bluuebunny/crossref_metadata_2025 huggingface dataset:
Finite Element Simulation of Fiber Reinforced Composites Under Bi-Axial Loading
Authors: Gomez Calvin , Dunn Mitchell , Veidt Martin , Reiner Johannes
Published: February 2023

Advances in testing of composite materials in recent years have mostly resulted in the ability to actively characterize the uniaxial response of composites while investigations of multiaxial load cases are rare due to various challenges. One of these challenges is the lack of a suitable specimen geometry for multiaxial testing without unwanted failure modes. Ideally, such geometry should be developed and assessed virtually by means of simulation before costly and time-consuming manufacturing and testing. Therefore, reliable, and efficient simulation methods are required that incorporate the evolution of damage in FRP composites.

This study investigates various geometric features virtually of cruciform specimens to test fiber-reinforced composites subjected to in-plane biaxial tensile loadings. The goal is to achieve uniform failure in the gauge region of the specimen due to biaxial stress states and to reduce any premature failure outside the gauge region. Efficient finite element simulation in the commercial software LS-DYNA is used to identify the optimal geometric features.
On irrationality criteria for the Ramanujan summation of certain series
Authors: Khurana Suraj Singh
Published: February 2023

In this paper, we prove a criterion for the irrationality of certain constants which arise from the Ramanujan summation of a family of infinite divergent sums. As an application, we provide a sufficient criterion for the irrationality of the values of the Riemann zeta function in the interval [Formula: see text]. We further see that our discussion leads to a natural generalization of a result of Sondow on the irrationality criterion for the Euler–Mascheroni constant.
First moment of central values of quadratic Hecke L-functions in the Gaussian field
Authors: Gao Peng , Zhao Liangyi
Published: February 2023

We evaluate the smoothed first moment of central values of a family of quadratic Hecke [Formula: see text]-functions in the Gaussian field using the method of double Dirichlet series. The asymptotic formula we obtain has an error term of size [Formula: see text] under the generalized Riemann hypothesis. The same approach also allows us to obtain asymptotic formulas for all [Formula: see text], [Formula: see text] for a smoothed double character sum involving [Formula: see text], where [Formula: see text] denotes the quadratic symbol in the Gaussian field.
Specialization of Mordell–Weil ranks of abelian schemes over surfaces to curves
Authors: Keller Timo
Published: February 2023

Using the Shioda–Tate theorem and an adaptation of Silverman’s specialization theorem, we reduce the specialization of Mordell–Weil ranks for abelian varieties over fields finitely generated over infinite finitely generated fields [Formula: see text] to the specialization theorem for Néron–Severi ranks recently proved by Ambrosi in positive characteristic. More precisely, we prove that after a blow-up of the base surface [Formula: see text], for all vertical curves [Formula: see text] of a fibration [Formula: see text] with [Formula: see text] from the complement of a sparse subset of [Formula: see text], the Mordell–Weil rank of an abelian scheme over [Formula: see text] stays the same when restricted to [Formula: see text].
Efficient Distributed Energy Resource Voltage Control Using Ensemble Deep Reinforcement Learning
Authors: Obert James , Trevizan Rodrigo D. , Chavez Adrian
Published: February 2023

To meet the challenges of low-carbon power generation, distributed energy resources (DERs) such as solar and wind power generators are now widely integrated into the power grid. Because of the autonomous nature of DERs, ensuring properly regulated output voltages of the individual sources to the grid distribution system poses a technical challenge to grid operators. Stochastic, model-free voltage regulation methods such as deep reinforcement learning (DRL) have proven effective in the regulation of DER output voltages; however, deriving an optimal voltage control policy using DRL over a large state space has a large computational time complexity. In this paper, we illustrate a computationally efficient method for deriving an optimal voltage control policy using a parallelized DRL ensemble. Additionally, we illustrate the resiliency of the control ensemble when random noise is introduced by a cyber-adversary.
Cortisol Biosensors: From Sensing Principles to Applications
Authors: Tanaka Yuki , Mohamed Salleh Nur Asinah binte , Aung Khin Moh Moh , Su Xiaodi , Sutarlie Laura
Published: February 2023

Stress detection and monitoring have attracted substantial research interests due to stress being a risk factor for health disorders and economic burdens. In particular, the steroid hormone cortisol plays an important role both as an indicator of stress and a coordinator of downstream physiological responses. Recent years have witnessed a flourishing of cortisol biosensors and bioassays based on various physical principles. In this review, we first provide an overview of cortisol function and its presence in different biological matrices. Next, we discuss the existing range of cortisol biosensors, from their sensing principles (i.e. chromogenic, nanoparticle-based colorimetric and fluorometric, surface-enhanced Raman spectroscopy, surface plasma resonance spectroscopy, and electrochemical sensors), performances (sensitivity, selectivity, portability, etc.), and applications. We particularly correlate the sensing performances and their suitability for point-of-care diagnostics with sensor principles and the use of different affinity ligands, such as antibodies, aptamers, molecular imprint, and even 2D materials such as MXenes. Finally, we discuss the challenges and perspectives of future high-performing cortisol sensors for a wider range of applications in human and animal stress monitoring.
Comparison of main and accompanying metals distribution patterns in newly documented deposits of the Northern Copper Belt in Poland
Authors: Pietrzela Alicja , Bieńko Tomasz
Published: February 2023

