodules for the study of quantum groupoids in the setting of C*-algebras. These unitaries and Hopf C*-bimodules generalize multiplicative unitaries and Hopf C*-algebras and are analogues of the pseudo-multiplicative unitaries and Hopf–von Neumann-bimodules studied by Enock, Lesieur and Vallin. To each C*-pseudo-multiplicative unitary, we associate two Fourier algebras with a duality pairing and in the regular case two Hopf C*-bimodules. The theory is illustrated by examples related to locally compact Hausdorff groupoids. In particular, we obtain a continuous Fourier algebra for a locally compact Hausdorff groupoid.
Design framework for multivariable ILC : (de)centralized design & modeling considerations

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On the Deep Learning Models for EEG-Based Brain-Computer Interface Using Motor Imagery

Motor imagery (MI) based brain-computer interface (BCI) is an important BCI paradigm which requires powerful classifiers. Recent development of deep learning technology has prompted considerable interest in using deep learning for classification and resulted in multiple models. Finding the best performing models among them would be beneficial for designing better BCI systems and classifiers going forward. However, it is difficult to directly compare performance of various models through the original publications, since the datasets used to test the models are different from each other, too small, or even not publicly available. In this work, we selected five MI-EEG deep classification models proposed recently: EEGNet, Shallow & Deep ConvNet, MB3D and ParaAtt, and tested them on two large, publicly available, databases with 42 and 62 human subjects. Our results show that the models performed similarly on one dataset while EEGNet performed the best on the second with a relatively small training cost using the parameters that we evaluated.
Reactive Architecture, Augmented Textiles, Domotics and Soft Architecture Fabrication: On Electronic and Reactive Textiles in Domestic Contexts

Abstract The present paper interrogates the status and the role of electronic and reactive textiles in domestic contexts. After a preliminary incursion into the modern definition of home and homing, the paper addresses the changes that took place in the domestic space due to the development of digital and communication technologies. Defined as a “sensing home,” as a “communicating domestic space,” smart homes are challenging the traditional understanding of home, defined in terms of intimacy and privacy. In this context, electronic and reactive textiles are asked to overcome the low acceptance of smart homes, through their technical, sensorial, and cultural dimensions. The paper highlights some of the pros and cons in accommodating the latest technological advances in the field of textiles, analyses the way physical computing allows textiles to transform into domotics (robots for domestic environments), presents some of the latest developments on soft architecture fabrication and argues in favor of a much more critical approach to the development of sensors and actuators in textile objects.
Exploring mutation specific beta blocker pharmacology of the pathogenic late sodium channel current from patient-specific pluripotent stem cell myocytes derived from long QT syndrome mutation carriers

ABSTRACT The congenital long QT syndrome (LQTS), one of the most common cardiac channelopathies, is characterized by delayed ventricular repolarization underlying prolongation of the QT interval of the surface electrocardiogram. LQTS is caused by mutations in genes coding for cardiac ion channels or ion channel-associated proteins. The major therapeutic approach to LQTS management is beta blocker therapy which has been shown to be effective in treatment of LQTS variants caused by mutations in K+ channels. However, this approach has been questioned in the treatment of patients identified as LQTS variant 3(LQT3) patients who carry mutations in SCN5A, the gene coding for the principal cardiac Na+ channel. LQT3 mutations are gain of function mutations that disrupt spontaneous Na+ channel inactivation and promote persistent or late Na+ channel current (INaL) that delays repolarization and underlies QT prolongation. Clinical investigation of patients with the two most common LQT3 mutations, the ΔKPQ and the E1784K mutations, found beta blocker treatment a useful therapeutic approach for managing arrhythmias in this patient population. However, there is little experimental data that reveals the mechanisms underlying these antiarrhythmic actions. Here, we have investigated the effects of the beta blocker propranolol on INaL expressed by ΔKPQ and E1784K channels in induced pluripotent stem cells derived from patients carrying these mutations. Our results indicate that propranolol preferentially inhibits INaL expressed by these channels suggesting that the protective effects of propranolol in treating LQT3 patients is due in part to modulation of INaL.
Critical insight into recombinase polymerase amplification technology

ABSTRACT Introduction Recombinase polymerase amplification (RPA) is a promising and emerging technology for rapidly amplifying target nucleic acid from minimally processed samples and through small portable instruments. RPA is suitable for point-of-care testing (POCT) and on-site field testing, and it is compatible with microfluidic devices. Several detection assays have been developed, but limited research has dug deeper into the chemistry of RPA to understand its kinetics and fix its shortcomings. Areas covered This review provides a detailed introduction of RPA molecular mechanism, kits formats, optimization, application, pros, and cons. Moreover, this critical review discusses the nonspecificity issue of RPA, highlights its consequences, and emphasizes the need for more research to resolve it. This review discusses the reaction kinetics of RPA in relation to target length, product quantity, and sensitivity. This critical review also questions the novelty of recombinase-aided amplification (RAA). In short, this review discusses many aspects of RPA technology that have not been discussed previously and provides a deeper insight and new perspectives of the technology. Expert opinion RPA is an excellent choice for pathogen detection, especially in low-resource settings. It has a potential to replace PCR for all purposes, provided its shortcomings are fixed and its reagent accessibility is improved.
Application of palaeogenetic techniques to historic mollusc shells reveals phylogeographic structure in a New Zealand abalone

