bluuebunny/crossref_metadata_2025 huggingface dataset:
Feasibility and acceptability of remote procedures to study tobacco product use and respiratory health: an observational study
Authors: Vogel Erin A , Rebuli Meghan E , Wong Melissa , Leventhal Adam , Monterosso John , Tackett Alayna P
Published: December 2022

Objective

Obtaining ecologically valid biological samples is critical for understanding respiratory effects of tobacco use, but can be burdensome. In two diverse samples, we examined feasibility and acceptability of studying pulmonary function and respiratory health entirely remotely.

Design

Observational feasibility and acceptability study.

Setting and participants

Adults age 18–25 (Biomedical Respiratory Effects Associated through Habitual Use of E-Cigarettes [BREATHE] Study) and 21–65 (Adult IQOS Respiratory [AIRS] Study) recruited from previous research studies and advertisements in Southern California, USA (BREATHE (AIRS): N=77 (N=31) completed baseline, n=64 (n=20) completed feasibility and acceptability measures). Shared inclusion criteria for the two studies were ownership of a smartphone, willingness to download applications and English fluency. In addition, BREATHE participants reported one of three tobacco use patterns. AIRS participants smoked daily and were willing to use a heated tobacco product. Exclusion criteria were medical contraindications.

Interventions

A 4-week study consisted of five virtual study visits, twice daily ecological momentary assessment diaries and spirometry assessments, and weekly Nasal Epithelial Lining Fluid and saliva collection. All study visits were conducted via video conference; study materials and biospecimens were exchanged via mail. Participants reported feasibility and acceptability of daily diaries, breath tests, biospecimen collection and shipments.

Measures

Surveys assessed perceptions of timing and overall experience of daily diaries and breath tests, difficulty of and overall experience with biospecimen collection, and experience sending and receiving shipments.

Results

Most participants evaluated daily diaries and breath tests as manageable (62.5%–95.0%) and likeable (54.7%–70.0%). Breath tests were frequently described as ‘interesting’ (55.0%–57.8%) and ‘easy’ (25.0%–48.4%). Most participants reported that biospecimen collection was easy (50.0%–85.0%), and that shipments were easy to send (87.5%–95.0%), receive (95.3%–95.0%) and schedule (56.3%–60.0%). No participants received shipments in poor condition.

Conclusions

Remote research procedures may be feasible and acceptable to facilitate tobacco research studies, potentially resulting in more diverse samples of participants and more generalisable research results.
Prevalence and predictors of spontaneous preterm births in Nepal: findings from a prospective, population-based pregnancy cohort in rural Nepal–a secondary data analysis
Authors: Subedi Seema , Hazel Elizabeth A , Mohan Diwakar , Zeger Scott , Mullany Luke C , Tielsch James M , Khatry Subarna K , LeClerq Steven C , Black Robert E , Katz Joanne
Published: December 2022

Objective

Preterm birth can have short-term and long-term complications for a child. Socioeconomic factors and pregnancy-related morbidities may be important to predict and prevent preterm births in low-resource settings. The objective of our study was to find prevalence and predictors of spontaneous preterm birth in rural Nepal.

Design

This is a secondary observational analysis of trial data (registration numberNCT01177111).

Setting

Rural Sarlahi district, Nepal.

Participants

40 119 pregnant women enrolled from 9 September 2010 to 16 January 2017.

Outcome measures

The outcome variable is spontaneous preterm birth. Generalized Estimating Equations Poisson regression with robust variance was fitted to present effect estimates as risk ratios.

Result

The prevalence of spontaneous preterm birth was 14.5% (0.5% non-spontaneous). Characteristics not varying in pregnancy associated with increased risk of preterm birth were maternal age less than 18 years (adjusted risk ratio=1.13, 95% CI: 1.02 to 1.26); being Muslim (1.53, 1.16 to 2.01); first pregnancy (1.15, 1.04 to 1.28); multiple births (4.91, 4.20 to 5.75) and male child (1.10, 1.02 to 1.17). Those associated with decreased risk were maternal education >5 years (0.81, 0.73 to 0.90); maternal height ≥150 cm (0.89, 0.81 to 0.98) and being from wealthier families (0.83, 0.74 to 0.93). Pregnancy-related morbidities associated with increased risk of preterm birth were vaginal bleeding (1.53, 1.08 to 2.18); swelling (1.37, 1.17 to 1.60); high systolic blood pressure (BP) (1.47, 1.08 to 2.01) and high diastolic BP (1.41, 1.17 to 1.70) in the third trimester. Those associated with decreased risk were respiratory problem in the third trimester (0.86, 0.79 to 0.94); having poor appetite, nausea and vomiting in the second trimester (0.86, 0.80 to 0.92) and third trimester (0.86, 0.79 to 0.94); and higher weight gain from second to third trimester (0.89, 0.87 to 0.90).