Three new world-class sediment-hosted stratiform copper deposits have recently been documented in SW Poland, in the deep parts of the Fore-Sudetic Monocline: Nowa Sól, Sulmierzyce North and Mozów. Along with the adjacent prognostic areas, these deposits form an extensive west–east-trending belt, distant from the well-known deposits of the Sieroszowice–Lubin area and referred to as the Northern Copper Belt. This major discovery was a result of an exploration program performed by the Canadian Miedzi Copper Corporation, which involved studies of archival data and the company's own drilling program. Investigation of the core material included microscopic observations of thin sections and chemical analyses using inductively coupled plasma (ICP) mass spectrometry and/or ICP optical emission spectrometry. The aim of this study was to compare available geochemical data from the documented deposits and determine the distribution patterns of the main and accompanying metals. Particular attention was paid to Cu, Ag, Pb, Zn, Co, Ni, Mo, V and Au. Each of the studied deposits is characterized by a different position of the ore mineralization in the lithological profile. Average concentrations of the analysed elements and their distribution in the ore series, both vertically and laterally, indicate that distinct mineralizing systems were responsible for the formation of each orebody. Among the main factors influencing metal distribution in the analysed deposits are: the spatial range of the epigenetic, oxidized
Rote Fäule
facies; composition and thickness of the source rocks for the mineralizing brines; and tectonics.
A Human-centered Evaluation of a Toxicity Detection API: Testing Transferability and Unpacking Latent Attributes
Authors: Muralikumar Meena Devii , Yang Yun Shan , McDonald David W.
Published: February 2023

Perspective is a publicly available, machine learning API that can score text for toxicity. It is available for use in online platforms and communities to limit toxicity and promote civil dialogue. In this work, we adopt a human-centered approach to evaluating Perspective by investigating if human ratings of toxicity align with Perspective’s toxicity scores. We also test its transferability by making this comparison for comments from three platforms that have different commenting styles and moderation strategies: news websites, YouTube, and Twitter. Apart from toxicity, the main attribute, we collect participant ratings for three additional attributes: respectfulness, formality, and presence of stereotypes. While disrespect is part of how Perspective defines toxicity, formality and presence of stereotypes were included in the study to explore if they could be hidden/latent attributes that affect toxicity scores from Perspective. We analyzed how participant ratings for these additional attributes vary with respect to Perspective’s toxicity score for comments from each platform. We find that for high toxicity scores, Perspective strongly aligns with participant ratings of toxicity and disrespectfulness across all three platforms, providing weak evidence of its transferability. However, our evaluation also surfaced formality and presence of stereotypes as latent attributes that are unrecognized parts of Perspective’s scores. We discuss how and why this evaluation is “human-centered,” the importance of conducting such evaluations, and implications of these results for content moderation in social platforms.
Knowledge-based Data Processing for Multilingual Natural Language Analysis
Authors: Jain Deepak Kumar , Eyre Yamila GarcÍa-MartÍnez , Kumar Akshi , Gupta Brij B. , Kotecha Ketan
Published: February 2023

Natural Language Processing (NLP) aids the empowerment of intelligent machines by enhancing human language understanding for linguistic-based human-computer communication. Recent developments in processing power, as well as the availability of large volumes of linguistic data, have enhanced the demand for data-driven methods for automatic semantic analysis. This paper proposes multilingual data processing using feature extraction with classification using deep learning architectures. Here, the input text data has been collected based on various languages and processed to remove missing values and null values. The processed data has been extracted using Histogram Equalization based Global Local Entropy (HEGLE) and classified using Kernel-based Radial basis Function (Ker_Rad_BF). These architectures could be utilized to process natural language. We present solutions to the multilingual sentiment analysis issue in this research article by implementing algorithms, and we compare precision factors to discover the optimum option for multilingual sentiment analysis. For the HASOC dataset, the proposed HEGLE_ Ker_Rad_BF achieved an accuracy of 98%, a precision of 97%, a recall of 90.5%, an f-1 score of 85%, RMSE of 55.6%, and a loss curve analysis attained 44%. For the TRAC dataset, the accuracy of 98%, the precision attained is 97%, the Recall is 91%, the F-1 score is 87%, and the RMSE of the proposed neural network is 55%.
A Heterogeneous Parallel Computing Approach Optimizing SpTTM on CPU-GPU via GCN
Authors: Wang Haotian , Yang Wangdong , Ouyang Renqiu , Hu Rong , Li Kenli , Li Keqin
Published: February 2023

Sparse Tensor-Times-Matrix (SpTTM)
is the core calculation in tensor analysis. The sparse distributions of different tensors vary greatly, which poses a big challenge to designing efficient and general SpTTM. In this paper, we describe SpTTM on CPU-GPU heterogeneous hybrid systems and give a parallel execution strategy for SpTTM in different sparse formats. We analyze the theoretical computer powers and estimate the number of tasks to achieve the load balancing between the CPU and the GPU of the heterogeneous systems. We discuss a method to describe tensor sparse structure by graph structure and design a new graph neural network SPT-GCN to select a suitable tensor sparse format. Furthermore, we perform extensive experiments using real datasets to demonstrate the advantages and efficiency of our proposed input-aware slice-wise SpTTM. The experimental results show that our input-aware slice-wise SpTTM can achieve an average speedup of 1.310 × compared to ParTI! library on a CPU-GPU heterogeneous system.
A Survey on Event-Based News Narrative Extraction
Authors: Keith Norambuena Brian Felipe , Mitra Tanushree , North Chris
Published: February 2023

