An Analysis Scheme for 3D Visualization of Positron Emitting Radioisotopes Using Positron Emission Mammography System

Proton range monitoring and verification is important to enhance the effectiveness of treatment by ensuring that the correct dose is delivered to the correct location. Upon proton irradiation, different positron emitting radioisotopes are produced by the inelastic nuclear interactions of protons with the target elements. Recently, it was reported that the 16O(p,2p2n)13N reaction has a relatively low threshold energy, and it could be potentially used for proton range verification. In the present work, we have proposed an analysis scheme (i.e., algorithm) for the extraction and three-dimensional visualization of positron emitting radioisotopes. The proposed step-by-step analysis scheme was tested using our own experimentally obtained dynamic data from a positron emission mammography (PEM) system (our developed PEMGRAPH system). The experimental irradiation was performed using an azimuthally varying field (AVF) cyclotron with a 80 MeV monoenergetic pencil-like beam. The 3D visualization showed promising results for proton-induced radioisotope distribution. The proposed scheme and developed tools would be useful for the extraction and 3D visualization of positron emitting radioisotopes and in turn for proton range monitoring and verification.

Evaluation of Mei-yu heavy-rainfall quantitative precipitation forecasts in Taiwan by a cloud-resolving model for three seasons of 2012–2014

In this study, the performance of quantitative precipitation forecasts (QPFs) by the Cloud-Resolving Storm Simulator (CReSS) in Taiwan, at a horizontal grid spacing of 2.5 km and a domain size of 1500×1200 km2, in the range of 1–3 d during three Mei-yu seasons (May–June) of 2012–2014 is evaluated using categorical statistics, with an emphasis on heavy-rainfall events (≥100 mm per 24 h). The categorical statistics are chosen because the main hazards are landslides and floods in Taiwan, so predicting heavy rainfall at the correct location is important. The overall threat scores (TSs) of QPFs for all events on day 1 (0–24 h) are 0.18, 0.15, and 0.09 at thresholds of 100, 250, and 500 mm, respectively, and indicate considerable improvements at increased resolution compared to past results and 5 km models (TS < 0.1 at 100 mm and TS ≤ 0.02 at 250 mm). Moreover, the TSs are shown to be higher and the model more skillful in predicting larger events, in agreement with earlier findings for typhoons. After classification based on observed rainfall, the TSs of day − 1 QPFs for the largest 4 % of events by CReSS at 100, 250, and 500 mm (per 24 h) are 0.34, 0.24, and 0.16, respectively, and can reach 0.15 at 250 mm on day 2 (24–48 h) and 130 mm on day 3 (48–72 h). The larger events also exhibit higher probability of detection and lower false alarm ratio than smaller ones almost without exception across all thresholds. With the convection and terrain better resolved, the strength of the model is found to lie mainly in the topographic rainfall in Taiwan rather than migratory events that are more difficult to predict. Our results highlight the crucial importance of cloud-resolving capability and the size of fine mesh for heavy-rainfall QPFs in Taiwan.

Intelligent POIs Recommender System Based on Time Series Analysis with Seasonal Adjustment

Recommender systems have been applied on a variety of applications including movies, music, news, books, research articles, search queries, and travel information. Instead of searching travel information from the extremely huge amount of travel data, a personalized travel recommender system is desired. However, an inappropriate travel recommendation may result from a wrong season, even if it is already a correct location. The current recommender systems from time to time make an inappropriate commendation without considering the seasonal factor. In order to resolve the discrepancy, the seasonal factor should have been taken into consideration when making a good travel recommender system. Therefore, this study has taken the trend analysis, time series, and seasonal factor into considerations to cope with the above mentioned discrepancy and to make the travel recommender system renders a better fit.

A Sequence-to-Sequence Transformer Model for Disconnection Aware Retrosynthesis

Retrosynthesis is an approach commonly undertaken when considering the manufacture of novel molecules. During this process, a target molecule is broken down and analyzed by considering the bonds to be changed as well as the functional group interconversion. In modern computer-assisted synthesis planning tools, the predictions of these changes are typically carried out automatically. However there may be some benefit to the decision being guided by those executing the process: typically, chemists have a clear idea where the retrosynthetic change should happen, but not how such a transformation is to be realized. Using a data-driven model, the retrosynthesis task can be further explored by giving chemists the option to explore specific disconnections. In this work, we design an approach to provide this option by adapting a transformer-based model for single-step retrosynthesis. The model takes as input a product SMILES string, in which the atoms where the transformation should occur are tagged accordingly. This model predicts precursors corresponding to a disconnection occurring in the correct location in 88.9% of the test set reactions. The assessment with a forward prediction model shows that 76% of the predictions are chemically correct, with 14.1% perfectly matching the ground truth.

Proposal for a Pivot-Based Vehicle Trajectory Clustering Method

Given the large volume of georeferenced information generated and stored by many types of devices, the study and improvement of techniques capable of operating with these data is an area of great interest. The analysis of vehicular trajectories with the aim of forming clusters and identifying emerging patterns is very useful for characterizing and analyzing transportation flows in cities. This paper presents a new trajectory clustering method capable of identifying clusters of vehicular sub-trajectories in various sectors of a city. The proposed method is based on the use of an auxiliary structure to determine the correct location of the centroid of each group or set of sub-trajectories along the adaptive process. The proposed method was applied on three real databases, as well as being compared with other relevant methods, achieving satisfactory results and showing good cluster quality according to the Silhouette index.

