bluuebunny/crossref_metadata_2025 huggingface dataset:
Procedure for assessing patients referred to the UK’s military Heat Illness Clinic: a case series
Authors: House Carol , Stacey M , Woods D , Allsopp A , Roiz de Sa D
Published: July 2021

Introduction

The UK military operates a Heat Illness Clinic (HIC) to aid the return to exercise, training and occupational duty recommendations for individuals who have suffered exertional heat illness or heatstroke. This paper describes the process of assessment and reports representative data from n=22 patients referred to the HIC.

Method

The assessment included clinical consultation, and measurement of maximal oxygen consumption (V̇O2max) and a heat tolerance test (HTT) conducted on a treadmill in an environmental chamber with an air temperature of 34°C and 44% relative humidity. Patients began the HTT wearing military clothing, carrying a rucksack (mass 15 kg) and walking at 60% V̇O2max, at 30 min the rucksack and jacket were removed and the T-shirt at 45 min, individuals continued walking for 60–90 min. Patients were considered heat tolerant if rectal temperature achieved a plateau.

Results

N=14 patients were heat tolerant on the first assessment and of the n=8 patients required to return for repeat assessment, five were heat tolerant on the second assessment and the remaining three on the third assessment.

Conclusions

In conjunction with patient history and clinical evaluation, the HTT provides a physiological basis to assist with decisions concerning patient management and return to duty following an episode of heat illness.
Web-based survey to evaluate the prevalence of chronic and subacute cough and patient characteristics in Japan
Authors: Tobe Keisuke , Kubo Takekazu , Okuyama Kotoba , Kikuchi Masashi , Chen Yirong , Schelfhout Jonathan , Abe Machiko , Tokita Shigeru
Published: July 2021

Background

Cough lasting 3–8 weeks and more than 8 weeks are defined as subacute/prolonged cough and chronic cough, respectively. Japanese chronic cough population has not been well studied. This study aimed to describe the prevalence and characteristics of chronic cough and subacute cough patients in Japan. This study also sought to compare between chronic cough patients who were not greatly satisfied with treatment effectiveness for resolving cough and other chronic cough patients.

Methods

Data from a cross-sectional online 2019 Japan National Health and Wellness Survey and a supplemental chronic cough survey were used to understand respondents’ chronic cough status and their cough-specific characteristics and experience. The prevalence, patient characteristics and cough-specific characteristics were summarised descriptively. Patients who were not greatly satisfied with treatment effectiveness and other chronic cough patients were compared for their characteristics and cough severity.

Results

The point prevalence of chronic cough was 2.89% and 12-month period prevalence was 4.29%. Among all chronic cough patients analysed, the average age was 56 years old, 61.1% were males and 29.4% were current smokers. Patients were most frequently told by a physician that cough was related to allergic rhinitis, asthma and cough variant asthma. Only 44.2% of chronic cough patients had spoken with a physician about their cough, and half of chronic cough patients did not use any medications. Patients who were not greatly satisfied with treatment effectiveness had significantly greater cough severity during past 2 weeks compared with other chronic cough patients (Visual Analogue Scale 45.34 vs 39.63).

Conclusions

This study described the prevalence and patient characteristics information of chronic cough patients in Japan. Furthermore, the study highlighted an unmet need for better diagnosis and treatments for chronic cough patients, especially among patients who were not greatly satisfied with treatment effectiveness and reported significantly worse cough severity.
Society for Immunotherapy of Cancer (SITC) clinical practice guideline on immunotherapy for the treatment of urothelial cancer
Authors: Galsky Matthew D , Balar Arjun V , Black Peter C , Campbell Matthew T , Dykstra Gail S , Grivas Petros , Gupta Shilpa , Hoimes Christoper J , Lopez Lidia P , Meeks Joshua J , Plimack Elizabeth R , Rosenberg Jonathan E , Shore Neal , Steinberg Gary D , Kamat Ashish M
Published: July 2021

A number of immunotherapies have been developed and adopted for the treatment of urothelial cancer (encompassing cancers arising from the bladder, urethra, or renal pelvis). For these immunotherapies to positively impact patient outcomes, optimal selection of agents and treatment scheduling, especially in conjunction with existing treatment paradigms, is paramount. Immunotherapies also warrant specific and unique considerations regarding patient management, emphasizing both the prompt identification and treatment of potential toxicities. In order to address these issues, the Society for Immunotherapy of Cancer (SITC) convened a panel of experts in the field of immunotherapy for urothelial cancer. The expert panel developed this clinical practice guideline (CPG) to inform healthcare professionals on important aspects of immunotherapeutic treatment for urothelial cancer, including diagnostic testing, treatment planning, immune-related adverse events (irAEs), and patient quality of life (QOL) considerations. The evidence- and consensus-based recommendations in this CPG are intended to give guidance to cancer care providers treating patients with urothelial cancer.
Results from London Regional Clinical Genetics services over a 5-year period on germline TP53 testing in women diagnosed with breast cancer at <30 years
Authors: Garrett Alice , Talukdar Sabrina , Izatt Louise , Brady Angela F , Whyte Sinead , Josephs Katherine S , Shanmugasundaram Monisha , Guillemot Li Shan , Vakili Dara , Ey Shevaun , Ahmed Munaza
Published: July 2021

Background

The most common cancer diagnosed in germline TP53 pathogenic variant (PV) carriers is premenopausal breast cancer. An increased rate of breast tumour HER2 positivity has been reported in this group. Screening for breast/other cancers is recommended in PV carriers.