Narratives are fundamental to our understanding of the world, providing us with a natural structure for knowledge representation over time. Computational narrative extraction is a subfield of artificial intelligence that makes heavy use of information retrieval and natural language processing techniques. Despite the importance of computational narrative extraction, relatively little scholarly work exists on synthesizing previous research and strategizing future research in the area. In particular, this article focuses on extracting news narratives from an event-centric perspective. Extracting narratives from news data has multiple applications in understanding the evolving information landscape. This survey presents an extensive study of research in the area of event-based news narrative extraction. In particular, we screened more than 900 articles, which yielded 54 relevant articles. These articles are synthesized and organized by representation model, extraction criteria, and evaluation approaches. Based on the reviewed studies, we identify recent trends, open challenges, and potential research lines.
Guided Depth Map Super-Resolution: A Survey
Authors: Zhong Zhiwei , Liu Xianming , Jiang Junjun , Zhao Debin , Ji Xiangyang
Published: February 2023

Guided depth map super-resolution (GDSR), which aims to reconstruct a high-resolution depth map from a low-resolution observation with the help of a paired high-resolution color image, is a longstanding and fundamental problem that has attracted considerable attention from computer vision and image processing communities. Myriad novel and effective approaches have been proposed recently, especially with powerful deep learning techniques. This survey is an effort to present a comprehensive survey of recent progress in GDSR. We start by summarizing the problem of GDSR and explaining why it is challenging. Next, we introduce some commonly used datasets and image quality assessment methods. In addition, we roughly classify existing GDSR methods into three categories: filtering-based methods, prior-based methods, and learning-based methods. In each category, we introduce the general description of the published algorithms and design principles, summarize the representative methods, and discuss their highlights and limitations. Moreover, depth-related applications are introduced. Furthermore, we conduct experiments to evaluate the performance of some representative methods based on unified experimental configurations, so as to offer a systematic and fair performance evaluation to readers. Finally, weconclude this survey with possible directions and open problems for further research. All related materials can be found at
https://github.com/zhwzhong/Guided-Depth-Map-Super-resolution-A-Survey
.
Multiomics uncover the proinflammatory role of Trpm4 deletion after myocardial infarction in mice
Authors: Boukenna Mey , Rougier Jean-Sébastien , Aghagolzadeh Parisa , Pradervand Sylvain , Guichard Sabrina , Hämmerli Anne-Flore , Pedrazzini Thierry , Abriel Hugues
Published: February 2023

Deletion of Trpm4 increases markers of cardiac and systemic inflammation within the first 24 h after MI, while inducing an earlier fibrotic transition at 72 h and more overall chronic fibrosis and angiogenesis at 5 wk. The descriptive, robust, and methodologically broad approach of this study sheds light on an important caveat that will need to be taken into account in all future therapeutic attempts to inhibit TRPM4 post-MI.
Study on Volleyball‐Movement Pose Recognition Based on Joint Point Sequence
Authors: Li Xi
Published: February 2023

With the high‐speed operation of society and the increasing development of modern science, people’s quality of life continues to improve. Contemporary people are increasingly concerned about their quality of life, pay attention to body management, and strengthen physical exercise. Volleyball is a sport that is loved by many people. Studying volleyball postures and recognizing and detecting them can provide theoretical guidance and suggestions for people. Besides, when it is applied to competitions, it can also help the judges to make fair and reasonable decisions. At present, pose recognition in ball sports is challenging in action complexity and research data. Meanwhile, the research also has an important application value. Therefore, this article studies human volleyball pose recognition by combining the analysis and summary of the existing human pose recognition studies based on joint point sequences and long short‐term memory (LSTM). This article proposes a data preprocessing method based on the angle and relative distance feature enhancement and a ball‐motion pose recognition model based on LSTM‐Attention. The experimental results show that the data preprocessing method proposed here can further improve the accuracy of gesture recognition. For example, the joint point coordinate information of the coordinate system transformation significantly improves the recognition accuracy of the five ball‐motion poses by at least 0.01. In addition, it is concluded that the LSTM‐attention recognition model is not only scientific in structure design but also has considerable competitiveness in gesture recognition performance.
Cement Transport Vehicle Routing with a Hybrid Sine Cosine Optimization Algorithm
Authors: Pham Vu Hong Son , Nguyen Van Nam
Published: February 2023

This study will solve the classical vehicle routing problem, the goal is to generate k trips with the shortest distance for h customers with predetermined locations and needs.. The proposed solution to the classical vehicle routing problem is a hybrid sine cosine algorithm. The sine cosine algorithm is hybridized with the grey wolf optimizer, which is used in combination with the methods of tournament selection, opposition learning, and the mutation and crossover method to build the optimal routing plan for the means of transporting cement. To demonstrate the advantages of the developed hybrid sine cosine algorithm, this algorithm is evaluated and compared with modern algorithms such as sine cosine algorithm, dragonfly algorithm, grey wolf optimizer, ant lion optimizer, particle swarm optimization, modified hybrid particle swarm optimization, genetic algorithm, and the double-population genetic algorithm in case studies. The hybrid sine cos algorithm gives optimal results in these cases because it balances mining and exploration. Thus, the results of this study indicate that managers can use the developed hybrid sine cosine algorithm to create optimal vehicle routing plans to reduce transportation distances.
The Experience of Alcohol and Drug Recovery Service Staff Working with Mothers Who Have Had Their Children Removed
Authors: McFarline Sarah , White Naomi , Russell Lynda
Published: February 2023