Conclusion

The prevalence of preterm birth is high in rural Nepal. Interventions that increase maternal education may play a role. Monitoring morbidities during antenatal care to intervene to reduce them through an effective health system may help reduce preterm birth.
Homotopy theory of net representations
Authors: Anastopoulos Angelos , Benini Marco
Published: December 2022

The homotopy theory of representations of nets of algebras over a (small) category with values in a closed symmetric monoidal model category is developed. We illustrate how each morphism of nets of algebras determines a change-of-net Quillen adjunction between the model categories of net representations, which is furthermore, a Quillen equivalence when the morphism is a weak equivalence. These techniques are applied in the context of homotopy algebraic quantum field theory with values in cochain complexes. In particular, an explicit construction is presented that produces constant net representations for Maxwell [Formula: see text]-forms on a fixed oriented and time-oriented globally hyperbolic Lorentzian manifold.
Wireless Communication for Drilling Using Acoustic Wave Based on MIMO-OFDM
Authors: Geng Yanfeng , Zheng Zhong
Published: December 2022

Underground data transmission methods are divided into wired and wireless. Wired transmission includes traditional cable and optical fiber. Wireless transmission includes pressure wave and electromagnetic wave. The limitation of the down-hole data upload rate has become the bottleneck. The wireless transmission system of an acoustic wave using a drilling fluid channel is studied. Drilling fluid channel is a multi-path channel with frequency selective fading characteristics. In the process of drilling, the shape of drill string is spatial spiral bending. This paper provides an exhaustive research in OFDM-MIMO for drilling acoustic telemetry system. The characteristics of drilling fluid channel are discussed. The performances of multiple input multiple output (MIMO), multiple input single output (MISO) and single input single output (SISO) wireless acoustic transmission systems are compared. Acoustic waves transmitted along the drilling fluid channel can realize underground wireless communication with a high transmission rate and a low bit error rate.
Tree Social Relations Optimization-Based ReLU-BiLSTM Framework for Improving Video Quality in Video Compression
Authors: Sivakumar K. , Sasikumar S. , Krishnamurthy M.
Published: December 2022

High-Efficiency Video Coding (HEVC) has a higher coding efficiency, its encoding performance must be increased to keep up with the expanding number of multimedia applications. Therefore, this paper proposes a novel Rectified Linear Unit-Bidirectional Long Short-Term Memory-based Tree Social Relations Optimization (ReLU-BiLSTM-based TSRO) method to enhance the quality of video transmission. The significant objective of our proposed method aims in enhancing the standards of entropy encoding process in HEVC. Here, context-adaptive binary arithmetic coding (CABAC) framework which is prevalent and an improved form of entropy coding model is utilized in HEVC standards. In addition to this, the performances of the proposed method are determined by evaluating various measures such as mean square error, cumulative distribution factor, compression ratio, peak signal-to-noise ratio (PSNR) and bit error rate. Finally, the proposed method is examined with five different sequences of video from football, tennis, garden, mobile and coastguard. The performances of the proposed method are compared with various approaches, and the result analysis shows that the proposed method attained minimum mean square error (MSE) loss with maximum PSNR rate.
SEGMENTATION OF MRI IMAGES USING A COMBINATION OF ACTIVE CONTOUR MODELING AND MORPHOLOGICAL PROCESSING
Authors: VEERAMALLA SANTHOSH KUMAR , HINDUMATHI V. , REDDY T. VASUDEVA , PATTAN ANWAR BHASHA , NANDAN T. P. KAUSALYA
Published: December 2022

Image segmentation in brain magnetic resonance imaging (MRI) largely relates to dividing brain tissue into components like white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF). Using the segmentation outputs, medical images can be 3D reconstructed and visualized efficiently. It is common for MRI pictures to have issues such as partial volume effects, asymmetrical grayscale, and noise. As a result, high accuracy in brain MRI picture segmentation is challenging to achieve in practical applications. In this paper, we developed an effective algorithm for brain MRI image segmentation utilizing a combination of statistical and partial differential equation-based approaches, based on a neuro-mechanical model. The findings of this work demonstrate that by combining various segmentation approaches, it is possible to quickly segment brain MRI data at a degree of precision necessary for different applications. Here, we show that when we use nonlinear filtering, [Formula: see text]-means clustering, and active contour modeling, we can get very good results when we segment brain MRI images. It is clear that the proposed approach has higher segmentation performance and can properly separate brain tissue from a large number of MRI images.
THE NEURAL MECHANISM OF PHYSICAL EXERCISE IN PREVENTION AND TREATMENT OF CARDIOVASCULAR DISEASE UNDER DEEP LEARNING
Authors: TU XIAOHONG , XIE QI , XIAO XIANGLIN , YAN KANGYING , ZHANG LONG
Published: December 2022

This work was to explore the application of deep learning (DL) in identifying the neural mechanism of cardiovascular disease (CVD) and the role of physical exercise in the prevention and treatment of CVD. 200 cases of outpatient treatment in the hospital from January to December in 2021 were included as the research objects. 100 people with fitness exercise habits were sorted into the experiment group, and the other 100 cases without fitness exercise habit were in the control group. In addition, a DL-based CVD recognition model was constructed. The results showed that the detection effect of the back propagation (BP) algorithm under DL was better, with an average of over 99%. Heart rate variability (HRV) time domain analysis results showed that the Rrmaen, standard deviation of N-N interval (SDNN), and root mean square of the difference (RMSSD) of the experiment group were [Formula: see text][Formula: see text]ms, [Formula: see text][Formula: see text]ms, and [Formula: see text][Formula: see text]ms, respectively. These were observably higher than those of the control group ([Formula: see text]). In the HRV frequency domain analysis, the total frequency (TF) in the experiment group was [Formula: see text][Formula: see text]MS2, which was notably higher than that in the control group ([Formula: see text][Formula: see text]MS2, [Formula: see text]). The scores of anxiety and depression in the experiment group before exercise intervention were [Formula: see text] and [Formula: see text], respectively, which were highly decreased after intervention ([Formula: see text]). The CVD recognition model based on a DL algorithm could effectively identify CVD. Long-term regular exercise can effectively change the regulatory function of cardiovascular autonomic nerves and depression and anxiety states, which had popularization value.
Closed-form shrinkage function based on mixture of Gauss–Laplace distributions for dropping ambient noise
Authors: Kim Kyong-Il , Kwak Wi-Ung , Choe Kyong-Hyok
Published: December 2022

