bluuebunny/crossref_metadata_2025 huggingface dataset:
Toward the circular economy into the olive oil supply chain: A case study analysis of a vertically integrated firm
Authors: Stempfle Sarah , Roselli Luigi , Carlucci Domenico , Leone Alessandro , de Gennaro Bernardo Corrado , Giannoccaro Giacomo
Published: December 2022

While the paradigm of circular economy (CE) and the processes of socio-technical transition have been broadly investigated at the theoretical level, understanding how the transition toward circular models can be implemented in practice is still limited. This contribution aims to provide in-depth and evidence-based insights on an emerging pathway for the operability of CE into the olive oil supply chain. A case study from the Apulia region (the leading olive oil producing area in Italy) is presented to show how an existing business model can be transformed into a circular one, and to what extent it can be replicated. The study focuses on a vertically integrated firm, in which a new industrial process has been introduced to manage olive pomace, which is one of the most important by-products obtained from olive oil extraction. The empirical analysis is built on the Circular Business Model Canvas (CBMC), which is conceived as a suitable theoretical and methodological tool to speed up the transition process toward CE at a micro-economic level. This analytical framework allows us to identify the interplaying elements that the firm combines to capture, create, and deliver value, as well as the relationships with the broader economic system. Particular attention is paid to two distinctive components of CBMC: material loops and adoption factors. Also, internal and external factors affecting the adoption of the new circular business model have been discussed by separating drivers and barriers of the transition process.
The practice of sustainable home cooking – a fascinating philosophical perspective
Authors: Salgado Diana , Verkerk Maarten J.
Published: December 2022

Introduction

In this article we explore the practice of sustainable home cooking from a philosophical perspective.

Methodology

We analyze the practice of sustainble homecooking on the basis of the theory of modal aspects (Dooyeweerd) and the Triple I model (Verkerk and others).

Results and discussion

Philosophy offers a fascinating perspective on sustainable home cooking. First, it shows the richtness of the phenomenon of home cooking. Second, it shows that home cooking constists out of two sub practices: preparing a meal and eating a dish. Each of these sub practices has an own identity and own inherent values. Third, the transition to sustainable home cooking requires three related strategies. (1) A transition of present home cooking practices to a sustainable practice by focussing on the inherent values of sustainable home cooking. (2) A transition of the whole food chain to a sustainable one. (3) A transition in the ideals and basic beliefs of society about sustainable home cooking.
Use of nonaversive handling and training procedures for laboratory mice and rats: Attitudes of American and Canadian laboratory animal professionals
Authors: O'Malley Carly I. , Hubley Raina , Moody Carly , Turner Patricia V.
Published: December 2022

Nonaversive or low stress handling techniques can reduce fear and stress in research rodents, ultimately improving study data quality. Uptake of low stress handling has been slow in the USA and Canada. In this study we explored the understanding, experience, and attitudes toward low stress handling of rats and mice in laboratory animal professionals from the USA (US) and Canada (CA). Participants (n = 40) were recruited for a standardized interview and job categories were divided into veterinary/PhD level roles (doctoral level; DL) and non-veterinary/non-PhD level roles (non-doctoral level, NDL) (US: 23, DL: 9, NDL: 14; CA: 17, DL: 8, and NDL: 9). Interviews were transcribed and analyzed using NVIVO. Two research assistants independently coded themes for each question and consolidated responses based on commonality. Laboratory animal professionals understood the benefits of low stress handling and training techniques with rats and mice, stating reduced stress, better data, and improved welfare, with CA participants more likely to mention animal welfare as a benefit, and DL more likely to mention improved research data and reduced stress. Participants across demographic groups indicated improved job satisfaction and decreased stress as the positive impacts low stress handling would have on their positions. The primary perceived barriers to low stress handling implementation were researcher attitudes, the time needed to implement and use these techniques, and training personnel to use the techniques properly and consistently. To promote refinement of handling of rats and mice, more educational opportunities on the benefits and implementation of low stress handling techniques need to be provided to laboratory animal professionals, as well as to researchers.
Poor Outcomes of Patients With NAFLD and Moderate Renal Dysfunction or Short-Term Dialysis Receiving a Liver Transplant Alone
Authors: Fernández-Carrillo Carlos , Li Yaming , Ventura-Cots Meritxell , Argemi Josepmaria , Dai Dongling , Clemente-Sánchez Ana , Duarte-Rojo Andres , Behari Jaideep , Ganesh Swaytha , Jonassaint Naudia L. , Tevar Amit D. , Hughes Christopher B. , Humar Abhinav , Molinari Michele , Landsittel Douglas P. , Bataller Ramon
Published: December 2022