Objectives

1. To assess the frequency of germline TP53 PVs reported diagnostically in women with breast cancer at <30 years of age.

2. To evaluate the impact of personal/family history and HER2 status on the likelihood of germline TP53 pathogenic/likely pathogenic variant (PV/LPV) identification.

Methods

Genetic test results from patients undergoing diagnostic germline TP53 tests between 2012 and 2017 in the four London Regional Clinical Genetics Services were reviewed. Clinical/pathology data and family history were extracted from genetics files for women diagnosed with breast cancer at <30 years.

Results

The overall germline TP53 PV/LPV variant detection rate was 9/270=3.3% in all women diagnosed with breast cancer at <30 years and 2/171=1.2% in those with no second/subsequent cancer diagnosis or family history of TP53-spectrum cancers. Breast cancers were significantly more likely to be HER2-positive in TP53 PV/LPV carriers than in non-carriers (p=0.00006).

Conclusions

Germline TP53 PVs/LPVs are uncommon among women diagnosed with breast cancer aged <30 years without other relevant personal or family cancer history but have an important clinical impact when identified.
Finnish flow diverter study: 8 years of experience in the treatment of acutely ruptured intracranial aneurysms
Authors: Alpay Kemal , Hinkka Tero , Lindgren Antti E , Isokangas Juha-Matti , Raj Rahul , Parkkola Riitta , Sinisalo Matias , Numminen Jussi , Pienimäki Juha-Pekka , Saari Petri , Seppänen Janne , Palosaari Kari , Rautio Riitta
Published: July 2021

Background

Flow diversion of acutely ruptured intracranial aneurysms (IAs) is controversial due to high treatment-related complication rates and a lack of supporting evidence. We present clinical and radiological results of the largest series to date.

Methods

This is a nationwide retrospective study of acutely ruptured IAs treated with flow diverters (FDs). The primary outcome was the modified Rankin Scale (mRS) score at the last available follow-up time. Secondary outcomes were treatment-related complications and the aneurysm occlusion rate.

Results

110 patients (64 females; mean age 55.7 years; range 12–82 years) with acutely ruptured IAs were treated with FDs between 2012 and 2020 in five centers. 70 acutely ruptured IAs (64%) were located in anterior circulation, and 47 acutely ruptured IAs (43%) were blister-like. A favorable functional outcome (mRS 0–2) was seen in 73% of patients (74/102). Treatment-related complications were seen in 45% of patients (n=49). Rebleeding was observed in 3 patients (3%). The data from radiological follow-ups were available for 80% of patients (n=88), and complete occlusion was seen in 90% of aneurysms (79/88). The data from clinical follow-ups were available for 93% of patients (n=102). The overall mortality rate was 18% (18/102).

Conclusions

FD treatment yields high occlusion for acutely ruptured IAs but is associated with a high risk of complications. Considering the high mortality rate of aneurysmal subarachnoid hemorrhage, the prevention of rebleeding is crucial. Thus, FD treatment may be justified as a last resort option.
Comparing weak- and unsupervised methods for resonant anomaly detection
Authors: Collins Jack H. , Martín-Ramiro Pablo , Nachman Benjamin , Shih David
Published: July 2021

Anomaly detection techniques are growing in importance at the Large Hadron Collider (LHC), motivated by the increasing need to search for new physics in a model-agnostic way. In this work, we provide a detailed comparative study between a well-studied unsupervised method called the autoencoder (AE) and a weakly-supervised approach based on the Classification Without Labels (CWoLa) technique. We examine the ability of the two methods to identify a new physics signal at different cross sections in a fully hadronic resonance search. By construction, the AE classification performance is independent of the amount of injected signal. In contrast, the CWoLa performance improves with increasing signal abundance. When integrating these approaches with a complete background estimate, we find that the two methods have complementary sensitivity. In particular, CWoLa is effective at finding diverse and moderately rare signals while the AE can provide sensitivity to very rare signals, but only with certain topologies. We therefore demonstrate that both techniques are complementary and can be used together for anomaly detection at the LHC.
Inquiring electromagnetic quantum fluctuations about the orientability of space
Authors: Lemos N. A. , Rebouças M. J.
Published: July 2021

