Embedding-based Scientific Literature Discovery in a Text Editor Application

Each claim in a research paper requires all relevant prior knowledge to be discovered, assimilated, and appropriately cited. However, despite the availability of powerful search engines and sophisticated text editing software, discovering relevant papers and integrating the knowledge into a manuscript remain complex tasks associated with high cognitive load. To define comprehensive search queries requires strong motivation from authors, irrespective of their familiarity with the research field. Moreover, switching between independent applications for literature discovery, bibliography management, reading papers, and writing text burdens authors further and interrupts their creative process. Here, we present a web application that combines text editing and literature discovery in an interactive user interface. The application is equipped with a search engine that couples Boolean keyword filtering with nearest neighbor search over text embeddings, providing a discovery experience tuned to an author's manuscript and his interests. Our application aims to take a step towards more enjoyable and effortless academic writing. The demo of the application (https://SciEditorDemo2020.herokuapp.com/) and a short video tutorial (https://youtu.be/pkdVU60IcRc) are available online

On the generating functions of the newly defined generalized hypergeometric functions

In this paper, we have defined new generalizations of some hypergeometric functions and fractional operators with the help of Fox-Wright function. Then, using each of the generalized fractional operators, we derived linear and bilinear generating function relations for these functions. Finally, we have shown that the newly defined hypergeometric functions and fractional operators can be reduced to functions and operators presented in many studies in the literature by giving special values for their parameters.Publisher's Versio

The volume fraction of brain ventricles to total brain volume: a computed tomography stereological study

This study has been designed to estimate the volume fraction of the brain ventricles volume to total brain volume and to correlate them with gender and age in normal subjects. Cranial computed tomography (CT) images of 80 normally evaluated subjects (five female and five male for each decade) were selected from 1,073 CT examinations. The volumes of total brain, cerebral aqueduct, fourth, third, and lateral ventricles and their ratios were estimated using the Cavalieri method and volume fraction-stereological methods. The ratio of total brain ventricle volume to total brain volume was comparable between the two genders (p > 0.05, independent t test). Mean volume fraction of total ventricle volume to total brain volume was found to be 1.21% in the first and 3.37% in the last decades. Mean volume fraction was found to increase significantly with age (p < 0.01, r = 0.630, Pearson). In conclusion, the mean percentage of total ventricle volume within the total brain volume was found to be 2%. We demonstrated the volume fraction of total ventricle to total brain in normal subjects. Total ventricle volume to total brain volume fractions can be important tools in determining ventricle volumes, which denote variability in some diseases (Alzheimer, schizophrenia, neurodegenerative disorders, etc.) and can be estimated by stereological methods. (Folia Morphol 2010; 69, 4: 193-200

Modelling and Configuration Control of Wing-Shaped Bi-Stable Piezoelectric Composites Under Aerodynamic Loads

Bi-stable composites have been considered for morphing applications thanks to their ability to hold two statically stable shapes with no energy consumption. In this paper, the modelling of the dynamic response of cantilevered wing-shaped bi-stable composites is presented. To this end, an analytical model approximating the dynamic response about each statically stable shape of wing-shaped bi-stable composites is derived. Theoretical modal properties are obtained to attain or stabilise a desired configuration following a previously introduced resonant control strategy. The resonant control technique is evaluated for a wing-shaped bi-stable composite subject to aerodynamic loads. Wind tunnel experiments are conducted on a wing-shaped specimen showing the ability of the control strategy to stabilise or attain a desired stable shape under aerodynamic loads

Optimization Based Tumor Classification from Microarray Gene Expression Data

An important use of data obtained from microarray measurements is the classification of tumor types with respect to genes that are either up or down regulated in specific cancer types. A number of algorithms have been proposed to obtain such classifications. These algorithms usually require parameter optimization to obtain accurate results depending on the type of data. Additionally, it is highly critical to find an optimal set of markers among those up or down regulated genes that can be clinically utilized to build assays for the diagnosis or to follow progression of specific cancer types. In this paper, we employ a mixed integer programming based classification algorithm named hyper-box enclosure method (HBE) for the classification of some cancer types with a minimal set of predictor genes. This optimization based method which is a user friendly and efficient classifier may allow the clinicians to diagnose and follow progression of certain cancer types.We apply HBE algorithm to some well known data sets such as leukemia, prostate cancer, diffuse large B-cell lymphoma (DLBCL), small round blue cell tumors (SRBCT) to find some predictor genes that can be utilized for diagnosis and prognosis in a robust manner with a high accuracy. Our approach does not require any modification or parameter optimization for each data set. Additionally, information gain attribute evaluator, relief attribute evaluator and correlation-based feature selection methods are employed for the gene selection. The results are compared with those from other studies and biological roles of selected genes in corresponding cancer type are described.The performance of our algorithm overall was better than the other algorithms reported in the literature and classifiers found in WEKA data-mining package. Since it does not require a parameter optimization and it performs consistently very high prediction rate on different type of data sets, HBE method is an effective and consistent tool for cancer type prediction with a small number of gene markers