Parenting can be impacted by substance misuse, and children can be at risk of maltreatment, leading to their removal from their mothers. Successful treatment of substance abuse relies on these women gaining effective support from services. Previous research has demonstrated the impact working in this field can have on staff, including high staff turnover, vicarious trauma, and burnout. The present study further explores the experience of staff members working in a Drug and Alcohol Recovery Service in Scotland who work with mothers who have had their children removed. Six interviews with nurses and social care workers were analysed using interpretive phenomenological analysis (IPA). Two superordinate themes were developed from the data: (1) complexity and tension within working relationships and (2) emotional experiences and attempts to resolve them. Participants described the complexity of their roles, including the dual role of supporting mothers while also being involved in the child removal process by providing reports and evidence and how they respond and work with mothers after removal and conflicts with the wider system. They also highlighted their attempts to cope with the emotional impact of being part of this process and the empathy they have with mothers, especially when they are parents themselves, and described the complexities of trying to cope and manage when working in this challenging area. Clinical implications, including training needs and requirements, are discussed.
Study on Damage Mechanism of Waterflooding Development in Weizhou 11-4N Low-Permeability Oilfield
Authors: Zhang Yi , Zhu Pengyu , Wei Feng , Xue Guoqing , Tang Mingguang , Zhang Congdi , Wang Rui
Published: February 2023

Weizhou 11-4N oilfield is a medium-low-porosity and low-permeability reservoir. The oilfield was initially developed by edge and bottom water energy and then transferred to water injection development. Affected by poor physical properties and heterogeneity of the reservoir, the oilfield appeared in the process of water injection development. When the water injection pressure increases, the water injection volume continues to decrease, and it is difficult to meet the injection requirements. On the basis of the analysis of reservoir heterogeneity, void structure, and clay minerals of reservoir, the water injection compatibility experiment, damage evaluation experiment, and nuclear magnetic resonance-velocity sensitivity experiments were carried out to clarify the damage in the process of oilfield water flooding development. Experiments show that the main causes of damage in Weizhou 11-4N oilfield water flooding development process are water quality incompatibility and strong velocity-sensitive damage. The determination of water type shows that the injected water and formation water are MgCl2 water type and NaHCO3 water type, respectively, under the classification of Surin water type, resulting in the formation of scale with calcium carbonate as the main component in the reservoir. Incompatibility of water quality is an important cause of reservoir damage and scaling. In the reservoir-sensitive flow experiment, the experimental core showed strong velocity sensitivity, the average velocity sensitivity damage rate was 466.31%, and the average critical velocity was 2.98 m/d. Nuclear magnetic resonance experiments show that the core has a significant decrease in average pore size after water flooding. The main damage range is the tiny throat of 0-2 μm. In this paper, the main damage interval of velocity-sensitive damage in the Weizhou 11-4N area and the change trend of void structure after velocity-sensitive experiment are clarified by nuclear magnetic resonance and velocity sensitivity experiments. The main cause of block reservoir damage provides the basis for the oilfield to take targeted measures and provides a guarantee for the efficient development of the subsequent oilfield.
miR-9a-5p Protects Ischemic Stroke by Regulating Oxidative Stress and Mitochondrial Autophagy
Authors: Ma Chunli , Gao Qing , Zhang Li , Wu Geng , Li Chao , Chen Jun , Fu Yuxuan , Yang Lei
Published: February 2023

Purpose. Present research is aimed at exploring the effect of miR-9a-5p on mitochondrial autophagy and alleviating cellular oxidative stress injury in ischemic stroke. Methods. SH-SY5Y cells were cultured with oxygen-glucose deprivation/reoxygenation (OGD/R) to simulate ischemia/reperfusion. The cells were treated in an anaerobic incubator (95% N2, 5% CO2) for 2 h and then reoxygenated in the normoxic condition for 24 h with 2 ml of normal medium. Cells were transfected with miR-9a-5p mimic/inhibitor or negative control. The RT-qPCR assay was utilized to measure the mRNA expression. Western blot was utilized to evaluate the protein expression. The CCK-8 assay was conducted to detect cell viability. Flow cytometry was applied to examine apoptosis and the cell cycle. The ELISA assay was applied to measure the contents of SOD and MDA in mitochondria. Autophagosomes were observed via electron microscopy. Results. By comparison with the control group, the miR-9a-5p expression in the OGD/R group obviously declined. Mitochondrial crista breaks, vacuole-like changes, and increased autophagosome formation were observed in the OGD/R group. OGD/R injury enhanced oxidative stress damage and mitophagy. When transfected with the miR-9a-5p mimic, mitophagosome production of SH-SY5Y cells decreased and oxidative stress injury was inhibited. However, the miR-9a-5p inhibitor obviously increased mitophagosome production and enhanced oxidative stress injury. Conclusion. miR-9a-5p protects against ischemic stroke by inhibiting OGD/R-induced mitochondrial autophagy and alleviating cellular oxidative stress injury.
Conflict Judgment and Safety Assessment at Unsignalized Intersections Based on Machine Vision
Authors: Wang Yuqiong , Wang Liming , Zhu Ruoyu , Xu Yi , Jiang Guoxin , Ma Xiaotian
Published: February 2023