The outcomes of patients with moderate renal impairment and the impact of liver disease etiology on renal function recovery after liver transplant alone (LTA) are largely unknown. We explored whether NAFLD patients with pre-LTA moderate renal dysfunction (GFR 25–45 ml/min/1.73 m2) may be more susceptible to develop post-LTA severe renal dysfunction (GFR<15 ml/min/1.73 m2) than ALD patients, as well as other overall outcomes. Using the UNOS/OPTN database, we selected patients undergoing liver transplant for NAFLD or ALD (2006–2016), 15,103 of whom received LTA. NAFLD patients with moderate renal dysfunction were more likely to develop subsequent GFR<15 ml/min/1.73 m2 than ALD patients (11.1% vs. 7.38%, p < 0.001). Patients on short-term dialysis pre-LTA (≤12 weeks) were more likely to develop severe renal dysfunction (31.7% vs. 18.1%), especially in NAFLD patients, and were more likely to receive a further kidney transplant (15.3% vs. 3.7%) and had lower survival (48.6% vs. 50.4%) after LTA (p < 0.001 for all). NAFLD was an independent risk factor for post-LTA severe renal dysfunction (HR = 1.2, p = 0.02). NAFLD patients with moderate renal dysfunction and those receiving short-term dialysis prior to LTA are at a higher risk of developing subsequent severe renal dysfunction. Underlying etiology of liver disease may play a role in predicting development and progression of renal failure in patients receiving LTA.
Emission-Driven Hybrid Rocket Engine Optimization for Small Launchers
Authors: Casalino Lorenzo , Ferrero Andrea , Masseni Filippo , Pastrone Dario
Published: December 2022

Hybrid rocket engines are a green alternative to solid rocket motors and may represent a low-cost alternative to kerosene fueled rockets, while granting performance and control features similar to that of typical storable liquid rocket engines. In this work, the design of a three-stage hybrid launcher is optimized by means of a coupled procedure: an evolutionary algorithm optimizes the engine design, whereas an indirect optimization method optimizes the corresponding ascent trajectory. The trajectory integration also provides the vertical emission profiles required for the evaluation of the environmental impact of the launch. The propellants are a paraffin-based wax and liquid oxygen. The vehicle is launched from the ground and uses an electric turbo pump feed system. The initial mass is given (5000 kg) and the insertion of the payload into a 600-km circular, and polar orbit is considered as a reference mission. Clusters of similar hybrid rocket engines, with only few differences, are employed in all stages to reduce the development and operational costs of the launcher. Optimization is carried out with the aim of maximizing the payload mass and then minimizing the overall environmental impact of the launch. The results show that satisfactory performance is achievable also considering rocket polluting emissions: the carbon footprint of the launch can be reduced by one fourth at the cost of a 5-kg payload mass reduction.
Can the Sorghum Planting Industry in Less-Favoured Areas Promote the Income Increase of Farmers? An Empirical Study of Survey Data from 901 Samples in Luquan County
Authors: Yang Renyi , Yang Zisheng
Published: December 2022

Poverty alleviation is the basic requirement of human social development. However, there is still a lack of quantitative research on the poverty alleviation effect of regional, characteristic industries. Few studies have focused on the increase of micro individual income and used more advanced policy evaluation tools for comparative analysis based on a quasi-experimental perspective. In addition, the existing research ignores the critical question: can characteristic industries really achieve sustainable development goals while bringing poverty alleviation results? We studied regional, characteristic industries from a new perspective, taking into account the poverty alleviation effect and regional sustainable development. Based on the survey data of 901 households of representative village committees of Tanglang and Dache in Luquan Yi and Miao Autonomous County, this study quantitatively analyzed the poverty alleviation effect of the sorghum planting industry by using the Propensity Score Matching Difference-in-Differences (PSM-DID) model. The adoption of the industrial alleviation policy has significantly increased the per capita net income of rural households in Tanglang and Dache village committees, by 2171.64 CNY and 1945.06 CNY, respectively. The estimation results of the whole sample show that the effect of the policy to the per capita net income of households is 1726.87 CNY. The development of the sorghum planting poverty alleviation industry in Luquan County has promoted income increase of households significantly, creating economic, social and ecological sustainability, and can provide a reference for less-favoured areas.
Growth and Forage Value of Two Forage Rice Cultivars According to Harvest Time in Reclaimed Land of South Korea
Authors: Jang Yeongmi , Sharavdorj Khulan , Nadalin Priscilla , Lee Suhwan , Cho Jinwoong
Published: December 2022

This study compares the growth of two forage rice cultivars (Oryza sativa L.), Mogwoo and Mogyang, in Midwest reclaimed land (Seongmun Tide Embankment, Korea) for two years to find the most adaptable cultivars and the appropriate harvest time. In the case of high salinity soil, it was confirmed that the influence of precipitation was relatively high on soil condition and crop growth. In Mogyang, plant height and culm length tended to decrease slightly as the precipitation increased. As for the tiller number, Mogyang was higher than Mogwoo, but the leaf area was about 1.5 to 2 times higher in Mogwoo than in Mogyang. In addition, in both cultivars, dry weight increased rapidly during the dough stage, and Mogyang was 1538 and 1815 g/m2, respectively, while Mogwoo was 2090 and 2752 g/m2, which was significantly higher. Mogyang had a CP of 4.8%, a TDN and RFV of 59.4%, 94.0, respectively, and Mogwoo had a CP of 9.7%, a TDN and RFV of 60.1%, 103.8, respectively, resulting in Mogwoo having higher values, and in particular Mogwoo was found to have better forage quality in the milk stage than in the dough stage. In addition, in terms of soil and climate conditions in Midwest reclaimed land, it was confirmed that the Mogwoo variety was the most suitable compared to Mogyang, and dry weight was higher in the dough stage than in the milk stage, but it was concluded that high forage quality could be obtained by harvesting during the milk stage.
Effects of Organic and Inorganic Fertilization on Soil Organic Carbon and Enzymatic Activities
Authors: Zhang Congzhi , Zhao Zhanhui , Li Fang , Zhang Jiabao
Published: December 2022

