101,857 research outputs found
Borderline shades: Morphometric features predict borderline personality traits but not histrionic traits
No full text: Borderline personality disorder (BPD) is one of the most diagnosed disorders in clinical settings. Besides the fully diagnosed disorder, borderline personality traits (BPT) are quite common in the general population. Prior studies have investigated the neural correlates of BPD but not of BPT. This paper investigates the neural correlates of BPT in a subclinical population using a supervised machine learning method known as Kernel Ridge Regression (KRR) to build predictive models. Additionally, we want to determine whether the same brain areas involved in BPD are also involved in subclinical BPT. Recent attempts to characterize the specific role of resting state-derived macro networks in BPD have highlighted the role of the default mode network. However, it is not known if this extends to the subclinical population. Finally, we wanted to test the hypothesis that the same circuitry that predicts BPT can also predict histrionic personality traits. Histrionic personality is sometimes considered a milder form of BPD, and making a differential diagnosis between the two may be difficult. For the first time KRR was applied to structural images of 135 individuals to predict BPT, based on the whole brain, on a circuit previously found to correctly classify BPD, and on the five macro-networks. At a whole brain level, results show that frontal and parietal regions, as well as the Heschl's area, the thalamus, the cingulum, and the insula, are able to predict borderline traits. BPT predictions increase when considering only the regions limited to the brain circuit derived from a study on BPD, confirming a certain overlap in brain structure between subclinical and clinical samples. Of all the five macro networks, only the DMN successfully predicts BPD, confirming previous observations on its role in the BPD. Histrionic traits could not be predicted by the BPT circuit. The results have implications for the diagnosis of BPD and a dimensional model of personality
Plant Disease Detection and Segmentation using End-to-End YOLOv8: A Comprehensive Approach
No full textPreventing and managing plant leaf diseases requires a dependable and precise detection method. Detecting leaf diseases in plants is a time-consuming process that has a negative impact on productivity and crop quality. By leveraging the PlantVillage and PlantDoc datasets to train the Ultralytics YOLOv8 model from end to end, this research intends to present a deep learning solution to the detection and segmentation of plant leaf disease. The YOLOv8 model, an advancement of the YOLO series, has been designed to increase detection speed without sacrificing accuracy. Its intricate architecture, composed of multiple convolutional layers, enables complex feature extraction from images, leading to precise identification of plant leaf diseases. As the model is trained end-to-end, it can effectively learn and generalize from the input data, thereby enhancing its predictive performance for unseen or novel instances of leaf diseases. The evaluation results for the YOLOv8 approach are validated by prominent statistical metrics like precision, recall, mAP50 and mAP50-95 value, and F1-score, which resulted in 99.8{%}, 99.3%, 99.5%, 96.5% and 0.999 for the bounding box and 99.1%, 99.3%, 99.3%, 98.5% and 0.992 for the segmentation mask respectively. The results demonstrate the model's strong performance in accurately detecting and segmenting diseased regions, as indicated by high precision, recall, and mAP values. These findings highlight the effectiveness of the YOLOv8 model in plant disease detection, showcasing its potential for precision agriculture and crop management applications
Efficacy of a virtual assistance-based lifestyle intervention in reducing risk factors for Type 2 diabetes in young employees in the information technology industry in India: LIMIT, a randomized controlled trial
No full textAims: To investigate a virtual assistance-based lifestyle intervention to reduce risk factors for Type 2 diabetes in young employees in the information technology industry in India.Methods: LIMIT (Lifestyle Modification in Information Technology) was a parallel-group, partially blinded, randomized controlled trial. Employees in the information technology industry with ?3 risk factors (family history of cardiometabolic disease, overweight/obesity, high blood pressure, impaired fasting glucose, hypertriglyceridaemia, high LDL cholesterol and low HDL cholesterol) from two industries were randomized to a control or an intervention (1:1) group. After initial lifestyle advice, the intervention group additionally received reinforcement through mobile phone messages (three per week) and e-mails (two per week) for 1 year. The primary outcome was change in prevalence of overweight/obesity, analysed by intention to treat.Results: Of 437 employees screened (mean age 36.2 ± 9.3 years; 74.8% men), 265 (61.0%) were eligible and randomized into control (n=132) or intervention (n=133) group. After 1 year, the prevalence of overweight/obesity reduced by 6.0% in the intervention group and increased by 6.8% in the control group (risk difference 11.2%; 95% CI 1.2–21.1; P=0.042). There were also significant improvements in lifestyle measurements, waist circumference, and total and LDL cholesterol in the intervention group.The number-needed-to-treat to prevent one case of overweight/obesity in 1 year was 9 (95% CI 5–82), with an incremental cost of INR10665 (£112.30) per case treated/prevented. A total of 98% of participants found the intervention acceptable.Conclusions: A virtual assistance-based lifestyle intervention was effective, cost-effective and acceptable in reducing risk factors for diabetes in young employees in the information technology industry, and is potentially scalabl
Protein-directed dynamic combinatorial chemistry
No full textDynamic combinatorial chemistry (DCC) is a novel approach to medicinal chemistry which integrates the synthesis and screening of small molecule libraries into a single step. The concept uses reversible chemical reactions to present a dynamic library of candidate structures to a template which selects and removes the best binder from equilibrium. Using this evolutionary process with a biopolymer template, such as a protein, leads to the protein directing the synthesis of its own best ligand. Biological DCC applications are extremely challenging since the thermodynamic criterion of reversibility has to be met under physiological conditions to ensure stability of the biomolecular template. The list of reversible reactions satisfying these stringent criteria is limited and is a major constraint on achieving both reaction and structural diversity in adaptive dynamic libraries. This thesis reports the development of a catalysed version of acylhydrazone dynamic libraries which are truly adaptive under protein-friendly conditions. In the presence of aniline as a trans-imination catalyst, acylhydrazone dynamic combinatorial libraries equilibrate rapidly at pH 6.2 and are switched off by an increase in pH. We designed acylhydrazone libraries targeting the enzyme superfamily Glutathione-S-Transferase (GST) using a scaffold aldehyde, 4-chloro-3-nitrobenzaldehyde, which is structurally related to a known GST substrate chlorodinitrobenzene. On interfacing these dynamic libraries with two different GST enzymes (SjGST from the helminth worm Schistosoma japonicum and hGSTP1-1, a human isoform and an important oncology drug target) we observed isoformselective amplification effects with two different acylhydrazones selected by the proteins. To explore the potential of anchoring in our DCC methodology we conjugated the endogenous GST ligand, glutathione (GSH) onto the scaffold chloronitrobenzaldehyde. The GSH recognition motif acts as an anchor and allows us to explore the hydrophobic binding site of the enzyme in a fragment-based approach. The presence of the glutathione moiety led to increased solubility of the library members and a DCC experiment with the enzymes led to the selection of conjugate hydrazones with significant binding ability. Multi-level dynamic libraries use multiple exchange processes in the same system to increase their accessible structural diversity. These exchange reactions may be orthogonal, where the different chemistries can be activated or deactivated independently of each other, or simultaneous, where all the processes are dynamic and crossover under the same conditions. Together, these interacting molecular networks provide an exciting experimental approach to the emerging field of systems chemistry. We demonstrate that two reversible reactions, conjugate addition of thiols to enones and hydrazone formation, are fully compatible and orthogonal to one another in a single dynamic library. Hydrazone exchange takes place at acidic pH, while conjugate addition operates at basic pH. Simple pH change can be used to switch between each process and establish two channels of reactivity
Verifiable Timed Signatures Made Practical
No full textA verifiable timed signature (VTS) scheme allows one to time-lock a signature on a known message for a given amount of time T such that after performing a sequential computation for time T anyone can extract s from the time-lock. Verifiability ensures that anyone can publicly check if a time-lock contains a valid signature on m without solving it first, and that the signature can be obtained by solving the same for time T.
This work formalizes VTS, presents efficient constructions compatible with BLS, Schnorr, and ECDSA signatures, and experimentally demonstrates that (unlike the predecessors) our constructions can be employed in practice. On a technical level, we design an efficient cut-and-choose protocol based on the recently proposed homomorphic time-lock puzzles to prove the validity of a signature encapsulated in a time-lock puzzle. We also present a new efficient range proof protocol that significantly improves upon existing proposals in terms of the proof size, and is of independent interest.