Orientability is an important global topological property of spacetime manifolds. It is often assumed that a test for spatial orientability requires a global journey across the whole 3-space to check for orientation-reversing paths. Since such a global expedition is not feasible, theoretical arguments that combine universality of physical experiments with local arrow of time, CP violation and CPT invariance are usually offered to support the choosing of time- and space-orientable spacetime manifolds. Another theoretical argument also offered to support this choice comes from the impossibility of having globally defined spinor fields on non-orientable spacetime manifolds. In this paper, we argue that it is possible to locally access spatial orientability of Minkowski empty spacetime through physical effects involving quantum vacuum electromagnetic fluctuations. We study the motions of a charged particle and a point electric dipole subject to these electromagnetic fluctuations in Minkowski spacetime with orientable and non-orientable spatial topologies. We derive analytic expressions for a statistical orientability indicator for both of these point-like particles in two inequivalent spatially flat topologies. For the charged particle, we show that it is possible to distinguish the orientable from the non-orientable topology by contrasting the time evolution of the orientability indicators. This result reveals that it is possible to access orientability through electromagnetic quantum vacuum fluctuations. However, the answer to the central question of the paper, namely how to locally probe the orientability of Minkowski 3-space intrinsically, comes about only in the study of the motions of an electric dipole. For this point-like particle, we find that a characteristic inversion pattern exhibited by the curves of the orientability statistical indicator is a signature of non-orientability. This result makes it clear that it is possible to locally unveil spatial non-orientability through the inversion pattern of curves of our orientability indicator for a point electric dipole under quantum vacuum electromagnetic fluctuations. Our findings might open the way to a conceivable experiment involving quantum vacuum electromagnetic fluctuations to locally probe the spatial orientability of Minkowski empty spacetime.
Inhibition of metastasis using particles that release chitosan upon radiation: A preliminary study
Authors: Harada Satoshi , Sato Takahiro
Published: July 2021

This study aimed to investigate the effect of the particles releasing chitosan upon exposure to radiation on inhibition of metastasis.

A 10 mL solution of water containing 0.2% weight/volume alginate, 0.1% hyaluronic acid, and 100-mg chitosan was sprayed into the vibrating solution through a stainless mesh filter (pore size: 0.8 [Formula: see text]m) using an ultrasound disintegrator, thereby generating chitosan particles. Further, [Formula: see text] particles floating in 0.1 mL normal saline were subcutaneously injected around the 4TI cells-derived tumor in the left hind legs of six-week-old male C3He/N mice. Six hours after injection, tumors were exposed to 10 Gy or 20 Gy of 100-keV soft X-ray radiation. The release of chitosan was expressed as the frequency of ruptured chitosan particles 12 h after radiation. The antimetastatic effect was confirmed by a reduction in the number of metastatic pulmonary nodules 21 days after completion of treatment.

More than [Formula: see text]% of the chitosan particles released chitosan in response to radiation. The particles releasing chitosan had a prolonged antimetastatic effect when compared with the particles not releasing chitosan, thereby resulting in a significantly greater antimetastatic effect lasting for four weeks since the completion of treatment, in tumors treated with both 10 Gy and 20 Gy of radiation.

Hence, particlizing chitosan could be useful in reducing metastasis in irradiated tumors.
The Role of Ophiopogonin D in Atherosclerosis: Impact on Lipid Metabolism and Gut Microbiota
Authors: Zhang Ya-Xin , Qu Shan-Shan , Zhang Li-Hua , Gu Yu-Yan , Chen Yi-Hao , Huang Zhi-Yong , Liu Meng-Hua , Zou Wei , Jiang Jing , Chen Jun-Qi , Wang Yu-Jue , Zhou Feng-Hua
Published: July 2021

Gut microbiota has been proven to play an important role in many metabolic diseases and cardiovascular disease, particularly atherosclerosis. Ophiopogonin D (OPD), one of the effective compounds in Ophiopogon japonicus, is considered beneficial to metabolic syndrome and cardiovascular diseases. In this study, we have illuminated the effect of OPD in ApoE knockout (ApoE[Formula: see text] mice on the development of atherosclerosis and gut microbiota. To investigate the potential ability of OPD to alleviate atherosclerosis, 24 eight-week-old male ApoE[Formula: see text] mice (C57BL/6 background) were fed a high-fat diet (HFD) for 12 weeks, and 8 male C57BL/6 mice were fed a normal diet, serving as the control group. ApoE[Formula: see text] mice were randomly divided into the model group, OPD group, and simvastatin group ([Formula: see text]= 8). After treatment for 12 consecutive weeks, the results showed that OPD treatment significantly decreased the plaque formation and levels of serum lipid compared with those in the model group. In addition, OPD improved oral glucose tolerance and insulin resistance as well as reducing hepatocyte steatosis. Further analysis revealed that OPD might attenuate atherosclerosis through inhibiting mTOR phosphorylation and the consequent lipid metabolism signaling pathways mediated by SREBP1 and SCD1 in vivo and in vitro. Furthermore, OPD treatment led to significant structural changes in gut microbiota and fecal metabolites in HFD-fed mice and reduced the relative abundance of Erysipelotrichaceae genera associated with cholesterol metabolism. Collectively, these findings illustrate that OPD could significantly protect against atherosclerosis, which might be associated with the moderation of lipid metabolism and alterations in gut microbiota composition and fecal metabolites.
Bioconvection mechanism using third-grade nanofluid flow with Cattaneo–Christov heat flux model and Arrhenius kinetics
Authors: Waqas Hassan , Khan Shan Ali , Bhatti M. M. , Hussain Sajjad
Published: July 2021