The overapplication of mineral nitrogen (N) fertilizer has become a scientific problem to be solved in the North China Plain; meanwhile, most organic manure cannot be recycled into the soil. To make full use of organic manure and decrease the applied rate of mineral N fertilizer, a four-year fertilization experiment was carried out to assess the effects of substituting mineral fertilizer with organic manure on soil organic carbon (SOC), labile organic carbon (LOC), stable organic carbon (UOC), microbial biomass carbon (MBC), and soil enzymatic activity. There were six treatments including unfertilized control (CK); mineral fertilizer without organic manure (FR); and mineral nitrogen substituted by organic manure at 20%, 40%, 60%, and 80% (FM1, FM2, FM3, and FM4), respectively. The results showed that SOC, UOC, and LOC were significantly increased by 13.30~40.56%, 41.10~121.92%, and 4.91~15.57% with increasing amounts of organic manure, respectively. Adding organic manure also enhanced urease, catalase, sucrase, and cellulase activities as well as MBC in surface soil (0–20 cm). The present study revealed the activities of urease, catalase, sucrase, and cellulase were closely related to SOC and its components. Following organic manure application, MBC and enzymatic activities had active effects in enhancing LOC and UOC sequestration based on path analyses. Additionally, organic manure increased SOC by direct and indirect enhancement of UOC and LOC, respectively, and improved SOC sequestration as compared to FR treatment. Finally, the study revealed that SOC quantity and quality were both significantly improved by combined application of mineral fertilizer and organic manure, and this effect was enhanced with the increase of organic manure application. Considering the improvements in soil properties and grain yields, substituting mineral fertilizer with organic manure might be a promising alternative in the North China Plain.
Effect of PAS-LuxR Family Regulators on the Secondary Metabolism of Streptomyces
Authors: Zhang Naifan , Dong Yao , Zhou Hongli , Cui Hao
Published: December 2022

With the development of sequencing technology and further scientific research, an increasing number of biosynthetic gene clusters associated with secondary Streptomyces metabolites have been identified and characterized. The encoded genes of a family of regulators designated as PAS-LuxR are gradually being discovered in some biosynthetic gene clusters of polyene macrolide, aminoglycoside, and amino acid analogues. PAS-LuxR family regulators affect secondary Streptomyces metabolites by interacting with other family regulators to regulate the transcription of the target genes in the gene cluster. This paper provides a review of the structure, function, regulatory mechanism, and application of these regulators to provide more information on the regulation of secondary metabolite biosynthesis in Streptomyces, and promote the application of PAS-LuxR family regulators in industrial breeding and other directions.
Outcomes of Beta-Lactam Allergic and Non-Beta-Lactam Allergic Patients with Intra-Abdominal Infection: A Case–Control Study
Authors: Naciri Tayma , Monnin Boris , Pantel Alix , Roger Claire , Kinowski Jean-Marie , Loubet Paul , Lavigne Jean-Philippe , Sotto Albert , Larcher Romaric
Published: December 2022

Background: In the case of intra-abdominal infections (IAI) in beta-lactam (BL) allergic patients, empiric antimicrobial therapy without BL is recommended; however, data regarding the outcome with alternative regimens are scarce. This study aimed to compare the outcomes of BL allergic (BLA) patients with IAI to those who were non-BLA (NBLA). Method: We conducted a case–control study in a French teaching hospital, between 1 January 2016 and 31 August 2021. BLA patients with IAI treated with fluoroquinolone or aztreonam and metronidazole were matched with controls treated with BL, on age, sex, disease severity, IAI localization, and healthcare-associated infection (HAI) status. We compared rates of therapeutic failures, adverse events, and HAI, and then assessed factors associated with therapeutic failure using a logistic regression model. Results: The therapeutic failure rate was 14% (p > 0.99) in both groups of 43 patients, and there was no significant difference in the adverse events rate (p > 0.99) and HAI rate (p = 0.154). Factors independently associated with therapeutic failure were higher BMI (OR 1.16; 95%CI [1.00–1.36]; p = 0.041), longer hospital length of stay (OR 1,20; 95%CI [1.08–1.41]; p = 0.006), and inadequate empiric antimicrobial therapy (OR 11.71; 95%CI [1.43–132.46]; p = 0.025). Conclusion: The outcomes of BLA patients with IAI treated without BL were the same as those for NBLA patients treated with BL.
Oxidative Regulation of Vascular Cav1.2 Channels Triggers Vascular Dysfunction in Hypertension-Related Disorders
Authors: Hu Xiang-Qun , Zhang Lubo
Published: December 2022

Blood pressure is determined by cardiac output and peripheral vascular resistance. The L-type voltage-gated Ca2+ (Cav1.2) channel in small arteries and arterioles plays an essential role in regulating Ca2+ influx, vascular resistance, and blood pressure. Hypertension and preeclampsia are characterized by high blood pressure. In addition, diabetes has a high prevalence of hypertension. The etiology of these disorders remains elusive, involving the complex interplay of environmental and genetic factors. Common to these disorders are oxidative stress and vascular dysfunction. Reactive oxygen species (ROS) derived from NADPH oxidases (NOXs) and mitochondria are primary sources of vascular oxidative stress, whereas dysfunction of the Cav1.2 channel confers increased vascular resistance in hypertension. This review will discuss the importance of ROS derived from NOXs and mitochondria in regulating vascular Cav1.2 and potential roles of ROS-mediated Cav1.2 dysfunction in aberrant vascular function in hypertension, diabetes, and preeclampsia.
Biomechanical Task-Based Gait Analysis Suggests ReWalk Gait Resembles Crutch Gait
Authors: Kim Jaewook , Kim Yekwang , Kim Seung-Jong
Published: December 2022