Removing the ambient noise and increasing the signal-to-noise ratio are very important for detecting defects and corrosions of conductive material by using the electromagnetic acoustic transducer. It is still an issue to remove the ambient noise without losing the original signal information. The aim of this paper is to solve the issue by using a new closed-form shrinkage function based on Gauss–Laplace mixture distribution in wavelet domain. First, we prove that Gauss–Laplace mixture distribution is well fitted to the statistical model for wavelet coefficients of noise-free signal of electromagnetic acoustic transducer. As well, we use Gauss–Laplace mixture distribution and Gauss distribution for statistical modeling on the wavelet coefficients of noise-free signal and ambient noise, respectively. Using these distributions, we derive a new closed-form shrinkage function that is an analytical solution of a Bayesian maximum a posteriori estimator. Next, we evaluate the denoising performance of new shrinkage function compared with various shrinkage functions in terms of the improved signal-to-noise ratio, root mean squared error and entropy. The experiment results show that the wavelet denoising method using the proposed shrinkage function effectively removes the ambient noise than the other existing denoising methods for noisy signal of electromagnetic acoustic transducer.
Injective edge chromatic index of generalized Petersen graph P(ck,k)
Authors: Hu Xiaolan , Legass Belayneh-Mengistu
Published: December 2022

An injective [Formula: see text]-edge coloring of a graph [Formula: see text] is a [Formula: see text]-edge coloring [Formula: see text] of [Formula: see text] such that [Formula: see text] for any three consecutive edges [Formula: see text] and [Formula: see text] of a path or a 3-cycle. The injective edge chromatic index of [Formula: see text], denoted by [Formula: see text], is the minimum [Formula: see text] such that [Formula: see text] has an injective [Formula: see text]-edge coloring. Li and Chen determined the injective edge chromatic index of the generalized Petersen graph [Formula: see text] for [Formula: see text]. In this paper, we consider the injective edge coloring of the generalized Petersen graph [Formula: see text] and show that [Formula: see text] for [Formula: see text].
THE REGIONAL ECONOMIC IMPACTS OF CLIMATE CHANGE ON FAMILY FARMING AND LARGE-SCALE AGRICULTURE IN BRAZIL: A COMPUTABLE GENERAL EQUILIBRIUM APPROACH
Authors: TANURE TARIK MARQUES DO PRADO , DOMINGUES EDSON PAULO , MAGALHÃES ALINE DE SOUZA
Published: December 2022

This paper analyzes the regional economic impacts of climate change (CC) on the agricultural productivity of crops linked to family farming and large-scale agriculture in Brazil. Variations in agricultural productivity estimated according to CC scenarios RCP 4.5 and RCP 8.5 [ IPCC ( 2014 ). Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Core Writing Team, RK Pachauri and LA Meyer (eds.), IPCC, Geneva, Switzerland, 151pp.], between 2021 and 2050, were used as inputs in the Computable General Equilibrium (CGE) model AGRO-BR to project the economic impacts of the phenomenon. The model presents regional configuration composed of the 27 Brazilian Federation Units and 42 agricultural sectors, disaggregated into family farming and large-scale agriculture sectors. The results indicate that the North and Northeast regions would be negatively affected, Midwest and Southeast would suffer moderate impacts, while the South region would benefit mostly. São Paulo, Paraná, and Rio Grande do Sul would show economic growth, softening the negative impacts on national GDP. Regional disparities and the deterioration of food security conditions could increase in Brazil.
Straits and seaways: end members within the continuous spectrum of the dynamic connection between basins
Authors: Rossi Valentina Marzia , Longhitano Sergio G. , Olariu Cornel , Chiocci Francesco L.
Published: December 2022

Straits and seaways are fundamental connectors of oceans, seas and more rarely lakes. They are ubiquitous in the modern geography and should be common in ancient landscapes. We compare their characteristics to improve our understanding of these features, with the aim to define better their geological use.

We review geomorphological, oceanographic, geological and depositional characteristics based on well-documented modern and ancient examples, with a stronger focus on the rock record.

‘Strait’ and ‘seaway’ are differentiated by their spatial and temporal scale. This influences the type and persistence of oceanographic circulation and sediment distribution. Straits are individual depositional systems, with predictable bedform and facies changes along the sediment transport pathway, whereas seaways are larger and longer-lived physiographic domains, composed of numerous depositional systems. Therefore, their stratigraphic signature in the rock record should be significantly different. We conclude that straits and seaways are end members of a continuum, giving rise to the occurrence of intermediate cases with transitional characteristics. The distinctive geological usage of the terms ‘strait’ and ‘seaway’, even without sharp boundaries between end members, may be helpful for predicting their occurrence, stratigraphy, palaeogeography, biota distribution and potential distribution of reservoirs and seals for fossil resources and CO
2
storage.
Stable Matchings with Restricted Preferences: Structure and Complexity
Authors: Cheng Christine T. , Rosenbaum Will
Published: December 2022

In the stable marriage (SM) problem, there are two sets of agents—traditionally referred to as men and women—and each agent has a preference list that ranks (a subset of) agents of the opposite sex. The goal is to find a matching between men and women that is stable in the sense that no man-woman pair mutually prefers each other to their assigned partners. In a seminal work, Gale and Shapley [
16
] showed that stable matchings always exist and described an efficient algorithm for finding one.