This article aims to explore an effective method for reducing vehicle collisions at unsignalized intersections. First, a monocular-binocular vision switching system is built to enable machine vision-based detection of obstacle vehicles in the left and right front directions. Then, the motion state and trajectory of each obstacle vehicle are predicted, and the intersection points of the trajectories of the obstacle vehicle and the ego vehicle are calculated. On this basis, a cross-conflict judgment model based on trajectories and collision times and a safety assessment model based on safety distance are established. Finally, the conflict judgment and safety assessment for the obstacle vehicles are simulated. The results of the simulation demonstrate that the monocular-binocular vision switching system proposed in this article can achieve a detection accuracy of 95%, a ranging accuracy of 96%, and a cross-conflict detection accuracy of 97%, while ensuring a maximum detection area, which can meet the requirements of traffic safety assurance at unsignalized intersections.
Information Security Protection of Internet of Energy Using Ensemble Public Key Algorithm under Big Data
Authors: Lin Baode , Geng Zhenwei , Yu Fengrong
Published: February 2023

This work aims to solve the specific problem in the Power Internet of Things (PIoT). PIoT is vulnerable to monitoring, tampering, forgery, and other attacks during frequent data interaction under the background of big data, leading to a severe threat to the power grid’s Information Security (ISEC). Cryptosystems can solve ISEC problems, such as confidentiality, data integrity, authentication, identity recognition, data control, and nonrepudiation. Thereupon, this work expounds on cryptography from public-key encryption and digital signature and puts forward the model of network information attack. Then, the security of the two cryptograms is certified against the two cyberattack modes. On this basis, an Identity-based Combined Encryption and Signature (IBCES) ensemble scheme is proposed by combining public-key encryption with the digital signature. Finally, the security of the proposed IBCES’s encryption and the signature schemes is verified, and the results prove their feasibility. The results show that the proposed IBCEs are effective and feasible, fully meeting the information confidentiality requirements. Additionally, smart grid against Information Security (ISEC) algorithms must comprehensively consider network resources and computing power. This work creatively combines the two cryptosystems. The proposal breaks the traditional key segmentation principle by applying the same key to different cryptosystems and ensures the independent security of the two cryptosystems. The conclusion provides technical support for future research on cryptography.
Considerations in Raman Spectroscopy for Real-Time API Concentration Measurement at Tablet Press Feed Frame
Authors: Kumar Sumit , Nagy Zoltan , Reklaitis Gintaras V. , Gonzalez Marcial
Published: February 2023

Raman spectroscopy is one of the important process analytical technology tools available for implementation in the continuous manufacturing of oral solid dosages. The aim of this study was to investigate several practical considerations in generating real-time measurements using Raman spectrometer at a tablet press feed frame, including the effects of fluorescence interference, photobleaching, feed-frame rpm, and material particle size. Fluorescence, in particular, is a significant drawback of Raman spectroscopy, compared to the use of near-infrared spectroscopy. Potential material sparing strategies were also investigated, including using stationary powders for calibration and isolation of feed-frame materials. Acetaminophen was used as the main active pharmaceutical ingredient (API), and microcrystalline cellulose (MCC) and lactose were used as excipients. The fluorescent behavior of MCC at 785 nm laser wavelength was reported and discussed. Raman spectra of a blend of MCC and acetaminophen and lactose and acetaminophen were collected at the feed frame of the tablet press. A series of preprocessing steps applied to remove the fluorescence interference was found to be effective, including the use of standard normal variate, subtraction of spectra of fluorescent material, baseline correction, and smoothing. Three different PLS models were prepared for different scenarios and their performances were compared. The models were able to predict the concentration of acetaminophen with root mean squared error prediction (RMSEP) of 0.29% w/w when there was no fluorescence interference and 0.57% w/w when there was fluorescence interference in background spectra. The study demonstrated the feasibility of using Raman spectroscopy for API concentration prediction even in the case of fluorescent interference and showed that Raman measurements were robust; that is, they were not much affected by feed-frame rpm and excipient particle size.
Combined Effects of Different Bracket Bonding Adhesives and Different Resin Removal Methods on Enamel Discoloration: A Preliminary Study
Authors: Niknam Ozra , Shamohammadi Milad , Ataei Zeynab , Rakhshan Vahid
Published: February 2023

Introduction. This study aimed to investigate the effects of 3 orthodontic bracket adhesives and 3 resin removal methods on enamel discoloration. Methods. Ninety metal orthodontic brackets were bonded to 90 intact human premolars, using 3 adhesives (total etch composite (Transbond), self-etch composite (OptiBond), and light-curedresin-modified glass ionomer cement (RMGI, Fuji); n = 3 × 30). Each “bracket bonding” group (n = 30) was randomly divided into three subgroups of 10 specimens each, each with a different method of remnant resin removal (using only tungsten carbide burs; using tungsten carbide burs plus Sof-Lex polisher discs; using tungsten carbide burs and Stainbuster burs; n = 3 × 30). After bracket debonding and coffee staining (at 37°C for one week), the color change parameters (Δa, Δb, ΔL, and ΔE) were measured and then analyzed statistically (α = 0.05). Results. All 9 mean ΔE values were significantly greater than 3.7 and 1.0 (