Current gait rehabilitation strategies rely heavily on motor learning principles, which involve facilitating active patient participation, high-doses of biomechanical task-related motor activities and accurate feedback. Furthermore, appropriate muscle groups need to be recruited for the joint movements that constitute the biomechanical task-related activities in order to effectively promote motor learning. Recently, exoskeleton-type robots utilizing crutches have been incorporated into overground gait rehabilitation programs. However, it is unclear which gait-related tasks are being trained because the joint movements and muscle recruitment patterns deviate from those of natural gait. This raises concerns because repetitive training with these devices may not lead to desirable rehabilitative gains. In this study, we compare the lower limb joint angles and electromyography patterns of healthy subjects walking with and without ReWalk in accordance with the three major biomechanical tasks required by bipedal gait: weight acceptance (WA), single-limb support, and limb advancement. Furthermore, we investigate whether the physical constraints of ReWalk, most noticeably the use of crutches and fixed ankle joints, were responsible for the specific changes by conducting additional walking sessions with either crutches or ankle foot orthoses. The results from the six healthy male volunteers suggest that the gait patterns observed with ReWalk deviate significantly from those of natural gait, particularly during the WA, and closely resemble those of crutch gait.
An Optimized Gradient Boost Decision Tree Using Enhanced African Buffalo Optimization Method for Cyber Security Intrusion Detection
Authors: Mishra Shailendra
Published: December 2022

The cyber security field has witnessed several intrusion detection systems (IDSs) that are critical to the detection of malicious activities in network traffic. In the last couple of years, much research has been conducted in this field; however, in the present circumstances, network attacks are increasing in both volume and diverseness. The objective of this research work is to introduce new IDSs based on a combination of Genetic Algorithms (GAs) and Optimized Gradient Boost Decision Trees (OGBDTs). To improve classification, enhanced African Buffalo Optimizations (EABOs) are used. Optimization Gradient Boost Decision Trees (OGBDT-IDS) include data exploration, preprocessing, standardization, and feature ratings/selection modules. In high-dimensional data, GAs are appropriate tools for selecting features. In machine learning techniques (MLTs), gradient-boosted decision trees (GBDTs) are used as a base learner, and the predictions are added to the set of trees. In this study, the experimental results demonstrate that the proposed methods improve cyber intrusion detection for unused and new cases. Based on performance evaluations, the proposed IDS (OGBDT) performs better than traditional MLTs. The performances are evaluated by comparing accuracy, precision, recall, and F-score using the UNBS-NB 15, KDD 99, and CICIDS2018 datasets. The proposed IDS has the highest attack detection rates, and can predict attacks in all datasets in the least amount of time.
High Dielectric Design of Polymer Composites by Using Artificial Neural Network
Authors: Ji Sungyub , Jeong Dae-Yong , Kim Cheolhee , Yi Sung
Published: December 2022

Polymer-based composites with a high dielectric property have shown great potential in electrical energy storage applications. It is important to predict the dielectric constant in designing polymer composites, but it is costly and time consuming. In this study, dielectric properties of various polymer composites have been predicted by using an artificial neural network (ANN) model trained with hundreds of experimentally measured data. Eight variables such as the dielectric constant of matrix, filler, and shell, the diameter of filler, the volume fraction of filler, the dimension of filler, the thickness of shell, and the frequency were considered. To improve the prediction accuracy, hyper parameters of the ANN model were optimized through the hyperband method. Using the ANN model, we demonstrated the correlation between the dielectric constant of polymer composites and the variables. The ANN model predicted the dielectric constant with a coefficient of determination (R2) of 0.97. Furthermore, the ANN model shows good performance to predict dielectric constant at various frequencies (spanning from 100 Hz to 100 kHz). Hence, we present that the AI-based prediction model using ANN method can be helpful in designing the polymer composites with desired properties.
A Topology Based Automatic Registration Method for Infrared and Polarized Coupled Imaging
Authors: Zhong Aiqi , Fu Qiang , Huang Danfei , Zong Kang , Jiang Huilin
Published: December 2022

In multi-source camera collaborative imaging research, it is known that the differences in size and resolution of the sensor chip, the angle of view and field of view when imaging, and the imaging characteristics of optical systems between cameras, makes image registration a topic that can never be avoided in data analysis and post-processing. Additionally, lacking common features between multi-source images means that the accurate registration of multi-modal images can only be completed manually. Aiming at the registration problem of the polarization parameter image and infrared image, this study takes advantage of the invariant feature of the imaging target topology and introduces the image texture-based segmentation method to obtain the target topology structure. Subsequently, the registration control points are extracted based on the target topology skeleton, which can break through the limitation of feature differences, improve the robustness of the algorithm to target transformation, and realize the automatic registration of multi-source images.
Interpretation of Archaeogeological and Lithological Characters for Stones Used in Korean Ancient Tombs around the Songpa of Seoul
Authors: Lee Gyu Hye , Park Jun Hyoung , Lee Chan Hee
Published: December 2022