This paper aims to study the effects of activation energy and thermal radiation in the bioconvection flow of nanofluid (third-grade nanofluid) containing swimming microorganisms in the presence of a heat source-sink past a stretching sheet. Brownian movement and thermophoresis diffusion are used in mathematical modeling. The given flow phenomenon is modeled in the form of governing partial differential equations. Furthermore, appropriate dimensionless transformation is used to transfer the governing system of PDEs into an ordinary one. The remodeled systems of ODEs are tackled numerically by bvp4c on Matlab with a shooting scheme in computational tool MATLAB. The bearing of prominently involved parameters on the numerical solution of velocity, temperature distribution, nanoparticles concentration and concentration of microorganisms is comprehensively discussed and elaborated through figures. It is established that velocity can be improved with a mixed convection aspect. Furthermore, the temperature and concentration of nanoparticles reduce against Prandtl number, also, large Peclet number declines the microorganisms field. The work contained in this paper has applications in nanotechnology, electrical and mechanical engineering, biomedicine, biotechnology, drug delivery, cancer treatment, food processing and various industries. No such work is yet reported, and it is good for the research in applied sciences.
GPN: A novel gravity model based on position and neighborhood to identify influential nodes in complex networks
Authors: Tu Dengqin , Xu Guiqiong , Meng Lei
Published: July 2021

The identification of influential nodes is one of the most significant and challenging research issues in network science. Many centrality indices have been established starting from topological features of networks. In this work, we propose a novel gravity model based on position and neighborhood (GPN), in which the mass of focal and neighbor nodes is redefined by the extended outspreading capability and modified k-shell iteration index, respectively. This new model comprehensively considers the position, local and path information of nodes to identify influential nodes. To test the effectiveness of GPN, a number of simulation experiments on nine real networks have been conducted with the aid of the susceptible–infected–recovered (SIR) model. The results indicate that GPN has better performance than seven popular methods. Furthermore, the proposed method has near linear time cost and thus it is suitable for large-scale networks.
A novel fuzzy community detection method based on improved community adjacency list
Authors: Zhou Xinyue
Published: July 2021

With the development of economy and society, network analysis is widely used in more and more fields. Signed network has a good effect in the process of representation and display. As an important part of network analysis, fuzzy community detection plays an increasingly important role in analyzing and visualizing the real world. Fuzzy community detection helps to detect nodes that belong to some communities but are still closely related to other communities. These nodes are helpful for mining information from the network more realistically. However, there is little research in this field. This paper proposes a fuzzy community detection algorithm based on pointer and adjacency list. The model adopts a new ICALF network data structure, which can achieve the effect of storing community partition structure and membership value between community and node at the same time, with low time complexity and storage space. Experiments on real networks verify the correctness of the method, and prove that the method is suitable for large-scale network applications.
Numerical analysis of time-dependent stagnation point flow of Oldroyd-B fluid subject to modified Fourier’s law
Authors: Qasim Foukeea , Sun Tian-Chuan , Abbas S. Z. , Khan W. A. , Malik M. Y.
Published: July 2021

This paper aims to investigate the time-dependent stagnation point flow of an Oldroyd-B fluid subjected to the modified Fourier law. The flow into a vertically stretched cylinder at the stagnation point is discussed. The heat flux model of a non-Fourier is intended for the transfer of thermal energy in fluid flow. The study is carried out on the surface heating source, namely the surface temperature. The developed nonlinear partial differential equation for regulating fluid flow and heat transport is transformed via appropriate similarity variables into a nonlinear ordinary differential equation. The development and analysis of convergent series solutions were considered for velocity and temperature. Prandtl number numerical values are computed and investigated. This study’s findings are compared to the previous findings. By making use of the bvp4c Matlab method, numerical solutions are obtained. Besides, high buoyancy parameter values are found to increase the fluid velocity for the stimulating approach. By improving the thermal relaxation time parameter values, heat transfer in the fluid flow decreases. The temperature field effects are displayed graphically.
Theoretical model of gain calculation of active photonic-crystal microcavity waveguide
Authors: Gu Ting-Wei , Jiang Chun
Published: July 2021

In this paper, we propose an active photonic-crystal microcavity waveguide with two-level atom-doped-dielectric slab as background material, and derive the model for signal gain calculation and analyze its gain characteristics. The analytical results show that the structure can generate high gain in a short length because of the efficient utilization of pump power in the microcavity. The proposed waveguide will be promising for the development of an active integrated photonic system.
High temperature analysis of strained superjunction vertical single diffused MOSFET
Authors: Parmar Onika , Naugarhiya Alok
Published: July 2021

This paper focuses on testing the reliability of a Strained Superjunction Vertical Single diffused MOS (s-SJVSDMOS) at high-temperature. It provides an in-depth study of the device behavior at high-temperatures specifically at 300, 350 and 400 K. The s-SJVSDMOS is simulated in 2D T-CAD simulator and the outcomes are extracted. The variation of the extracted parameters with temperature is explored. The electrical and channel characteristics of the device are analyzed here. From the discussion, it was deduced that at high-temperature the device exhibits analogous characteristics as at room-temperature condition.
Splittings of right-angled Artin groups
Authors: Hull M.
Published: July 2021