Natural history collections worldwide contain a plethora of mollusc shells. Recent studies have detailed the sequencing of DNA extracted from shells up to thousands of years old and from various taphonomic and preservational contexts. However, previous approaches have largely addressed methodological rather than evolutionary research questions. Here, we report the generation of DNA sequence data from mollusc shells using such techniques, applied to Haliotis virginea Gmelin, 1791, a New Zealand abalone, in which morphological variation has led to the recognition of several forms and subspecies. We successfully recovered near‐complete mitogenomes from 22 specimens including 12 dry‐preserved shells up to 60 years old. We used a combination of palaeogenetic techniques that have not previously been applied to shell, including DNA extraction optimized for ultra‐short fragments and hybridization‐capture of single‐stranded DNA libraries. Phylogenetic analyses revealed three major, well‐supported clades comprising samples from: (1) The Three Kings Islands; (2) the Auckland, Chatham and Antipodes Islands; and (3) mainland New Zealand and Campbell Island. This phylogeographic structure does not correspond to the currently recognized forms. Critically, our nonreliance on freshly collected or ethanol‐preserved samples enabled inclusion of topotypes of all recognized subspecies as well as additional difficult‐to‐sample populations. Broader application of these comparatively cost‐effective and reliable methods to modern, historical, archaeological and palaeontological shell samples has the potential to revolutionize invertebrate genetic research.
Personal dosimetry for positron emitters, and occupational exposures from clinical use of gallium-68

The current status and issues regarding positron dosimetry in nuclear medicine are summarized. The suitability of the United Kingdom Health Security Agency extremity and eye beta-gamma personal thermoluminescence dosemeters are then considered. Monte Carlo modelling is performed to determine their responses and derive sets of calibration factors, along with H p(0.07) and H p(3) conversion coefficients, for carbon-11, nitrogen-13, oxygen-15, fluorine-18 and gallium-68 sources, which are commonly used in positron emission tomography (PET) computed tomography; data for these isotopes is assumed extrapolatable to other positron sources. It is found that the dosemeters are adequate for assessing exposures to PET radionuclides, even if their routine calibrations to caesium-137 were maintained. An idealized set of measurements representing gallium-68 exposure scenarios is then described, including reproducible mock-ups of individuals manipulating vials and syringes. Finally, a short case-study is presented that explores occupational doses during routine clinical use of gallium-68. The extremity dosemeter results demonstrated significant variations dependent upon the exposure conditions, with some seen to be comparatively large; whole-body and eye dose rates per activity were found to be lower. The importance of routine dose monitoring of workers is emphasized, with the need for a longer-termed follow-up study demonstrated.
A density-based matrix transformation clustering method for electrical load

Feature extraction of electrical load plays a vital role in providing a reliable basis and guidance for power companies. In this paper, we propose a novel clustering algorithm named the Density-based Matrix Transformation (DBMT) Clustering method to extract features (peaks, valleys and trends) of electrical load curves. The main objective of the algorithm is to reorder the data items until the data items belonging to the same cluster are organized together; that is, the adjacent matrix is rearranged to the type of block diagonal. This method adaptively determines the number of clusters and filters out noise without input global parameters. Moreover, for the specific characteristics of raw electrical load data, we propose a variant of Dynamic Time Warp (DTW) distance, dsDTW, which aligns the peaks, valleys and trends of load curves meanwhile dealing with missing values in different situations. After feeding the dsDTW adjacent matrix to DBMT, the results indicate that our proposal can accurately extract the feature of the load curves compared to different clustering methods.
Prognostic significance of TG/HDL-C and non-HDL-C/HDL-C ratios in patients with non-small cell lung cancer: a retrospective study

Objective Lung cancer is a malignancy with high a mortality rate that threatens human health. This study is aimed to explore the correlation among the triglyceride/high-density lipoprotein ratio (TG/HDL-C), non-high-density lipoprotein/high-density lipoprotein ratio (non-HDL-C/HDL-C) and survival of patients with non-small cell lung cancer (NSCLC) undergoing video-associated thoracic surgery (VATS). Methods This retrospective study analyzed 284 patients with NSCLC who underwent VATS at Hebei General Hospital, Shijiazhuang, China. The time-dependent receiver operating characteristic curve was used to determine the optimal cutoff value and evaluate the area under the curve. Kaplan–Meier and Cox regression analyses were performed to determine the prognostic effect. Results The median overall survival (OS) was 46 months. Patients with low TG/HDL-C and low non-HDL-C/HDL-C had a longer OS. The low non-HDL-C/HDL-C group showed a longer mean survival time (59.00 vs. 52.35 months). Multivariate analysis revealed that TG/HDL-C and non-HDL-C/HDL-C were significantly correlated with OS. Conclusions TG/HDL-C and non-HDL-C/HDL-C are associated with the prognosis of patients with NSCLC who received VATS. Preoperative serum TG/HDL-C and non-HDL-C/HDL-C may be effective independent prognostic factors for predicting the outcomes of patients with NSCLC.