This study concerns the lithologic characteristics of the stone used as the main construction materials of ancient Korean tombs, and aims to understand how they were supplied. Specifically, we investigated the main ancient tombs in the Songpa district, south of the Hangang River in Seoul, composing the connected stone-mound tombs in the Seokchon-dong tomb complex, Bangi-dong tomb No. 3, and 13 horizontal stone-chamber tombs in the Gamil-dong tomb complex. There are major differences among the tombs reflected in the types of rock used as construction materials in these sites. Tombs at Seokchon-dong and Bangi-dong were built mainly using biotite gneiss, whereas those at Gamil-dong are composed of amphibole schist. By comparing the characteristics of the rocks collected from the provenance sites, we concluded that the quartzite used at the Gamil-dong tombs was from Cheonma Mountain, the gneiss at the Bangi-dong sites was from Daemo Mountain, and the amphibole schist and diabase at the Gamil-dong sites were from Cheonma Mountain. On the other hand, gravel-shaped stone materials are found in the tombs of Seokchon-dong and Bangi-dong, but not in Gamil-dong tombs. Therefore, it can be seen that between Seokchon-dong, Bangi-dong, and Gamil-dong tombs, there is a difference not only in the main constituent rock types, but also in the shape of the stone materials. These gravel-shaped stones are assumed to have been transported via the Hangang River drainage system and supplied to Seokchon-dong and Bangi-dong tombs. Therefore, we consider that the constructors of the tombs in the ancient Songpa district locally sourced materials of different rock types.
Hardware-Aware Mobile Building Block Evaluation for Computer Vision
Authors: Bonnaerens Maxim , Freiberger Matthias , Verhelst Marian , Dambre Joni
Published: December 2022

In this paper, we propose a methodology to accurately evaluate and compare the performance of efficient neural network building blocks for computer vision in a hardware-aware manner. Our comparison uses pareto fronts based on randomly sampled networks from a design space to capture the underlying accuracy/complexity trade-offs. We show that our approach enables matching of information obtained by previous comparison paradigms, but provides more insights into the relationship between hardware cost and accuracy. We use our methodology to analyze different building blocks and evaluate their performance on a range of embedded hardware platforms. This highlights the importance of benchmarking building blocks as a preselection step in the design process of a neural network. We show that choosing the right building block can speed up inference by up to a factor of two on specific hardware ML accelerators.
Oral Pathologies in Migrants: The Experience of the “PROTECT” Project in 3023 Patients
Authors: Palaia Gaspare , Bossù Maurizio , Pranno Nicola , Ralli Massimo , Bruscolini Alice , Capocci Mauro , Gaimari Gianfranco , Macali Federica , Corridore Denise , Cotticelli Luisa , Covello Francesco , Karaboue Michele Ahmed Antonio , Di Carlo Stefano , Romeo Umberto , Ottolenghi Livia , Polimeni Antonella
Published: December 2022

Introduction: The number of people with migrant status living in Europe is proliferating. Most of the refugees in Italy come from war zones, and many of them denounce having been victims of persecutory acts in their country of origin. Highly cultured migrant populations have shown better results and oral health behaviour than those who were poorly cultured. The PROTECT project aimed to build a network for the early management of head and neck pathologies among refugees and migrants, promoting the dissemination of correct information about the prevention and treatment of these pathologies. Materials and methods: A national cross-sectional study among the refugees and migrant population in the Lazio region, Italy, from February 2018 to September 2021 was performed. The oral health of 3023 participants was investigated within a network of 56 reception centres and cultural associations. Data collected via an oral health survey questionnaire gathered information on participants’ demographic factors, migration status and dental behaviours and clinical examinations of the participants with the help of mouth mirrors, periodontal probes and artificial light. Results: The mean age was 31.6 ± 13.1, and among all the subjects, 2058 were male (68.1%) and 965 were women (41.9%). Most participants were born in Nigeria, followed by Bangladesh, Pakistan, Somalia, Mali and Senegal. The overall oral pain prevalence was 48.2%. The prevalence of patients claiming poor oral hygiene was 32.4%; 36.2% of the subjects consumed high amounts of sugar; and 26.7% saw their dentist for a check-up in the last year. At the clinical examination, 68.9% of patients had caries experience (considering decay of deciduous teeth, and caries of permanent teeth and teeth with fillings), with 32.2% showing pulpal involvement. Low levels of oral hygiene were also found at the clinical examination, with 46.5% of patients presenting plaque and calculus. The trend of the DMFT index was found to be 5.41. Good periodontal health (CPI = 0) was present in approximately 33.5% of patients. The CPI = 1 index reported bleeding from gingivitis in 37% of patients; tartar was found in 27% of patients (CPI = 2). The percentage of patients with CPI = 3 was 3.6%. Just over half (52.2%) of the migrants examined had malocclusion, and only 0.7% had a malocclusion in treatment. Conclusions: The goal to be achieved is to develop education and prevention programs for head–neck diseases, and perhaps even more. The first step towards this goal can be removing the obstacles migrants encounter in accessing health care.
Information Consumer Experience: A Systematic Review
Authors: Godoy María Paz , Rusu Cristian , Ugalde Jonathan
Published: December 2022