We show that if a right-angled Artin group [Formula: see text] has a non-trivial, minimal action on a tree [Formula: see text] with more than two ends, then [Formula: see text] contains a separating subgraph [Formula: see text] such that [Formula: see text] stabilizes an edge in [Formula: see text].
CHARACTERIZATION AND ELECTROCHEMICAL CORROSION ANALYSIS OF HEAT-TREATED REINFORCED HA COATINGS DEPOSITED BY VACUUM PLASMA SPRAY TECHNIQUE
Authors: SINGH KANG AMARDEEP , SINGH GURBHINDER , CHAWLA VIKAS , PRAKASH CHANDER , RADHAKRISHNAN RAMANUJAM , WU LINDA YONGLING , ZHENG H. Y.
Published: July 2021

Herein, a biomimetic coating of hydroxyapatite (HA)–Al2O3 and HA–ZrO2 was deposited on Ti–6Al–4V-alloy using vacuum plasma spray (VPS) technique. The bond-coat of ZrO2 has been introduced between the substrate and reinforced HA coatings to study the effect of bond-coat on structural, mechanical properties and electrochemical corrosion performance of the developed coatings. In addition, the impact of thermal treatment of coating was investigated on these properties too. Coating characteristics, such as morphology, porosity, surface roughness, and crystallinity were investigated. The corrosion performance of coatings was tested in Hank’s-based salt solution (HBSS). Significant enhancement in crystallinity and surface-hardness has been witnessed after heat treatment; nevertheless, porosity reduced. The electrochemical corrosion study revealed that the corrosion resistance of heat-treated samples was better than the as-sprayed coatings samples. The intensity of XRD peaks of all coatings increased after 24[Formula: see text]h immersion in HBSS for the electrochemical test in comparison to the intensity of peaks before the corrosion test.
PREVALENCE AND RISK FACTORS OF SELF-REPORTED MUSCULOSKELETAL DISORDERS AMONG LOW RESOURCED URBAN COMMUNITY DWELLERS
Authors: Akindele Mukadas O. , Shehu Abba , Useh Ushotanefe
Published: July 2021

Background: Musculoskeletal disorders are prevalent in communities across the world and their impact is affecting people in almost all occupational settings. Aim: The aim of this study was to determine the prevalence of self-reported musculoskeletal disorders among urban dwellers, Kano metropolis. Method: A total of 206 participants were recruited using a stratified sampling technique in a cross-sectional survey. The data was collected using a standard Nordic Musculoskeletal Questionnaire (NMQ) and International Physical Activity Questionnaire (IPAQ) to measure work-related musculoskeletal disorders and physical activity levels of the participants. Results: The results showed that the majority of the participants (63.9%) were males and 36.9% were females between the ages of 18 and 65 years, with the majority of them between 18 and 34 years, singles and self-employed. Also, the majority of the participants had moderate physical activity levels, normal body mass index and low risk of cardiovascular diseases using the waist to hip ratio classifications. About 78.2% of the participants reported 12-month musculoskeletal disorders while 37.4% reported 7-day musculoskeletal disorders. Low back was the most common site affected by 45.6% of the respondents. Also, the result showed no significant relationship between 12-month musculoskeletal disorder and BMI, physical activity level and waist/hip ratio but a relationship between 7 Days musculoskeletal disorder and BMI, physical activity level and waist/hip ratio. Conclusion: It was concluded that there was a high prevalence of musculoskeletal disorders among urban community dwellers in Kano metropolis, with low back pain the most reported while upper back has the least prevalence. Clinical Rehabilitation Impact: There was a high prevalence of WMSD among the general populace irrespective of the sociodemographic affiliations. Lower back was the most reported anatomical site among our participants. Men had a higher number of WMSD than women. There was an association between WMSD and WHR and BMI. Excess weight management might be helpful especially in individuals with high BMI and WHR.
Integration of Dynamic Multi-Atlas and Deep Learning Techniques to Improve Segmentation of the Prostate in MR Images
Authors: Moradi Hamid , Foruzan Amir Hossein
Published: July 2021

Accurate delineation of the prostate in MR images is an essential step for treatment planning and volume estimation of the organ. Prostate segmentation is a challenging task due to its variable size and shape. Moreover, neighboring tissues have a low-contrast with the prostate. We propose a robust and precise automatic algorithm to define the prostate’s boundaries in MR images in this paper. First, we find the prostate’s ROI by a deep neural network and decrease the input image’s size. Next, a dynamic multi-atlas-based approach obtains the initial segmentation of the prostate. A watershed algorithm improves the initial segmentation at the next stage. Finally, an SSM algorithm keeps the result in the domain of allowable prostate shapes. The quantitative evaluation of 74 prostate volumes demonstrated that the proposed method yields a mean Dice coefficient of [Formula: see text]. In comparison with recent researches, our algorithm is robust against shape and size variations.
On essential elements in a lattice and Goldie analogue theorem
Authors: Sahoo Tapatee , Kedukodi Babushri Srinivas , Shum Kar Ping , Panackal Harikrishnan , Kuncham Syam Prasad
Published: July 2021