The Effect of Noise on the Response of a Vertical Cantilever Beam Energy Harvester

An energy harvesting concept has been proposed comprising a piezoelectric patch on a vertical cantilever beam with a tip mass. The cantilever beam is excited in the transverse direction at its base. This device is highly nonlinear with two potential wells for large tip masses, when the beam is buckled. For the pre-buckled case considered here, the stiffness is low and hence the displacement response is large, leading to multiple solutions to harmonic excitation that are exploited in the harvesting device. To maximise the energy harvested in systems with multiple solutions the higher amplitude response should be preferred. This paper investigates the amplitude of random noise excitation where the harvester is unable to sustain the high amplitude solution, and at some point will jump to the low amplitude solution. The investigation is performed on a validated model of the harvester and the effect is demonstrated experimentally

Virtual reality as a tool for political decision-making? An empirical study on the power of immersive images on voting behavior

One of the strengths of virtual reality (VR) is to provide a highly realistic user experience. How would VR's power of realism affect political decision-making, for example, when experienced by citizens before they cast their vote on an issue? We set out to empirically assess if and how voting information presented in VR would influence people's voting behavior, compared to the traditional text presentation format. In a 2 (format: text vs. VR) × 2 (argumentation: pro vs. con) between-subject factorial experiment, we assessed participants' voting behavior on a fictitious popular initiative. We first asked all participants (N = 179) to cast their vote based on a brief text, inspired by the traditional Swiss voting booklet (baseline). We then randomly assigned participants to one of four experimental conditions containing the same pro or con arguments concerning the voting issue. Participants could then adjust their previously-cast vote. This was followed by retrospective interviews (N = 32) to gain deeper insights into the decision-making process of the participants. Our study shows that the presentation format has a reinforcing effect, that is, leading to more YES votes for the VR group, and fewer YES votes for the text group. Irrespective of the pro or con arguments, participants show an overall increase in YES votes in VR, which is not the case for the text group. We identified six factors that may have led to this positive change with VR: (1) the affirmative power of images, (2) the vividness of immersive images, (3) first-person storytelling and storyliving, (4) the greater affordances of VR for engagement through interaction, (5) the design of the VR environment, and (6) the novelty of the VR technology

Cytotoxic Potential of Rare Plant Salvia candidissima subsp. candidissima on Breast Cancer Cells

© 2023 The Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC), https://creativecommons.org/licenses/by-nc/4.0/Breast cancer is the leading cause of cancer-related deaths in women throughout the world. Research on natural anti-cancer products from plants has gained traction. Salvia L. species and their derivatives are rare in Turkey and have suggested for their potential anti-cancer effects. The aim of this study is to assess the potential cytotoxic/apoptotic activities of methanol extract of Salvia candidissima Vahl. subsp. candidissima (SCE) on MCF-7 and MDA-MB-231 breast cancer cells. A GCxGC-TOF/MS system and a dual stage commercial thermal desorption injector were used to determine the chemical components of SCE. MTT and ATP viability tests were used to investigate the anti-growth activity. The apoptosis-inducing effect was assessed using a fluorescence staining method. Caspase-cleaved keratin 18 (ccK18, M30-antigen) levels measured by M30-CytoDeath ELISA Kit. The results showed that SCE suppressed the survival of the MCF-7 and MDA-MB-231 breast cancer cells in a dose-dependent manner, based on the findings of both MTT and ATP cell viability tests and pyknotic cell nuclei were observed via fluorescent staining in both cell lines after 48 h of treatment. The treatment group had greater levels of caspase-cleaved keratin 18 in the MCF-7 cells than the untreated group. These results showed that SCE triggers apoptosis, causes cell death in MCF-7 and MDA-MB-231 cell lines. SCE may become promising therapeutic strategy in the treatment of breast cancer with further in vitro and in vivo studies.Peer reviewe

Structural and magnetic properties of Co-V nanoparticles

We have investigated the structural and magnetic properties of Co1-xVx nanoparticles (NPs) with composition x = 0.25 (stoichiometric) and 0.29 (under-stoichiometric) prepared by the cluster-beam deposition (CBD) technique. Our data shows that the as-made Co1-xVx NPs are a mixture of the high-temperature phase (HTP) and the low-temperature phase (LTP) of Co3V and the particles are superparamagnetic at room temperature (RT) with blocking temperatures (TB) of 90 and 137 K for x = 0.25 and 0.29, respectively. This behavior contrasts with the bulk which are paramagnetic down to 4.2 K. When the Co75V25 NPs are annealed at 573 K, they undergo a phase separation into a mixture of phases and become ferromagnetic at room temperature with Curie temperature (Tc) of 515 K