The experience of employees that work with information has been studied in the literature using approaches that analyze information system success (e.g., Information Management, User Experience) or employee satisfaction (e.g., Job Satisfaction, Employee Experience) as two separate problems. Therefore, there are no approaches that analyze both employee experiences and information used within the organization simultaneously. This scenario has motivated us to define a new approach based on Consumer Experience (CX), called Information Consumer Experience (ICX). In order to accomplish this objective, a systematic review was performed, including articles indexed in four databases (Scopus, Web of Sciences, ACM digital, and Science Direct) published in the last decade (from 2012 to 2022) in order to answer the following research questions: (1) What is ICX? (2) What factors influence ICX? and (3) What methods are used for ICX evaluation? We selected 127 works and analyzed various ICX-related concept definitions, research approaches, data collection, and evaluation methods. The main contribution of this review is to identify a set of definitions, approaches, and methods for ICX modeling, evaluation, and design. The results obtained have allowed us to introduce a formal definition for the ICX concept derived from the CX approach and propose future research lines to explore ICX analysis, considering the factors and methods identified in this work, as ICX can be considered a specific case of CX.
Flow Study on the Anemometers of the Perseverance Based on Towing Tank Visualization
Authors: Rodríguez-Sevillano Ángel Antonio , Casati-Calzada María Jesús , Bardera-Mora Rafael , Feliz-Huidobro Alejandro , Calle-González Claudia , Fernández-Antón Jaime
Published: December 2022

Flow visualization is necessary in fields such as engineering, since it allows us to know what is happening around the element being studied by means of a preliminary method, although it is relatively close to future research and computation methodology. The present project studies the interference at the anemometers of the Mars rover Perseverance, caused by the mast holding one of its cameras. After obtaining the model, manufactured by a 3D printer, it was placed inside a hydrodynamic towing tank, and red dye was added for a visual observation of the interference during the experiment. A comparison was made between the results achieved and those seen in a wind tunnel, realizing the high correlation they have. Finally, this paper promotes the use of the hydrodynamic towing tank in preliminary studies due to its low costs, considering the adequate comparison with other higher precision methodologies.
Investigation of the Temperature Dependence of Parameters in the Generalized Peukert Equation Used to Estimate the Residual Capacity of Traction Lithium-Ion Batteries
Authors: Galushkin Nikolay E. , Yazvinskaya Nataliya N. , Galushkin Dmitriy N.
Published: December 2022

The Peukert equation is widely used in various analytical models of lithium-ion batteries. However, the classical Peukert equation is applicable to lithium-ion batteries only in a limited range of discharge currents. Additionally, it does not take into account the temperature impact on a battery’s released capacity. In this paper, the applicability of the generalized Peukert equation C = Cm/(1 + (i/i0)n) is investigated for the residual capacity determination of lithium-ion batteries based on the Hausmann model. It is proved that all the parameters (Cm, i0, and n) of this equation depend on a battery’s temperature. That is why, for a battery-released capacity calculation, it is necessary to take into account the battery’s temperature. The equations are found to describe the temperature dependence of all the parameters of the generalized Peukert equation. The physical meaning of all the parameters is established and it is shown that the generalized Peukert equation obtained with temperature consideration is applicable to any current and temperature of a battery.
A Systematic Literature Review on Diabetic Retinopathy Using an Artificial Intelligence Approach
Authors: Bidwai Pooja , Gite Shilpa , Pahuja Kishore , Kotecha Ketan
Published: December 2022

Diabetic retinopathy occurs due to long-term diabetes with changing blood glucose levels and has become the most common cause of vision loss worldwide. It has become a severe problem among the working-age group that needs to be solved early to avoid vision loss in the future. Artificial intelligence-based technologies have been utilized to detect and grade diabetic retinopathy at the initial level. Early detection allows for proper treatment and, as a result, eyesight complications can be avoided. The in-depth analysis now details the various methods for diagnosing diabetic retinopathy using blood vessels, microaneurysms, exudates, macula, optic discs, and hemorrhages. In most trials, fundus images of the retina are used, which are taken using a fundus camera. This survey discusses the basics of diabetes, its prevalence, complications, and artificial intelligence approaches to deal with the early detection and classification of diabetic retinopathy. The research also discusses artificial intelligence-based techniques such as machine learning and deep learning. New research fields such as transfer learning using generative adversarial networks, domain adaptation, multitask learning, and explainable artificial intelligence in diabetic retinopathy are also considered. A list of existing datasets, screening systems, performance measurements, biomarkers in diabetic retinopathy, potential issues, and challenges faced in ophthalmology, followed by the future scope conclusion, is discussed. To the author, no other literature has analyzed recent state-of-the-art techniques considering the PRISMA approach and artificial intelligence as the core.
Bioactive Materials for Next-Generation Dentistry
Authors: Ibarretxe Gaskon
Published: December 2022

Teeth were some of the first organs whose function was effectively restored by inert refilling materials that have become widely known to the general public; amalgams, polymeric resin composites, and gutta-percha are some such examples [...]
A Deep Learning Approach for Detecting Stroke from Brain CT Images Using OzNet
Authors: Ozaltin Oznur , Coskun Orhan , Yeniay Ozgur , Subasi Abdulhamit
Published: December 2022