Irving and Leather [
24
] defined the rotation poset of an SM instance and showed that it determines the structure of the set of stable matchings of the instance. They further showed that every finite poset can be realized as the rotation poset of some SM instance. Consequently, many problems—such as counting stable matchings and finding certain “fair” stable matchings—are computationally intractable (NP-hard) in general.

In this article, we consider SM instances in which certain restrictions are placed on the preference lists. We show that three natural preference models—
k
-bounded,
k
-attribute, and

(k
1
, k
2
)

-list—can realize arbitrary rotation posets for constant values of
k
. Hence, even in these highly restricted preference models, many stable matching problems remain intractable. In contrast, we show that for any fixed constant
k
, the rotation posets of
k
-range instances are highly restricted. As a consequence, we show that exactly counting and uniformly sampling stable matchings, finding median, sex-equal, and balanced stable matchings, are fixed-parameter tractable when parameterized by the range of the instance. Thus, these problems can be solved in polynomial time on instances of the k-range model for any fixed constant k.
Two Strongly Truthful Mechanisms for Three Heterogeneous Agents Answering One Question
Authors: Schoenebeck Grant , Yu Fang-Yi
Published: December 2022

Peer prediction mechanisms incentivize self-interested agents to truthfully report their signals even in the absence of verification by comparing agents’ reports with their peers. We propose two new mechanisms, Source and Target Differential Peer Prediction, and prove very strong guarantees for a very general setting.

Our Differential Peer Prediction mechanisms are
strongly truthful
: Truth-telling is a strict Bayesian Nash equilibrium. Also, truth-telling pays strictly higher than any other equilibria, excluding permutation equilibria, which pays the same amount as truth-telling. The guarantees hold for
asymmetric priors
among agents, which the mechanisms need not know (
detail-free
) in the
single question setting
. Moreover, they only require
three agents
, each of which submits a
single item report
: two report their signals (answers), and the other reports her forecast (prediction of one of the other agent’s reports). Our proof technique is straightforward, conceptually motivated, and turns on the logarithmic scoring rule’s special properties.

Moreover, we can recast the Bayesian Truth Serum mechanism [
20
] into our framework. We can also extend our results to the setting of
continuous signals
with a slightly weaker guarantee on the optimality of the truthful equilibrium.
Converting a face-to-face neuroanatomy course-based undergraduate research experience (CURE) to an online environment: lessons learned from remote teaching
Authors: D’Arcy Christina E. , Lapsov Leonid , Navarro Vanessa , Nevarez Denise , Olimpo Jeffrey T.
Published: December 2022

Herein, we describe the process of converting a novel, face-to-face neuroanatomy course-based undergraduate research experience (CURE) to an online-only research setting. We document student affective and skill gains resultant from participating in this course and examine best practices for structuring online CUREs to maximize student learning and success.
CGRP physiology, pharmacology, and therapeutic targets: migraine and beyond
Authors: Russo Andrew F. , Hay Debbie L.
Published: December 2022

Calcitonin gene-related peptide (CGRP) is a neuropeptide with diverse physiological functions. Its two isoforms (α and β) are widely expressed throughout the body in sensory neurons as well as in other cell types, such as motor neurons and neuroendocrine cells. CGRP acts via at least two G protein-coupled receptors that form unusual complexes with receptor activity-modifying proteins. These are the CGRP receptor and the AMY1receptor; in rodents, additional receptors come into play. Although CGRP is known to produce many effects, the precise molecular identity of the receptor(s) that mediates CGRP effects is seldom clear. Despite the many enigmas still in CGRP biology, therapeutics that target the CGRP axis to treat or prevent migraine are a bench-to-bedside success story. This review provides a contextual background on the regulation and sites of CGRP expression and CGRP receptor pharmacology. The physiological actions of CGRP in the nervous system are discussed, along with updates on CGRP actions in the cardiovascular, pulmonary, gastrointestinal, immune, hematopoietic, and reproductive systems and metabolic effects of CGRP in muscle and adipose tissues. We cover how CGRP in these systems is associated with disease states, most notably migraine. In this context, we discuss how CGRP actions in both the peripheral and central nervous systems provide a basis for therapeutic targeting of CGRP in migraine. Finally, we highlight potentially fertile ground for the development of additional therapeutics and combinatorial strategies that could be designed to modulate CGRP signaling for migraine and other diseases.
Synthetic Analogs of Antimicrobial Peptides from Limulus Inhibit the Growth of Listeria monocytogenes by Increasing Cell Membrane Permeability and Suppressing Virulence Genes
Authors: Xie Haiwei , Wang Mingyang , Wu Zhongling , Lai Zhantu , Luo Liping , Lin Fengcai , Lei Jia
Published: December 2022