P

values ≤0.002, t-test). The effects of composites and resin removal methods on the ΔE parameter (and their interaction) were significant (

P

values ≤0.008, two-way ANOVA). There were significant pairwise comparisons between total etch (Transbond) and each of the other composites (

P

values ≤0.008, Tukey). Nonetheless, the difference between self-etch (OptiBond) and RMGI (Fuji) was not significant (

P
=
0.967

). There were significant pairwise comparisons between the ΔE parameter of group “Bur + Stainbuster” and ΔE of each of the other methods (both

P

values ≤0.017). Conclusions. All 9 pairs of adhesives and resin removal techniques will cause quite visible discolorations. Still, self-etch composites or RMGI might be recommended over total etch composites. Moreover, using Stainbuster burs together with tungsten carbide burs is recommended to reduce discoloration. However, the coloration caused by each composite type can change drastically given the following adhesive removal technique used.
A Review of Common Techniques for Visual Simultaneous Localization and Mapping
Authors: Dai Yong , Wu Jiaxin , Wang Duo
Published: February 2023

Mobile robots are widely used in medicine, agriculture, home furnishing, and industry. Simultaneous localization and mapping (SLAM) is the working basis of mobile robots, so it is extremely necessary and meaningful for making researches on SLAM technology. SLAM technology involves robot mechanism kinematics, logic, mathematics, perceptual detection, and other fields. However, it faces the problem of classifying the technical content, which leads to diverse technical frameworks of SLAM. Among all sorts of SLAM, visual SLAM (V-SLAM) has become the key academic research due to its advantages of low price, easy installation, and simple algorithm model. Firstly, we illustrate the superiority of V-SLAM by comparing it with other localization techniques. Secondly, we sort out some open-source V-SLAM algorithms and compare their real-time performance, robustness, and innovation. Then, we analyze the frameworks, mathematical models, and related basic theoretical knowledge of V-SLAM. Meanwhile, we review the related works from four aspects: visual odometry, back-end optimization, loop closure detection, and mapping. Finally, we prospect the future development trend and make a foundation for researchers to expand works in the future. All in all, this paper classifies each module of V-SLAM in detail and provides better readability to readers. This is undoubtedly the most comprehensive review of V-SLAM recently.
High-Yield Alpha-Cellulose from Oil Palm Empty Fruit Bunches by Optimizing Thermochemical Delignification Processes for Use as Microcrystalline Cellulose
Authors: Susi Susi , Ainuri Makhmudun , Wagiman Wagiman , Falah Mohammad Affan Fajar
Published: February 2023

Oil palm empty fruit bunches (OPEFB) are lignocellulosic materials that are a by-product of the palm oil industry, which have less use and utilization is still limited. OPEFB’s high cellulose content could potentially develop into various bioproducts, especially biomaterials. The thermochemical delignification process can obtain high-yieldalpha-cellulose. The cellulose extraction process can be done by combining the bleaching process under acidic conditions and alkaline delignification to obtain high-purity cellulose. The bleaching conditions vary in the concentration of NaClO2, the length of bleaching, the temperature, and the number of stages. The research obtains high α-cellulose by optimizing bleaching conditions under acidic conditions in cellulose’s OPEFB extraction with variability on NaClO2 concentration and bleaching time using response surface methodology (RSM). The bleaching process was implemented at an early stage with a concentration of 3% NaClO2 and a bleaching time of 2 hours as a center point with a bleaching cycle of twice at pH 4–4.5 using acetic acid. Bleached fibers were delignified using 10% NaOH for 2 hours at room temperature. The RSM analysis resulted in optimum bleaching conditions at a concentration of 3.22% NaClO2 for 1 hour, yielding OPEFB’s cellulose of 82.96% ± 2.53, hemicellulose of 9.27% ± 2.28, and lignin of 1.68% ± 0.58. The validation and verification process in the bleaching conditions obtained cellulose of 84.87% and α-cellulose of 88.51%, with a crystallinity index of 70.55% and crystallite size of 2.35 nm. Scanning electron microscopy on surface cellulose morphology at optimum bleaching helped remove hemicellulose impurities, lignin, and inorganic materials and a more intensive opening of cellulose fibrils. The bleaching process optimization point was verified to improve the delignification performance and potentially produce high yield α-cellulose content for microcrystalline cellulose use.
Sensor FDI System Based on Discrete‐TimeFractional‐Order Observers
Authors: Escobar-Jiménez R. F. , Alegría-Zamudio M. , Téllez-Anguiano A. C. , Olivares-Peregrino V. H.
Published: February 2023

The design of sensor fault detection and isolation (FDI) systems has been studied widely by several authors of different fields of science (engineering, mathematics, physics) to ensure the continuous operation of systems or processes. This research presents the design and evaluation of a fault detection and isolation (FDI) system based on discrete fractional‐orderhigh‐gain observers (DFOHGO) for the outlet temperature sensors of a heat exchanger. The formulation of the discrete fractional‐order observers is based on the Grünwald–Letnikov fractional‐order derivative. The FDI system is based on a bank of two DFOHGOs to carry out a residual evaluation. The obtained results showed that the DFOHGOs provide accurate estimations of the temperatures. This allows switching the faulty sensor signal to the temperature estimations provided by the DFOHGOs when a fault occurs.
Profeta e o Principal: A ação política ameríndia e seus personagens
Authors: Cimbaluk Lucas
Published: February 2023