A brain stroke is a life-threatening medical disorder caused by the inadequate blood supply to the brain. After the stroke, the damaged area of the brain will not operate normally. As a result, early detection is crucial for more effective therapy. Computed tomography (CT) images supply a rapid diagnosis of brain stroke. However, while doctors are analyzing each brain CT image, time is running fast. This circumstance may lead to result in a delay in treatment and making errors. Therefore, we targeted the utilization of an efficient artificial intelligence algorithm in stroke detection. In this paper, we designed hybrid algorithms that include a new convolution neural networks (CNN) architecture called OzNet and various machine learning algorithms for binary classification of real brain stroke CT images. When we classified the dataset with OzNet, we acquired successful performance. However, for this target, we combined it with a minimum Redundancy Maximum Relevance (mRMR) method and Decision Tree (DT), k-Nearest Neighbors (kNN), Linear Discriminant Analysis (LDA), Naïve Bayes (NB), and Support Vector Machines (SVM). In addition, 4096 significant features were obtained from the fully connected layer of OzNet, and we reduced the dimension of features from 4096 to 250 using the mRMR method. Finally, we utilized these machine learning algorithms to classify important features. As a result, OzNet-mRMR-NB was an excellent hybrid algorithm and achieved an accuracy of 98.42% and AUC of 0.99 to detect stroke from brain CT images.
Recent Progress in Bioprinting: From Bioink Design to Applications
Authors: Zhang Wujie
Published: December 2022

Currently, there are more than 100,000 people on the US national transplant waiting list, and 17 people die each day waiting for an organ transplant [...]
Interpretable and Predictive Deep Neural Network Modeling of the SARS-CoV-2 Spike Protein Sequence to Predict COVID-19 Disease Severity
Authors: Sokhansanj Bahrad A. , Zhao Zhengqiao , Rosen Gail L.
Published: December 2022

Through the COVID-19 pandemic, SARS-CoV-2 has gained and lost multiple mutations in novel or unexpected combinations. Predicting how complex mutations affect COVID-19 disease severity is critical in planning public health responses as the virus continues to evolve. This paper presents a novel computational framework to complement conventional lineage classification and applies it to predict the severe disease potential of viral genetic variation. The transformer-based neural network model architecture has additional layers that provide sample embeddings and sequence-wide attention for interpretation and visualization. First, training a model to predict SARS-CoV-2 taxonomy validates the architecture’s interpretability. Second, an interpretable predictive model of disease severity is trained on spike protein sequence and patient metadata from GISAID. Confounding effects of changing patient demographics, increasing vaccination rates, and improving treatment over time are addressed by including demographics and case date as independent input to the neural network model. The resulting model can be interpreted to identify potentially significant virus mutations and proves to be a robust predctive tool. Although trained on sequence data obtained entirely before the availability of empirical data for Omicron, the model can predict the Omicron’s reduced risk of severe disease, in accord with epidemiological and experimental data.
Polar Phenol Detection in Plasma and Serum: Insights on Sample Pre-Treatment for LC/MS Analysis and Application on the Serum of Corinthian Currant-Fed Rats
Authors: Vasilakopoulou Paraskevi B. , Gousgouni Aimilia-Tatiana , Yanni Amalia E. , Kostomitsopoulos Nikolaos , Karathanos Vaios T. , Chiou Antonia
Published: December 2022

Analysis of plasma and serum provides valuable information on the amounts of polar phenols’ circulating after ingestion. In the present study, protein precipitation (PPT), liquid–liquid extraction (LLE), solid phase extraction (SPE), enzymatic hydrolysis and their combinations were meticulously evaluated for the extraction of a variety of polar phenolic moieties from plasma and serum. The recovery values of the above methods were compared; satisfactory recoveries (>60%) were attained for most analytes. Polar phenol aglycones undergo degradation with enzymatic hydrolysis; however, their extended phase II metabolism makes enzymatic hydrolysis a mandated process for their analysis in such biofluids. Hence, enzymatic hydrolysis followed by LLE was used for the identification of polar phenols in rats’ serum, after the long-term oral consumption of Corinthian Currant. Corinthian Currant is a Greek dried vine product rich in bioactive polar phenolics. Flavonoids and phenolic acids, detected as aglycones, ranged from 0.57 ± 0.08 to 181.66 ± 48.95 and 3.45 ± 1.20 to 897.81 ± 173.96 ng/mL, respectively. The majority of polar phenolics were present as phase II metabolites, representing their fasting state in the blood stream. This is the first study evaluating the presence of polar phenolics in the serum of rats following a long-term diet supplemented with Corinthian Currant as a whole food.
In Vitro Modeling of Diabetes Impact on Vascular Endothelium: Are Essentials Engaged to Tune Metabolism?
Authors: Vorotnikov Alexander V. , Khapchaev Asker Y. , Nickashin Alexey V. , Shirinsky Vladimir P.
Published: December 2022