Listeria monocytogenes is a foodborne pathogen that can cause listeriosis in humans and animals. It is of significant concern to the food industry as it can grow at low temperatures. Aggravatingly, only some of the commonly used food preservatives can effectively inhibit the growth of LM. In this study, the effectiveness of synthetic analogs of antimicrobial peptides from Limulus in inhibiting the growth of LM was studied. As determined by the Kirby–Bauer disc diffusion method, the diameters of the inhibition zones produced by the synthetic antimicrobial peptides ranged from 8.24 mm to 8.86 mm, and the minimum inhibitory concentrations (MICs) of the peptides ranged from 40 μg/mL to 160 μg/mL. At their MICs, initially, the synthetic antimicrobial peptides exhibited bacteriostatic effects on LM. They permeabilized the cell membrane of the bacterium and suppressed virulence genes (the inlA, prfA, and hly genes) in the bacterium. However, the bacteriostatic effects were effective only for 1 h, after which the bacterium slowly became resistant to them. After 6 h, the bacterium resumed its growth. Although cells in treatment groups resumed their growth after 6 h, the growth of the cells was inhibited compared to the growth of cells in the control group. Further studies are necessary to reduce the resistance of LM to the antibacterial effects of the synthetic antimicrobial peptides.
Beneficial Effects of Lactic Acid Bacteria on Animal Reproduction Function
Authors: Nur Mahendra Mohamad Yusril , Dadi Tri Bhawono , Kamaludeen Juriah , Pertiwi Herinda
Published: December 2022

Considering the importance of a healthy uterus to the success of breeding, the beneficial effects of lactic acid bacteria on animal reproduction function are of particular interest. In recent decades, infertility has become a widespread issue, with microbiological variables playing a significant role. According to reports, dysbiosis of the vaginal microbiota is connected with infertility; however, the effect of the normal vaginal microbiota on infertility is unknown. In addition, lactic acid bacteria dominate the reproductive system. According to evidence, vaginal lactic acid bacteria play a crucial role in limiting the invasion of pathogenic bacteria by triggering anti-inflammatory chemicals through IL-8, IL-1, and IL-6; immunological responses through inhibition of the adherence of other microorganisms, production of inhibiting substances, and stimulation of mucus production; and also reproductive hormones by increased testosterone hormone release, enhanced the levels of luteinizing hormone, follicle stimulating hormone, the amount of prostaglandin E (2), and prostaglandin F2 alpha. The objective of this study was to compare the advantages of lactic acid bacteria in animal reproduction based on the most recent literature. The administration of a single strain or numerous strains of lactic acid bacteria has a favourable impact on steroidogenesis, gametogenesis, and animal fertility.
Digital Identity Verification and Management System of Blockchain-Based Verifiable Certificate with the Privacy Protection of Identity and Behavior
Authors: Song Zhiming , Wang Guiwen , Yu Yimin , Chen Taowei
Published: December 2022

Due to the advantages in self-sovereignty identity management and scalability of blockchain, digital identity verification and management systems (DIVMS) of blockchain-based verifiable certificates (VC) are getting more and more attention. However, user privacy in the systems’ traditional architectures cannot be guaranteed. In this paper, the zero-knowledge succinct noninteractive arguments of knowledge (zkSNARKs) referred to as Groth16 are introduced in order to implement privacy protection of the user’s identity and behavior of DIVMS of blockchain-based VC. In the proposed architecture, the malleability attack of Groth16 is considered, and verifications of zero-knowledge proof (ZKP) and the digital signature of an identity provider (IDP) attached to VC and the status management of VC are implemented on the smart contracts of the blockchain to overcome single point failure. Furthermore, a prototype system is designed to verify the proposed architecture’s capability in privacy protection and to evaluate its performances in cost and throughput. Finally, the security of the proposed architecture is discussed, and its comparisons are conducted with those existing blockchain-based DIVMSs, especially those systems using Groth16 of zkSNARKs to improve the privacy of user. All results mentioned above have shown that the proposed system is efficient and safe, and it can improve the privacy of DIVMS of the blockchain based VC while avoiding single point failure.
Modeling Behavior of U-Turning Vehicles at the Median Opening Using a Merging Behavior Approach: A Case Study in Bahir Dar City, Ethiopia
Authors: Wolelaw Natnael Melsew , Tessema Amare Tilahun , Alene Getachew Asefa
Published: December 2022

Median openings are one of the most commonly used road features, which are mainly used to allow U-turning movement in urban areas, and this study focuses mainly on modeling the behavior of U-turning vehicles at the median opening using a merging behavior approach. The purpose of the study is to estimate and model the critical gap of u-turning vehicles at the median opening under mixed traffic conditions. Under this study, the accepted gap, rejected gap, driver waiting time, merging time, and critical gap are estimated, and the modified Raff’s method and modified INAFOGA method are used for the estimation of a critical gap. However, modified INAFOGA is used for the modeling of critical gaps under mixed traffic conditions. In this study, sixteen median openings were selected in Bahir Dar city, and data were collected using a video recording technique at each selected median opening during the peak hour of the day. The necessary data were extracted using Forevid analysis software tools. Different types of traffic are involved in the mixed traffic, and each vehicle type is categorized according to the Ethiopian Road Authority’s 2013 design guide into seven different classes, such as 2-wheeler, 3-wheeler, passenger car, minibus, small bus and truck, medium bus, and medium truck. Among those traffic types, three vehicle classes (three-wheeler, passenger car, and minibus) were only considered due to the prohibition of U-turning movement for medium and large vehicles. For the modeling of critical gaps, waiting time and conflicting traffic flow are used as independent variables using the regression technique. Driver waiting time and the critical gap were found to be power related to passenger cars and minibuses and exponentially to three-wheelers. Conflicting traffic flow and critical gaps were power related to passenger cars and minibuses and linearly related to three-wheelers.
Agromorphological Diversity and Disease Assessment of Grain Amaranth in Lamjung, Nepal
Authors: Adhikari Prabha , Joshi Laxmi Prasad , Ayer Dipendra Kumar , Tiwari Khusi Ram
Published: December 2022