We introduce the concept of essentiality in a lattice [Formula: see text] with respect to an element [Formula: see text]. We define notions such as [Formula: see text]-essential, [Formula: see text]-uniform elements and obtain some of their properties. Examples of lattices are given wherein essentiality can be retained with respect to an arbitrary element (specifically, there are elements in [Formula: see text] which are [Formula: see text]-essential but not essential). We prove Goldie analogue results in terms of [Formula: see text]-uniform elements and [Formula: see text]-∨-independent sets. Furthermore, we define a graph with respect to [Formula: see text]-essential element in a lattice and study its properties.
A Framework for Generating Summaries from Temporal Personal Health Data
Authors: Harris Jonathan J. , Chen Ching-Hua , Zaki Mohammed J.
Published: July 2021

Although it has become easier for individuals to track their personal health data (e.g., heart rate, step count, and nutrient intake data), there is still a wide chasm between the collection of data and the generation of meaningful summaries to help users better understand what their data means to them. With an increased comprehension of their data, users will be able to act upon the newfound information and work toward striving closer to their health goals. We aim to bridge the gap between data collection and summary generation by mining the data for interesting behavioral findings that may provide hints about a user’s tendencies. Our focus is on improving the explainability of temporal personal health data via a set of informative summary templates, or “protoforms.” These protoforms span both evaluation-based summaries that help users evaluate their health goals and pattern-based summaries that explain their implicit behaviors. In addition to individual-level summaries, the protoforms we use are also designed for population-level summaries. We apply our approach to generate summaries (both univariate and multivariate) from real user health data and show that the summaries our system generates are both interesting and useful.
Learning Multimodal Affinities for Textual Editing in Images
Authors: Perel Or , Anschel Oron , Ben-Eliezer Omri , Mazor Shai , Averbuch-Elor Hadar
Published: July 2021

Nowadays, as cameras are rapidly adopted in our daily routine, images of documents are becoming both abundant and prevalent. Unlike natural images that capture physical objects, document-images contain a significant amount of text with critical semantics and complicated layouts. In this work, we devise a generic unsupervised technique to learn multimodal affinities between textual entities in a document-image, considering their visual style, the content of their underlying text, and their geometric context within the image. We then use these learned affinities to automatically

cluster the textual entities in the image into different semantic groups. The core of our approach is a deep optimization scheme dedicated for an image provided by the user that detects and leverages reliable pairwise connections in the multimodal representation of the textual elements to properly learn the affinities. We show that our technique can operate on highly varying images spanning a wide range of documents and demonstrate its applicability for various editing operations manipulating the content, appearance, and geometry of the image.
Vectorization for Fast, Analytic, and Differentiable Visibility
Authors: Zhou Yang , Wu Lifan , Ramamoorthi Ravi , Yan Ling-Qi
Published: July 2021

In Computer Graphics, the two main approaches to rendering and visibility involve ray tracing and rasterization. However, a limitation of both approaches is that they essentially use point sampling. This is the source of noise and aliasing, and also leads to significant difficulties for differentiable rendering. In this work, we present a new rendering method, which we call vectorization, that computes 2D point-to-region integrals analytically, thus eliminating point sampling in the 2D integration domain such as for pixel footprints and area lights. Our vectorization revisits the concept of beam tracing, and handles the hidden surface removal problem robustly and accurately. That is, for each intersecting triangle inserted into the viewport of a beam in an arbitrary order, we are able to maintain all the visible regions formed by intersections and occlusions, thanks to our Visibility Bounding Volume Hierarchy structure. As a result, our vectorization produces perfectly anti-aliased visibility, accurate and analytic shading and shadows, and most important, fast and noise-free gradients with Automatic Differentiation or Finite Differences that directly enables differentiable rendering without any changes to our rendering pipeline. Our results are inherently high-quality and noise-free, and our gradients are one to two orders of magnitude faster than those computed with existing differentiable rendering methods.
BlueFlood
Authors: Nahas Beshr Al , Escobar-Molero Antonio , Klaue Jirka , Duquennoy Simon , Landsiedel Olaf
Published: July 2021

Bluetooth is an omnipresent technology, available on billions of devices today. While it has been traditionally limited to peer-to-peer communication and star networks, the recent Bluetooth Mesh standard extends it to multi-hop networking. In addition, the Bluetooth 5 standard introduces new modes to allow for increased reliability. In this article, we evaluate the feasibility of concurrent transmissions (CT) in Bluetooth via modeling and controlled experiments and then devise an efficient network-wide data dissemination protocol, BlueFlood, based on CT for multi-hop Bluetooth networks.

First, we model and analyze how CT distorts the received waveform and characterize the Bit Error Rate of a Frequency-Shift Keying receiver to show that CT is feasible over Bluetooth. Second, we verify our analytic results with a controlled experimental study of CT over Bluetooth PHY. Third, we present BlueFlood, a fast and efficient network-wide data dissemination in multi-hop Bluetooth networks.