SZTUTMAN, Renato. O Profeta e o Principal: A ação política ameríndia e seus personagens. São Paulo: Editora da Universidade de São Paulo, Fapesp, 2012, 576 pp.
Visão dos localistas sobre a cólera no século XIX: Tradução do Comunicado do Conselho de Saúde do Reino da Baviera publicado em 1873
Authors: Sestelo José Antônio de Freitas , Fonseca Jael Glauce da
Published: February 2023

Apresenta tradução para o português de excertos do Comunicado do Conselho de Saúde do Reino da Baviera à População de Munique publicado originalmente em alemão depois da segunda grande epidemia de cólera na cidade em 1854. Foi utilizada como fonte primária a quinta edição do texto de autoria de Max von Pettenkofer publicada em 1873. Após uma breve introdução são apresentados os excertos do texto com comentários à luz dos conceitos da Medicina Social.
Potencial de aproveitamento de sítios arqueológicos para fins de musealização in loco: estudo de caso no Curimataú e Seridó da Paraíba
Authors: Rosa João Henrique , Santos Juvandi de Souza
Published: February 2023

O objetivo do presente texto é discutir perspectivas de avaliação do potencial de criação de museus arqueológicos a céu aberto, propondo como ferramenta uma chave prévia de classificação baseada em aspectos físicos e institucionais, que avalia a capacidade de resposta para propostas de musealização de sítios no seu próprio local de implantação, usando como amostra parcial duas regiões arqueológicas, Curimataú e Seridó, localizadas a nor-nordeste do Estado da Paraíba. A chave utiliza quatorze características básicas que são classificadas de acordo com pesos de 0 a 2 e que, combinadas, resultam em uma pontuação supostamente indicadora da maior ou menor aptidão dos sítios analisados em receber intervenções de musealização in loco. O resultado obtido nessa iniciativa indicou que dos dezessete sítios classificados, 53% apresentaram Alto potencial, 29% Médio e 18% Baixo, não figurando nenhum sítio nos extremos Muito alto e Muito baixo potencial. O texto aponta ainda que essa proposta foi capaz de diagnosticar potencialidades e deficiências considerando características básicas e de fácil acesso a gestores e profissionais interessados.
Optimization of Ingredients and Process for Development of Cereals-Soy-Veggie Mix Healthy Noodles
Authors: Mangaraj Shukadev , Nishad Praween , Thakur Rajeev Ranjan , Deshpande Sumedha , Sami Rokayya , Aljahani Amani H. , Helal Mahmoud , Fikry Mohammad
Published: February 2023

Composite flour based noodles were developed by optimizing ingredients and processing conditions using Box-Behnken Design. For ingredients optimization, wheat flour (20–25%), refined wheat flour (Maida) (40–50%), defatted soy flour (10–18%) and vegetable powder (5–7%)
were taken as independent variables. For process optimization, feed moisture content (30–40%, db), steaming time (7–12 min), drying temperature (45–65 °C) and drying time (6–8 h) were selected as input parameters. The optimum values of ingredients were found to
be 20%, 48.54%, 17.39% and 6.52% for wheat, refined wheat, defatted soy flour and vegetable powder, respectively. The optimum value for process variables were recorded as 30.09%, 7.89 min, 64.75 °C and 7.95 h for feed moisture content, steaming time, drying temperature and drying time,
respectively. The optimized composite flour and developed noodle showed higher protein content (16.28%), energy value (309.78 kcal), hardness (143.09 g) with low fat (0.972%) and moisture content (4.35%).
Obstetrical Trauma: Reducing the Burden of Trauma Transfer to Tertiary Care Centers
Authors: Kirk Charlotte H. , Ciraulo Giovanni E. , Ciraulo Rocco S. , Falank Carolyne R. , Ciraulo David L.
Published: February 2023

Background

In rural state trauma systems, management of the obstetrical trauma patient often defaults to transfer to level I trauma centers. We evaluate the necessity of transferring obstetrical trauma patients without severe maternal injury.

Materials and Methods

A retrospective 5-year review of obstetrical trauma patients admitted to a rural state-level I trauma center was conducted. Injury severity measures such as abdominal AIS, ISS, and GCS were correlated with outcomes. Furthermore, the impact of maternal and gestational age on uterine compromise, uterine irritability, and the need for cesarean section intervention are presented.

Results

Twenty-one percent of patients were transferred from outside facilities with a median age of 29 years, average ISS of 3.9 ± 5.6, GCS of 13.8 ± 3.6, and abdominal AIS of 1.6 ± .8. Outcomes included maternal fatality of 2%, fetal demise of 4%, 6% experienced premature rupture of membranes, 9% experienced fetal placental compromise, 15% had uterine contractions, 15% of cesarean deliveries, and fetal decelerations occurred in 4%. Predictors of fetal compromise are strongly associated with high maternal ISS and low GCS.