Amaranth is a nutritious traditional food and vegetable crop with incomparable health benefits. However, very little research has been carried out to study diversity of amaranth in Nepal. An experiment was conducted in the research field of the Institute of Agriculture and Animal Science (IAAS) at Sundarbazar, Lamjung, Nepal, during 2021 growing season to assess twelve amaranth accessions based on agromorphological characters. Seed materials were collected from the Nepal Agriculture Genetic Resource Center (NAGRC), Khumaltar, and the experiment was conducted in alpha-lattice design with 3 replications. Early maturing accessions had inflorescence at 42.33 days while late maturing accessions were after 82 days. ANOVA test for quantitative traits revealed significant differences among the accessions for all traits studied except stem girth. Similarly, from frequency distribution of agromorphological characters, high variability was found in stem pigmentation, terminal inflorescence shape, inflorescence color, and seed color. Diversity indices (Shannon–Weaver diversity index and Simpson’s index of diversity) were also estimated in which inflorescence color, terminal inflorescence shape, seed color, stem pigmentation, leaf shape, branching index, and leaf pigmentation exhibited high variation confirming the presence of tremendous diversity in Amaranthus. Accessions NGRCO 6977, NGRCO 6969, and NGRCO 6871 had low disease incidence showing the potential of developing resistant varieties through précised breeding in the future. High yield attributing traits were possessed by accessions NGRCO 6977, CO 2435, NGRCO 6904, and CO 1239. Accession NGRCO 6977 was found superior among twelve accessions with highest grain yield and least disease occurrence which can further be evaluated in successive years as a promising variety in mid-hill region.
Optimization for a New XY Positioning Mechanism by Artificial Neural Network-Based Metaheuristic Algorithms
Authors: Dang Minh Phung , Le Hieu Giang , Nguyen Ngoc Phat , Le Chau Ngoc , Dao Thanh-Phong
Published: December 2022

This paper devotes a new method in modeling and optimizing to handle the optimization of the XY positioning mechanism. The fitness functions and constraints of the mechanism are formulated via proposing a combination of artificial neural network (ANN) and particle swarm optimization (PSO) methods. Next, the PSO is hybridized with the grey wolf optimization, namely PSO-GWO, which is applied to three scenarios in handling the single objective function. In order to search the multiple functions for the mechanism, the multiobjective optimization genetic algorithm (MOGA) is applied to the last scenario. The achieved results showed that the fitness functions are well-formulated using the PSO-based ANN method. In the scenario 1, the stroke achieved by the PSO-GWO (1852.9842 μm) is better than that gained from the GWO (1802.8087 μm). In the scenarios 2, the stress gained from the PSO-GWO (243.3183 MPa) is lower than that achieved from the GWO (245.0401 MPa). In the scenario 3, the safety factor retrieved from the PSO-GWO (1.9767) is greater than that achieved from the GWO (1.9278). In the scenario 4, by using MOGA, the optimal results found that the stroke is about (1741.3 μm) and the safety factor is 1.8929. The prediction results are well-fitted with the numerical and experimental verifications. The results of this paper are expected to facilitate the synthesis and analysis of compliant mechanisms and related engineering designs.
Long-Term Suitability of Left Gastric Artery Inflow for Arterial Perfusion of Living Donor Right Lobe Grafts
Authors: Lipinska Judyta A. , Wang Johnny , Carey Joseph N. , Ahearn Aaron A. , Genyk Yuri S.
Published: December 2022

Poorer than expected, living donor liver transplant outcomes are observed after recipient graft artery thrombosis. At grafting, the risk for later thrombosis is high if a dissected hepatic artery is used for standard reconstruction. Surgeon diagnosis of dissection requires nonstandard management with alternative technique in addition to microvascular expertise. Intimal flap repair with standard reconstruction is contingent on basis of a redo anastomosis. It is a suboptimal choice for living donor transplantation. Achieving goal graft arterial perfusion at first revascularization is crucial for superior outcomes. Managing dissection at grafting with nonstandard left gastric artery reconstruction is unreported. Our experience is limited, but this is our preferred alternative technique to standard hepatic artery reconstruction complicated by dissection. Here, we describe our two-case experience with left gastric arterialized grafts for management of dissection. Our living donor graft recipients with alternatively arterialized grafts are now 6- and 2-years posttransplant.
A Review of the Advancement in Speech Emotion Recognition for Indo-Aryan and Dravidian Languages
Authors: Alam Monisha Syeda Tamanna , Sultana Sadia
Published: December 2022

Speech emotion recognition (SER) has grown to be one of the most trending research topics in computational linguistics in the last two decades. Speech being the primary communication medium, understanding the emotional state of humans from speech and responding accordingly have made the speech emotion recognition system an essential part of the human-computer interaction (HCI) field. Although there are a few review works carried out for SER, none of them discusses the development of SER system for the Indo-Aryan or Dravidian language families. This paper focuses on some studies carried out for the development of an automatic SER system for Indo-Aryan and Dravidian languages. Besides, it presents a brief study of the prominent databases available for SER experiments. Some remarkable research works on the identification of emotion from the speech signal in the last two decades have also been discussed in this paper.
Abstract B013: Loss of the extracellular domain of human epidermal growth factor receptor 2 (HER2) p95 isoform is common in large DCIS lesions
Authors: Schindler Nicole F. , Glencer Alexa , Mori Hidetoshi , Hirst Gillian , Rodas Cristian Maldonado , Campbell Michael , Esserman Laura , Borowsky Alexander
Published: December 2022