VTS is a versatile tool with numerous existing applications. In this work, we demonstrate VTS’s applicability to resolve three challenging issues in the space of cryptocurrencies. Specifically, we show how VTS is the cryptographic cornerstone to construct:
(i) Payment channel networks with improved on-chain unlinkability of users involved in a transaction,
(ii) multi-party signing of transactions
for cryptocurrencies without any on-chain notion of time and
(iii) cryptocurrency-enabled fair multi-party computation protocol
Measuring industry-science links through inventor-author relations: A profiling method
No full textIn this pilot study we examine the performance of text-based profiling in recovering a set of validated inventor-author links. In a first step we match patents and publications solely based on their similarity in content. Next, we compare inventor and author names on the highest ranked matches for the occurrence of name matches. Finally, we compare these candidate matches with the names listed in a validated set of inventor-author names. Our text-based profile methodology performs significantly better than a random matching of patents and publications, suggesting that text-based profiling is a valuable complementary tool to the name searches used in previous studies.innovation; industry-science links; text-based profiling;
Nonhelical inverse transfer of a decaying turbulent magnetic field
No full textIn the presence of magnetic helicity, inverse transfer from small to large scales is well known in magnetohydrodynamic (MHD) turbulence and has applications in astrophysics, cosmology, and fusion plasmas. Using high resolution direct numerical simulations of magnetically dominated self-similarly decaying MHD turbulence, we report a similar inverse transfer even in the absence of magnetic helicity. We compute for the first time spectral energy transfer rates to show that this inverse transfer is about half as strong as with helicity, but in both cases the magnetic gain at large scales results from velocity at similar scales interacting with smaller-scale magnetic fields. This suggests that both inverse transfers are a consequence of a universal mechanisms for magnetically dominated turbulence. Possible explanations include inverse cascading of the mean squared vector potential associated with local near two-dimensionality and the shallower k^2 subinertial range spectrum of kinetic energy forcing the magnetic field with a k^4 subinertial range to attain larger-scale coherence. The inertial range shows a clear k^{-2} spectrum and is the first example of fully isotropic magnetically dominated MHD turbulence exhibiting weak turbulence scaling
Settling of finite-size particles in isotropically forced, homogeneous turbulence: interface-resolved simulations
No full textWe have simulated the gravity-induced settling of finite-size particles in a turbulent background flow which is forced in a statistically-stationary fashion. The simulations are accurately resolving the solid-fluid interface with the aid of an immersed boundary technique [1]. The parameters of the simulation are (apart from background turbulence) identical to those of reference [2], where particle clustering was observed at a Galileo number of 178 and a solid volume fraction of 0.005. In the present case, it is found that a relative turbulence intensity of 0.24 leads to the disappearance of the clusters; as a consequence, the increase in average particle settling velocity found in [2] also vanishes. [1] M. Uhlmann. An immersed boundary method with direct forcing for the simulation of particulate flows. J. Comput. Phys., 209(2):448–476, 2005. [2] M. Uhlmann and T. Doychev. Sedimentation of a dilute suspension of rigid spheres at intermediate Galileo numbers: the effect of clustering upon the particle motion. J. Fluid Mech., 752:310–348, 2014
Why do they use bhat chew sticks? An experiment to demonstrate the antihyperglycemic activity of Clerodendrum infortunatum Linn.
No full textIntroduction: The rise in blood glucose than the recommended level is called hyperglycemia, mainly caused by diabetes mellitus (DM). DM is in turn a consequence of decreased insulin secretion or action or both. This experiment is intended to evaluate the effect of Clerodendrum infortunatum Linn. (bhat) chew sticks in controlling diabetes in humans. Method: The fasting blood sugar was measured twice with the help of a glucometer. First, all participants were requested to measure their blood sugar on an empty stomach in the morning without using a bhat chew stick. The next morning, their fasting plasma sugar was again accessed after the use of the bhat chew sticks as a toothbrush. The fall in blood sugar value was recorded and the efficiency of the stimulus was tested using student t-test at α level of significance and n-1 degree of freedom. Result: A total of 27 individuals participated in the study and all responded to the stimulus. A fall in blood glucose was observed between 3-59 mg/dL and the response was not found to be significant at 0.05 level of significance. Conclusion: Rural people use chew sticks as toothbrushes and prefer C. infortunatum twigs to control diabetes. The present experiment shows that bhat lowers the blood sugar level in both diabetic and non-diabetic individuals. However, chronic impacts should also be monitored by conducting large-scale studies on humans to establish proper dosage, indications, and side effects of C. infortunatum.
Keywords: Clerodendrum infortunatum, diabetes, hyperglycemia, random blood sugar, chew stick
PSR J1141-6545: A Powerful Laboratory of GR and Tensor-Scalar , Theories of Gravity,
No full textVerbiest J, Bhat NDR, Bailes M. PSR J1141-6545: A Powerful Laboratory of GR and Tensor-Scalar , Theories of Gravity, . In: Damour T, Jantzen RT, Ruffini R, eds. The Twelfth Marcel Grossmann Meeting. Singapore: World Scientific; 2012: 1571-1573
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