Discussion

The frequency of traumatic injury in this unique population of patients is fortunately limited. The best predictor for fetal demise and uterine irritability is maternal injury severity, measured by ISS and GCS. Therefore, without severe maternal trauma, obstetrical trauma patients with minor injuries can safely be managed at non-tertiary care facilities with obstetrical capabilities.
Can a Multidisciplinary Endocrine Clinic be Beneficial for Patients and Surgeons?
Authors: Kennedy Alexis , Zmijewski Polina V. , Bahl Deepti , Banerjee Ronadip , Buczek Erin , Fazendin Jessica , Chen Herbert , Lindeman Brenessa
Published: February 2023

Background

Multidisciplinary clinics are expected to improve patient care by enhancing efficiency for both patients and care providers. We hypothesized that while these clinics are an efficient use of time for patients, they can limit a surgeon’s productivity.

Methods

A retrospective review was performed for patients evaluated in a Multidisciplinary Endocrine Tumor Clinic (MDETC) and Multidisciplinary Thyroid Cancer Clinic (MDTCC) from 2018 to 2021. Time from evaluation to surgery and prevalence of surgery were evaluated. Patients were compared to those evaluated in a surgeon-only endocrine surgery clinic (ESC) from 2017 to 2021. Chi-square and t-tests were used to test significance.

Results

Patients referred to the ESC underwent surgery more often than those referred to either multidisciplinary clinic (ESC 79.5%, MDETC 24.6%, MDTCC 7%; P < .001) but had a significantly longer delay between appointment and operation (ESC 19.9 days, MDETC 3.3 days, MDTCC 16.4 days; P < .001). Patients had a longer wait from referral to appointment for the MDCs (ESC 22.6 days, MDETC: 44.5, MDTCC 33; P < .05). There was no significant difference in miles traveled by patients to any clinic.

Conclusion

Multidisciplinary clinics can provide fewer appointments and faster time to surgery for patients but may lead to longer wait time from referral to appointment and fewer overall surgeries than endocrine surgeon-only clinics.
Primary Hepatic Inflammatory Myofibroblastic Tumor With Synchronous Primary Squamous Cell Lung Cancer in an Elderly Woman
Authors: Osumo Bismarck , Kelter David , Rosenberg Megan , Abbas Syed , Pulinthanathu Rajiv , Smith Franz
Published: February 2023

The hepatic inflammatory myofibroblastic tumor is a spindle cell tumor of the liver that originates from the mesenchymal tissues. It is a rare benign tumor with the potential to degenerate into a malignant and invasive tumor. It can occur anywhere in the body with the most common sites being the lung, mesentery, and omentum. The most common types are myxoid, vascular pattern, fibrous, or hypocellular fibroid type. Immunohistochemistry staining often indicates vimentin, muscle-specific actin, smooth muscle actin, and cytokeratin. These tumors are positive for CD 68 abundant histiocytes but negative for S100. Half of the inflammatory myofibroblastic tumors contain a clonal cytogenetic aberration that activates the ALK gene expression. We present a rare case of HIMT in an elderly female with active primary squamous lung cancer.
Incidence and Outcomes of Undiagnosed and Untreated Diabetes Mellitus in Trauma Patients
Authors: Massey Ashley C. , Dunbar Elizabeth G. , Lee Yann-Leei L. , Mbaka Maryann , Kinnard Christopher M. , Bright Andrew C. , Williams Ashley Y. , Polite Nathan M. , Capasso Thomas J. , Simmons Jon D. , Butts Charles C.
Published: February 2023

Diabetes is a major determinate for mortality in trauma patients. Many diabetics are undiagnosed or poorly controlled. Trauma patients disproportionately come from lower socioeconomic status, making missed diagnoses more likely. We aimed to quantify the incidence of undiagnosed or poorly controlled diabetics assessed at a Level 1 Trauma Center. We did a retrospective chart review of admitted trauma patients over a one-month period. Past Medical History, home medication lists, and Hemoglobin A1c on admission were recorded for each patient. We determined that 30 of 173 trauma patients qualifying for the study were diabetic. Furthermore, 30% of these diabetics were undiagnosed or had poorly controlled diabetes. Undiagnosed pre-diabetics made up 20% of the entire study group. Our data show that 26% of trauma patients would benefit from an intervention for improved glucose control. Trauma centers should consider creating routine clinical practice guidelines to identify at-risk patients and provide intervention for long-term management.
Traduction de l'Occupational Balance Questionnaire en français et sa validation
Authors: Larivière Nadine , Bertrand Anne Martine , Beaudoin Joliane , Giroux Annie , Grenier Karine , Page Raphaëlle , Perrin Cindy , Håkansson Carita
Published: February 2023

Description. Des questionnaires visant à mesurer l’équilibre occupationnel ont été créés ces dernières années, mais ceux disponibles en français sont limités. But. Cette étude visait à traduire et adapter transculturellement l’ Occupational Balance Questionnaire et à examiner la cohérence interne, la fidélité test-retest et la validité convergente de la version en français. Méthodologie. Une validation a été effectuée auprès de personnes adultes au Québec (n = 69) et en Suisse romande (n = 47). Résultats. La cohérence interne est bonne dans les deux régions (α > 0,85). La fidélité test-retest est satisfaisante au Québec (ICC = 0,629 ; p < 0,001), mais une différence significative est relevée entre deux passations en Suisse romande. Une relation significative est démontrée entre l’équilibre occupationnel et l’équilibre de vie (Québec r = 0,47 ; Suisse romande r = 0,52). Conséquences. Ces premiers résultats soutiennent l’utilisation de l’OBQ-français auprès de la population générale de deux régions francophones.