Background/Aim: Testing for human epidermal growth factor receptor 2 (HER2) positivity in women diagnosed with ductal carcinoma in situ (DCIS) is not performed routinely, although the frequency of HER2+ DCIS is at least 30%. HER2+ DCIS lesions may be at higher risk of progression to invasive carcinoma, and specific isoforms of HER2 may lead to different malignant potential. Loss of the HER2 extracellular domain engineered in mouse models demonstrates rapid progression to invasive behavior. Evaluating isoforms of HER2 may aid in classifying DCIS lesions as higher or lower risk, and may provide insight for novel treatment and prevention approaches. Methods: A cohort of high risk DCIS cases were assembled, enriched for the presence of high risk features, including large size (>5 cm) and palpable. Immunohistochemistry (IHC) and FISH were used to identify cases that were HER2 positive. MultiplexIHC was used to detect extracellular and intracellular domains of HER2, with imaging analysis performed to identify HER2 isoforms of HER2+ specimens. Isoforms were characterized as 1) full-length/extracellular domain (ECD) intact, 2) pure/complete loss of ECD (p95 isoform), 3) subclonal populations of both full-length ECD and p95 and 4) gradient/representing partial loss of ECD per cell (reflecting post-translational cleavage). Results: Out of 51 cases, 34 (67%) cases were HER2+. In multiplexIHC analysis for HER2, 51% displayed gradient (partial) or focal (subclonal) loss of the extracellular domain. 33% displayed pure p95 isoform (complete loss of ECD). Only 16% of the cohort displayed full-length HER2 extracellular domain. Conclusions: HER2 expression is much more common in large in situ lesions than in invasive lesions. This suggests that HER2 positivity may play a role in protecting against invasion. Investigation of HER2 Isoform testing using multiplex staining reveals heterogeneity with partial or complete loss of the HER2 extracellular domain being most common. Loss of the extracellular domain of human epidermal growth factor receptor 2 (HER2) p95 isoform is predominant among patients diagnosed with HER2 positive ductal carcinoma in situ (DCIS).

Citation Format: Nicole F. Schindler, Alexa Glencer, Hidetoshi Mori, Gillian Hirst, Cristian Maldonado Rodas, Michael Campbell, Laura Esserman, Alexander Borowsky. Loss of the extracellular domain of human epidermal growth factor receptor 2 (HER2) p95 isoform is common in large DCIS lesions [abstract]. In: Proceedings of the AACR Special Conference on Rethinking DCIS: An Opportunity for Prevention?; 2022 Sep 8-11; Philadelphia, PA. Philadelphia (PA): AACR; Can Prev Res 2022;15(12 Suppl_1): Abstract nr B013.
Abstract PR003: Pioneering genetic rat models of Ductal Carcinoma in situ (DCIS)
Authors: Lutz Catrin , Badoux Madelon , Eijkman Timo , de Klein Bim , Song Ji-Ying , Henneman Linda , Scheele Colinda , Wesseling Jelle , Jonkers Jos
Published: December 2022

DCIS has been virtually unknown before the introduction of breast cancer screening programs in the 1980s. Since then, its incidence has been rising steeply and it now accounts for about 25% of all newly diagnosed ‘breast cancer’ cases. Despite the increase in occurrence, the molecular underpinnings regulating DCIS initiation and progression remain elusive. In addition, almost all DCIS cases are hormone dependent, a characteristic which remains one of the biggest challenges to recapitulate in breast cancer research. We could successfully establish models for DCIS as well as estrogen receptor positive disease subtypes by somatically engineering the rat mammary gland via intraductal injection of lentiviral vectors encoding for the most commonly mutated genes (Ccnd1, Myc, Pik3ca and p53) in (pre-) breast cancer. Models with one perturbed gene remained mostly mammary tumor-free after an observation period of 18 months. However, when perturbed in two loci, animals showed mammary lesion formation within 5 and after up to 40 weeks. Histopathological analysis of these lesions characterized a broad spectrum of tumor types including ductal and lobular carcinomas, with both in situ and invasive phenotypes. Among these tumor types, DCIS lesions as well as invasive ductal carcinoma showed estrogen receptor positivity after immunohistochemical staining. Two distinct growth patterns were observed: a flat growing tumor, shaped by, and replacing the host rat mammary duct, and a round growing lesion, disregarding ductal structures. Interestingly, the flat growing tumor pattern evolved mostly in models expressing luminal drivers (Ccnd1 and Pik3ca) and strongly correlated with in situ growth. To increase luminal subtypes and to narrow down the broad tumor spectrum observed in these models, we generated a luminal cell type-specific promoter expressing our genes of interest. Pathological analysis of the arisen tumors indeed revealed a more homogeneous tumor subtype for all models, with an average tumor latency of 28 to 40 weeks. These genetically engineered models for DCIS and estrogen receptor positive breast cancer may aid in an improved treatment stratification by distinguishment between indolent and aggressive DCIS, a persisting challenge as of today. Additionally, these models broaden the scope of available hormone dependent breast cancer models, benefitting the search for novel treatment regiments for patients suffering from this breast cancer subtype.