In our experimental evaluation, in two testbeds deployed in university buildings, we show that BlueFlood achieves 99.9% end-to-end delivery ratio with a duty-cycle of 0.4% for periodic dissemination of advertising packets of 38 bytes with 200 milliseconds intervals at 2 Mbps. Moreover, we show that BlueFlood can be received by off-the-shelf devices such as smartphones, paving a seamless integration with existing technologies.
Robust Environmental Sensing Using UAVs
Authors: Boubrima Ahmed , Knightly Edward W.
Published: July 2021

In this article, we first investigate the quality of aerial air pollution measurements and characterize the main error sources of drone-mounted gas sensors. To that end, we build ASTRO+, an aerial-ground pollution monitoring platform, and use it to collect a comprehensive dataset of both aerial and reference air pollution measurements. We show that the dynamic airflow caused by drones affects temperature and humidity levels of the ambient air, which then affect the measurement quality of gas sensors. Then, in the second part of this article, we leverage the effects of weather conditions on pollution measurements’ quality in order to design an unmanned aerial vehicle mission planning algorithm that adapts the trajectory of the drones while taking into account the quality of aerial measurements. We evaluate our mission planning approach based on a Volatile Organic Compound pollution dataset and show a high-performance improvement that is maintained even when pollution dynamics are high.
Comparative Analysis of Low-Rank Matrix Denoising Algorithm-Based MRI and CT Images in Diagnosis of Cerebral Aneurysms
Authors: Li Aijun , Zheng Yuehua , Li Yan , Zhou Tao , Cao Peicheng , Qiu Shaobo , Wang Jinpeng
Published: July 2021

This study aimed to compare the role of magnetic resonance imaging (MRI) and computed tomography (CT) images based on the low-rank matrix (LRM) denoising (LRMD) algorithm in the diagnosis of cerebral aneurysms (CAs). By comparing the role of MRI and CT in the diagnosis of CA, it would be helpful to formulate more reasonable diagnosis strategies and provide a solid foundation for clinical treatment of patients. 80 patients with cerebral aneurysm admitted to hospital were selected as the research objects. First, the LRMD algorithm was established and applied to the image denoising process of MRI and CT. Then, the diagnosis rate of CA by MRI and CT before and after denoising was compared, and the diagnostic rates of the two methods for aneurysms of different sizes were compared. Finally, the location, foci, and patient satisfaction of the aneurysm were compared. The results showed that the MRI and CT images after denoising with LRM were clearer, and the secondary structures in the brain were more obvious. It meant that LRMD had good image denoising effect. The diagnostic rate of denoised MRI and CT was improved. Although the difference was not statistically notable, the diagnostic rate of CT was obviously higher in contrast to MRI (

P
<
0.05

). The diagnostic rate of CT for smaller aneurysms (<3 mm and 3–5 mm) was also notably higher in contrast to MRI (

P
<
0.05

). However, there was no difference in the diagnosis of tumor location between the two. The clarity of CT diagnostic images was better than MRI (

P
<
0.05

). Accordingly, patients were more satisfied with CT in contrast to MRI (

P
<
0.05

). In summary, CT images based on the LRMD algorithm were superior to MRI in the diagnosis of CA, and it could provide more accurate diagnosis results.
Development of Natural Fiber Hybrid Composites Using Sugarcane Bagasse and Bamboo Charcoal for Automotive Thermal Insulation Materials
Authors: Abedom Fasika , Sakthivel S. , Asfaw Daniel , Melese Bahiru , Solomon Eshetu , Kumar S. Senthil
Published: July 2021

The effective utilization of fibers from natural sources is the main objective of this research work, but natural fibers alone are not meeting the required strength properties. The objective of this study focuses on the experimental study of composites developed from bagasse fiber/bamboo charcoal for technical applications by investigating its diverse mechanical and thermal insulating properties. For this investigation, five hybrid composites with bagasse fiber/bamboo charcoal proportions of 100%/0%, 70%/30%, 50%/50%, 30%/70%, and 0%/100% with 65% polyurethane foam in all by using compression molding technique and their mechanical properties are evaluated experimentally under the ASTM standards. The fiber alignments, internal crack, and binding properties are checked by morphological test. It is observed that the tensile strength of sugarcane bagasse/charcoal composites produces 255.80 MPa which is approximately the same strength (260.10 MPa) as artificial fiber composites. The bagasse fiber/bamboo charcoal 30/70‐based composites show a higher thermal insulation coefficient than the other four samples‐reinforced composites. The impact and flexural strength of the 30/70 sample are higher than those of other samples. The results obtained report the possibility of exploitation of natural fiber sugarcane bagasse and bamboo charcoal for the production of reinforcements based on composites with good mechanical and thermal characteristics to utilize as automotive interior materials in component systems.
miR-193a Directly Targets PSEN1 and Inhibits Gastric Cancer Cell Growth, the Activation of PI3K/Akt Signaling Pathway, and the Epithelial-to-Mesenchymal Transition
Authors: Pan Xuemei , Zhao Ting , Mu Saisai , Li Shouchuan
Published: July 2021