Angiopathy is a common complication of diabetes mellitus. Vascular endothelium is among the first targets to experience blood-borne metabolic alterations, such as hyperglycemia and hyperlipidemia, the hallmarks of type 2 diabetes. To explore mechanisms of vascular dysfunction and eventual damage brought by these pathologic conditions and to find ways to protect vasculature in diabetic patients, various research approaches are used including in vitro endothelial cell-based models. We present an analysis of the data available from these models that identifies early endothelial cell apoptosis associated with oxidative stress as the major outcome of mimicking hyperglycemia and hyperlipidemia in vitro. However, the fate of endothelial cells observed in these studies does not closely follow it in vivo where massive endothelial damage occurs mainly in the terminal stages of diabetes and in conjunction with comorbidities. We propose that the discrepancy is likely in missing essentials that should be available to cultured endothelial cells to adjust the metabolic state and withstand the immediate apoptosis. We discuss the role of carnitine, creatine, and AMP-activated protein kinase (AMPK) in suiting the endothelial metabolism for long-term function in diabetic type milieu in vitro. Engagement of these essentials is anticipated to expand diabetes research options when using endothelial cell-based models.
Long-Term Synaptic Plasticity Tunes the Gain of Information Channels through the Cerebellum Granular Layer
Authors: Mapelli Jonathan , Boiani Giulia Maria , D’Angelo Egidio , Bigiani Albertino , Gandolfi Daniela
Published: December 2022

A central hypothesis on brain functioning is that long-term potentiation (LTP) and depression (LTD) regulate the signals transfer function by modifying the efficacy of synaptic transmission. In the cerebellum, granule cells have been shown to control the gain of signals transmitted through the mossy fiber pathway by exploiting synaptic inhibition in the glomeruli. However, the way LTP and LTD control signal transformation at the single-cell level in the space, time and frequency domains remains unclear. Here, the impact of LTP and LTD on incoming activity patterns was analyzed by combining patch-clamp recordings in acute cerebellar slices and mathematical modeling. LTP reduced the delay, increased the gain and broadened the frequency bandwidth of mossy fiber burst transmission, while LTD caused opposite changes. These properties, by exploiting NMDA subthreshold integration, emerged from microscopic changes in spike generation in individual granule cells such that LTP anticipated the emission of spikes and increased their number and precision, while LTD sorted the opposite effects. Thus, akin with the expansion recoding process theoretically attributed to the cerebellum granular layer, LTP and LTD could implement selective filtering lines channeling information toward the molecular and Purkinje cell layers for further processing.
The Role of Alpha Oscillations among the Main Neuropsychiatric Disorders in the Adult and Developing Human Brain: Evidence from the Last 10 Years of Research
Authors: Ippolito Giuseppe , Bertaccini Riccardo , Tarasi Luca , Di Gregorio Francesco , Trajkovic Jelena , Battaglia Simone , Romei Vincenzo
Published: December 2022

Alpha oscillations (7–13 Hz) are the dominant rhythm in both the resting and active brain. Accordingly, translational research has provided evidence for the involvement of aberrant alpha activity in the onset of symptomatological features underlying syndromes such as autism, schizophrenia, major depression, and Attention Deficit and Hyperactivity Disorder (ADHD). However, findings on the matter are difficult to reconcile due to the variety of paradigms, analyses, and clinical phenotypes at play, not to mention recent technical and methodological advances in this domain. Herein, we seek to address this issue by reviewing the literature gathered on this topic over the last ten years. For each neuropsychiatric disorder, a dedicated section will be provided, containing a concise account of the current models proposing characteristic alterations of alpha rhythms as a core mechanism to trigger the associated symptomatology, as well as a summary of the most relevant studies and scientific contributions issued throughout the last decade. We conclude with some advice and recommendations that might improve future inquiries within this field.
Methylene Blue Delivery Mediated by Focused Ultrasound-Induced Blood–Brain Barrier Disruption Reduces Neural Damage and Amyloid-Beta Plaques by AQP-4 Upregulation
Authors: Choi Hyo Jin , Han Mun , Jung Byeongjin , Hong Yu-Ri , Shin Seulgi , Lim Sungsu , Lee Eun-Hee , Kim Yun Kyung , Park Juyoung
Published: December 2022

Alzheimer’s disease (AD) is the most prevalent neurodegenerative disease worldwide, causing progressive cognitive decline, memory impairment, and neurological deficits. Methylene blue (MB), an antioxidant, has emerged as a potential drug for the treatment of AD owing to its cognitive improvement and neuroprotective functions. Despite the small molecular size of MB, which can cross the BBB, the therapeutic effective dosage using a BBB-permeable delivery system in a specific brain localization remains unclear. In this study, we presented magnetic resonance–guided focused ultrasound (MRgFUS) as a delivery system to enhance BBB permeability for the effective treatment of AD. MRgFUS using two ultrasound intensities (0.25 and 0.32 MPa) was used to intravenously deliver MB to the hippocampal region. Compared with treatment with 0.25 MPa FUS, treatment with 0.32 MPa FUS significantly enhanced MB brain accumulation. Deposition of amyloid-β (Aβ) plaques and neural cell damage was significantly reduced in 0.32 MPa FUS/MB-treated APP/PS1 mice. Furthermore, aquaporin-4 expression increased significantly in the 0.32 MPa FUS and 0.32 MPa FUS/MB groups without glial fibrillary acidic protein activation. The results from this study demonstrate that FUS improved MB delivery to the brain, and FUS/MB combination treatment reduced the number of Aβ plaques. This study revealed the potential of FUS-BBBD as an effective strategy to enhance the efficacy of therapeutic drugs for AD.