Cell biology of primary cell wall synthesis in plants

Building a complex structure such as the cell wall, with many individual parts that need to be assembled correctly from distinct sources within the cell, is a well-orchestrated process. Additional complexity is required to mediate dynamic responses to environmental and developmental cues. Enzymes, sugars and other cell wall components are constantly and actively transported to and from the plasma membrane during diffuse growth. Cell wall components are transported in vesicles on cytoskeletal tracks composed of microtubules and actin filaments. Many of these components, and additional proteins, vesicles, and lipids are trafficked to and from the cell plate during cytokinesis. In this review, we first discuss how the cytoskeleton is initially organized to add new cell wall material or to build a new cell wall, focusing on similarities during these processes. Next, we discuss how polysaccharides and enzymes that build the cell wall are trafficked to the correct location by motor proteins and through other interactions with the cytoskeleton. Finally, we discuss some of the special features of newly formed cell walls generated during cytokinesis.

Synthetic deconstruction of hunchback regulation by Bicoid

During development, cell identity is established reproducibly among individuals through the expression of specific genes at the correct time and correct location in space. How genes extract and combine both positional and temporal information from different transcription factor (TF) profiles along polarity axes remain largely unexplored. Here, we showcase the classic hunchback gene in fruit fly embryos, with focus on 3 of its main TFs: Bicoid, Zelda and Hunchback proteins. We constructed a series of synthetic MS2 reporters, where the numbers and combination of binding sites for each TF are varied. Using live imaging of transcription dynamics by these synthetic reporters and modeling tools, we show that i) a Bicoid-only synthetic reporter needs 3 more Bicoid binding sites than found in the hunchback promoter to recapitulates almost all spatial features of early hb expression but takes more time to reach steady state; ii) Hunchback and Zelda binding sites combined with Bicoid sites both reduce the time to reach steady state and increase expression at a different step in the activation process: Zld sites lower the Bicoid threshold required for activation while Hb sites increase the polymerase firing rate and reduce bursting; iii) the shift of the Bicoid-only reporter induced by a reduction by half of Bicoid concentrations indicates that the decay length of the Bicoid activity gradient is lower than the decay length of the Bicoid protein gradient. Altogether, this work indicates that Bicoid is the main source of positional information for hunchback expression and places back the Bicoid system within the physical limits of an equilibrium model.

Web Scraper Utilizes Google Street View Images to Power a University Tour

Due to the outbreak of the Covid-19 pandemic, college tours are no longer available, so many students have lost the opportunity to see their dream school’s campus. To solve this problem, we developed a product called “Virtourgo,” a university virtual tour website that uses Google Street View images gathered from a web scraper allowing students to see what college campuses are like even when tours are unavailable during the pandemic. The project consists of 3/4 parts: the web scraper script, the GitHub server, the Google Domains DNS Server, and the HTML files. Some challenges we met include scraping repeated pictures and letting the HTML dropdown menu jump to the correct location. We solved these by implementing Python and Javascript functions that specifically target such challenges. Finally, after experimenting with all the functions of the web scraper and website, we confirmed that it works as expected and can scrape and deliver tours of any university campus or public buildings we want.

Robotic Bronchoscopy for Peripheral Pulmonary Lesion Biopsy: Evidence-Based Review of the Two Platforms

Despite many advancements in recent years for the sampling of peripheral pulmonary lesions, the diagnostic yield remains low. Initial excitement about the current electromagnetic navigation platforms has subsided as the real-world data shows a significantly lower diagnostic sensitivity of ~70%. “CT-to-body divergence” has been identified as a major limitation of this modality. In-tandem use of the ultrathin bronchoscope and radial endobronchial ultrasound probe has yielded only comparable results, attributable to the limited peripheral reach, device maneuverability, stability, and distractors like atelectasis. As such, experts have identified three key steps in peripheral nodule sampling—navigation (to the lesion), confirmation (of the correct location), and acquisition (tissue sampling by tools). Robotic bronchoscopy (RB) is a novel innovation that aspires to improve upon these aspects and consequently, achieve a better diagnostic yield. Through this publication, we aim to review the technical aspects, safety, feasibility, and early efficacy data for this new diagnostic modality.

Face Perception and Pareidolia Production in Patients With Parkinson's Disease

In Parkinson's disease (PD) patients, visual misperceptions are a major problem within the non-motor symptoms. Pareidolia, i.e., the tendency to perceive a specific, meaningful image in an ambiguous visual pattern, is a phenomenon that occurs also in healthy subjects. Literature suggests that the perception of face pareidolia may be increased in patients with neurodegenerative diseases. We aimed to examine, within the same experiment, face perception and the production of face pareidolia in PD patients and healthy controls (HC). Thirty participants (15 PD patients and 15 HC) were presented with 47 naturalistic photographs in which faces were embedded or not. The likelihood to perceive the embedded faces was modified by manipulating their transparency. Participants were asked to decide for each photograph whether a face was embedded or not. We found that PD patients were significantly less likely to recognize embedded faces than controls. However, PD patients also perceived faces significantly more often in locations where none were actually present than controls. Linear regression analyses showed that gender, age, hallucinations, and Multiple-Choice Vocabulary Intelligence Test (MWT) score were significant predictors of face pareidolia production in PD patients. Montreal Cognitive Assessment (MoCA) was a significant predictor for pareidolia production in PD patients in trials in which a face was embedded in another region [F(1, 13) = 24.4, p = &lt;0.001]. We conclude that our new embedded faces paradigm is a useful tool to distinguish face perception performance between HC and PD patients. Furthermore, we speculate that our results observed in PD patients rely on disturbed interactions between the Dorsal (DAN) and Ventral Attention Networks (VAN). In photographs in which a face is present, the VAN may detect this as a behaviourally relevant stimulus. However, due to the deficient communication with the DAN in PD patients, the DAN would not direct attention to the correct location, identifying a face at a location where actually none is present.