Background. Gastric cancer, a kind of gastrointestinal malignancy, is the second type of leading death cancer. miR-193a is a key tumor suppressor in several diseases. PSEN1 is mainly related to Alzheimer’s disease and may be involved in the cleavage of the Notch receptor. Material and Methods. RT-PCR and western blot were applied to evaluate miR-193a and the expression level of PSEN1. Luciferase reporter assay was applied to verify whether PSEN1 was a target of miR-193a. The Kaplan–Meier method was employed to calculate the 5-year overall survival of gastric cancer patients. Results. miR-193a was downregulated in gastric cancer tissues and cell lines, and downregulation of miR-193a predicted poor 5-year overall survival of gastric cancer. miR-193a inhibited the proliferation and the activation of the PI3K/AKT signaling pathway in gastric cancer cells. miR-193a inhibited gastric cancer tumor growth in vivo. miR-193a impaired cell invasion and epithelial-to-mesenchymal transition (EMT) in HGC-27 cells. In addition, PSEN1 was a direct target of miR-193a and PSEN1 reversed partial functions of miR-193a in cell proliferation and invasion. Conclusion. miR-193a prominently decreased the proliferation, invasion, and activation of the PI3K/Akt signaling pathway and the abilities of epithelial-to-mesenchymal transition in gastric cancer cells. The newly identified miR-193a/PSEN1 axis provides novel insight into the pathogenesis of gastric cancer.
A Prediction Method for Flow-Stop Time in Deep-Water Volatile Oilfields: A Case Study of Akpo Oilfield in Niger Delta Basin
Authors: Kang Botao , Liu Pengcheng , Li Chenxi , Sun Yiyi , Xiao Peng , Tang Jiawei
Published: July 2021

Due to the difference in oil and water density, the wellhead pressure continues to decrease with water-cut rising in deep-water volatile oilfields. Once it is close to the lower limit, the production well will stop flowing. This phenomenon seriously affects the production and recoverable reserves. By taking the dynamic relative permeability which can reflect the macroscopic movement of oil and water in the reservoir as an intermediate bridge, production performance has been combined with dominant reservoir factors, including reservoir structure, reservoir connectivity, and heterogeneity. By the statistical analysis of actual data, this paper clarified the quantitative relationships between dominant reservoir factors and production performance and established the refined prediction methods for production dynamics including water-cut and liquid production rate. A prediction method for the wellhead pressure was further established, and the flow-stop time of single well can be accurately predicted. The results can be used in annual production forecast and recoverable reserve evaluation. This method had been successfully applied in Akpo oilfields in the Niger Basin. The results show that the production dynamics are significantly affected by reservoir factors in deep-water turbidite sandstone reservoir and the prediction method considering reservoir factors will be much more applicable. In deep-water volatile oilfields, the flow-stop risk of the production well in middle and high water-cut stages is very great and is mainly affected by the water-cut and liquid production rate. Judging from the application effect of Akpo oilfields, this method has high prediction accuracy and can be used to guide optimization and adjustment in deep-water oilfields.
Infra Soft Compact Spaces and Application to Fixed Point Theorem
Authors: Al-shami Tareq M.
Published: July 2021

Infra soft topology is one of the recent generalizations of soft topology which is closed under finite intersection. Herein, we contribute to this structure by presenting two kinds of soft covering properties, namely, infra soft compact and infra soft Lindelöf spaces. We describe them using a family of infra soft closed sets and display their main properties. With the assistance of examples, we mention some classical topological properties that are invalid in the frame of infra soft topology and determine under which condition they are valid. We focus on studying the “transmission” of these concepts between infra soft topology and classical infra topology which helps us to discover the behaviours of these concepts in infra soft topology using their counterparts in classical infra topology and vice versa. Among the obtained results, these concepts are closed under infra soft homeomorphisms and finite product of soft spaces. Finally, we introduce the concept of fixed soft points and reveal main characterizations, especially those induced from infra soft compact spaces.
Robotic Assistance in Unicompartmental Knee Arthroplasty Results in Superior Early Functional Recovery and Is More Likely to Meet Patient Expectations
Authors: Crizer Meredith P. , Haffar Amer , Battenberg Andrew , McGrath Mikayla , Sutton Ryan , Lonner Jess H.
Published: July 2021

Robotic technology has reduced the errors of implant alignment in unicompartmental knee arthroplasty (UKA), but its impact on functional recovery after UKA is poorly defined. The purpose of this study was to compare early functional recovery, pain levels, and satisfaction in UKA performed with either robotic assistance or conventional methods. A retrospective analysis was performed on 89 matched consecutive patients who underwent outpatient UKA by a single physician using either conventional instruments (n = 39) or robotic methods (n = 50), with otherwise identical perioperative protocols. Outcomes studied included Lower Extremity Functional Score (LEFS), new Knee Society Score (KSS), Knee Injury and Osteoarthritis Outcome Score for Joint Replacement (KOOS-JR.), VR/SF-12, Visual Analog Scale (VAS) pain scores, and perioperative opioid consumption. Patients in the robotic cohort had superior early functional outcomes, with greater LEFS (conventional = 23; robotic = 31) at 1 week post-op

p
=
0.015

and KOOS-JR (conventional = 74; robotic = 81) at up to 6 months post-op

p
=
0.037

; these two values remained statistically significant after mixed-model regression analysis

p
=
0.010
;
p
=
0.023

, respectively. At 1 year post-op, expectations were more likely to be met in those who received robotic assistance

p
=
0.06

. No differences were reported with respect to postoperative opioid usage

p
=
0.320

, reoperations

p
=
1.00

, and complications

p
=
0.628

. Robotic-assisted UKA resulted in more rapid recovery and less early postoperative pain and were more likely to meet expectations than conventional UKA, although functional differences equilibrated by 1 year postoperatively. Further follow-up is necessary to determine if implant durability is impacted by robotics.