Citation Format: Catrin Lutz, Madelon Badoux, Timo Eijkman, Bim de Klein, Ji-Ying Song, Linda Henneman, Colinda Scheele, Jelle Wesseling, Jos Jonkers. Pioneering genetic rat models of Ductal Carcinoma in situ (DCIS) [abstract]. In: Proceedings of the AACR Special Conference on Rethinking DCIS: An Opportunity for Prevention?; 2022 Sep 8-11; Philadelphia, PA. Philadelphia (PA): AACR; Can Prev Res 2022;15(12 Suppl_1): Abstract nr PR003.
Abstract IA007: PREVENT agent development pipeline
Authors: Miller Mark Stevn , Cholewa Brian , Clifford John , Gunasekharan Vignesh , Mohammed Altaf , Gupta Shanker , Shoemaker Robert , Sei Shizuko
Published: December 2022

The NCI’s PREVENT Cancer Preclinical Drug Development Program is a peer-reviewed program designed to support the preclinical development of promising agents and biomarkers for cancer interception/prevention towards clinical applications. PREVENT is not a grant program but allocates NCI contract resources to advance approved projects in a milestone-driven manner. Results obtained through NCI contract resources are returned to the applicant PIs and used to support further development by the applicants or in partnership with NCI. Resources available to PREVENT Program applicants include preclinical efficacy testing, CGMP manufacturing, GLP pharmacokinetic and IND-enabling toxicology studies, and IND filings. The PREVENT Program is focused on preventive agent development in the areas of Immunoprevention (cancer vaccines and immunomodulatory agents), Chemoprevention (novel mechanisms, anti-inflammatory agents, drug repurposing, toxicity reduction via alternative dosing regimens and agent combinations) and clinically translatable mechanistic biomarkers (pharmacodynamics, immune correlates, and tumor preventive efficacy). Submission deadlines for PREVENT Concept Applications occur twice per year on the second Monday in January and July. Further information can be obtained at the PREVENT Program website: https://prevention.cancer.gov/major-programs/prevent-cancer-preclinical

Citation Format: Mark Stevn Miller, Brian Cholewa, John Clifford, Vignesh Gunasekharan, Altaf Mohammed, Shanker Gupta, Robert Shoemaker, Shizuko Sei. PREVENT agent development pipeline [abstract]. In: Proceedings of the Second Biennial NCI Meeting: Translational Advances in Cancer Prevention Agent Development (TACPAD); 2022 Sep 7-9. Philadelphia (PA): AACR; Can Prev Res 2022;15(12 Suppl_2): Abstract nr IA007.
Abstract IA015: Immunoprevention of triple negative breast cancer by TOP2A derived peptide vaccination
Authors: Lee Sang Beom , Pan Jing , Xiong Donghai , Palen Katie , Johnson Bryon , Green Jeffrey E. , Sei Shizuko , Shoemaker Robert H. , Lubet Ronald A. , Wang Yian , You Ming
Published: December 2022

Top2A is a key enzyme involved in DNA replication and is a therapeutic target for several cancer types including breast cancer. Overexpression of Top2A has been observed in both human and mouse triple-negative breast cancer (TNBC). The present study evaluated both immunogenicity and antitumor efficacy of a newly formulated multi-peptide vaccine targeting multiple epitopes of the Top2A protein. Top2A-specific MHC II epitopes with optimal binding affinity were identified using a combined scoring system, which predicted their potential to elicit a Th1 immune response. The formulated vaccine contained top three Top2A peptides, which elicited the strongest immunologic response and showed 100% sequence homology between human and mouse. Anti-tumor efficacy of the Top2A vaccine was initially evaluated in a syngeneic TNBC mouse model, in which pre-graft preventive vaccination was associated with significantly decreased tumor growth as compared to the adjuvant controls. The Top2A peptide vaccine exhibited striking efficacy in a genetically engineered TNBC mouse model (C3(1)/Tag), reducing tumor burden by >90% when compared with adjuvant alone. Splenocytes collected from vaccinated animals showed a robust immunologic response to the immunizing peptides. There were no overt toxicities observed with the Top2A vaccination. To explore potential mechanisms underlying the anti-tumor response induced by Top2A vaccine treatment, scTCR-seq of tumors in both control and Top2A vaccine groups revealed new T cell clones as a consequence of Top2A vaccination. Furthermore, in vitro stimulation of these splenocytes by the vaccinated Top2A peptides resulted in the secretion of cytokines indicative of Th1 responses but with minimal secretion of Th2-related cytokines. Our data indicate that the newly developed multi-peptide Top2A vaccine is immunogenic and efficacious in the prevention of TNBC development and progression in vivo.

Citation Format: Sang Beom Lee, Jing Pan, Donghai Xiong, Katie Palen, Bryon Johnson, Jeffrey E. Green, Shizuko Sei, Robert H. Shoemaker, Ronald A. Lubet, Yian Wang, Ming You. Immunoprevention of triple negative breast cancer by TOP2A derived peptide vaccination [abstract]. In: Proceedings of the Second Biennial NCI Meeting: Translational Advances in Cancer Prevention Agent Development (TACPAD); 2022 Sep 7-9. Philadelphia (PA): AACR; Can Prev Res 2022;15(12 Suppl_2): Abstract nr IA015.