bluuebunny/crossref_metadata_2025 huggingface dataset:
Ghosting, Breadcrumbing, Catfishing: A Corpus Analysis of English Borrowings in the Spanish Speaking World
Authors: Rull García Irene , Bove Kathryn P.
Published: May 2022

The study aims to contribute to our understanding of the situation of languages in contact and the phenomenon of linguistic borrowings in the modern online world. The current study investigates the use of English terms borrowed to describe romantic relationships in Spanish. We use a list of terms presented in GQ Spain, a men’s culture, fashion and style magazine, as popular terms in 2020 to describe (a lack of) love in romantic relationships. In order to analyze the actual use of these borrowings in Spanish, we collected data from the Corpus del Español NOW (2012–2019), focusing on the number of occurrences of each English borrowing, level of morphological adaptation, co-occurrence of translations or explanations, date of first use and location of use. Overall, 11 of the 20 terms, such as ghosting, gaslighting or benching, appeared in the corpus. We note the presence of quotation marks, parentheses or uppercase letters in some cases, but it was observed that most examples keep their English form. However, many terms appeared with an explanation or translation, reflecting the novelty of the borrowing. Data regarding dates and countries were collected in order to set the year they were integrated with the new meaning (2013–2019). The country with the highest number of cases was Argentina, and there were a substantial number of cases in other Spanish-speaking countries. Overall, these findings show an increase in the incorporation of these borrowings over the years in the Spanish lexicon.
The Conceptual Model of Role Stress and Job Burnout in Judges: The Moderating Role of Career Calling
Authors: Pereira Sandra Patrícia Marques , Correia Pedro Miguel Alves Ribeiro , Da Palma Patrícia Jardim , Pitacho Liliana , Lunardi Fabrício Castagna
Published: May 2022

Judges are the central actors in the organization and functioning of the judicial system. Concerns about work efficiency, driven by the European Commission for the Efficiency of Justice, led countries to adopt a set of reforms in line with private sector ideals applied to the public field to better manage their financial and human resources. In the last decades, the Portuguese judicial system has undergone a reform based on New Public Management principles by adopting the new Law on the Organization of the Judiciary System (LOSJ), significantly altering judges’ duties, who beyond their traditional role of applying the law, perform the additional role of court-of-law judge-manager. The objective of this study is to explore the influence of role conflict and role ambiguity in occupational burnout among judges and to analyze the influence of calling orientation as a moderating variable, so as to present a conceptual model of role-stress management among the judiciary. Theoretically, this work contributes to the literature on role-stress management through its introduction of calling moderation, as well as to the literature on the positive influence of calling on burnout. In terms of its practical implications, the work contributes to a reconsideration of the current organizational structure of judicial work.
The Effect of Magnesium Hydroxide Addition on the Extinguishing Efficiency of Sodium Bicarbonate Powders
Authors: Izak Piotr , Biel Mateusz , Mastalska-Popławska Joanna , Janik Paweł , Mortka Piotr , Lesiak Piotr
Published: May 2022

This article analyzes the possibility of the modification of BC powder (a mixture of sodium bicarbonate and calcium carbonate) with magnesium hydroxide (Mg(OH)2). Extinguishing efficiency as well as the influence of this additive on other physicochemical properties were determined by performing a 13B fire test, rheological measurements of the powders, thermal tests (thermogravimetry (TG) and differential scanning calorimetry (DSC) in combination with quadrupole mass spectrometry (QMS)) and microscopic observations of the powders’ surface (scanning electron microscope (SEM) with energy dispersive X-ray analysis (EDS)). It was found that the increase of the Mg(OH)2 content causes deterioration of the rheological properties by increasing the slope angle of the flow curve in relation to the normal stress (the tangent of the flow curve slope varying from 0.258 for 5% of Mg(OH)2 up to 0.330 for 20% of Mg(OH)2). However, at the same time, the increased content of Mg(OH)2 increases the total energy of the chemical decomposition reaction (from −47.27 J/g for 5% of Mg(OH)2 up to −213.6 J/g for 20% of Mg(OH)2) resulting in the desirable higher level of heat removal from the fire. The initial extinguishing effect of the fire becomes more effective as the hydroxide content increases (within the first 2 s), but at a later stage (from t = 63 s), the temperature is no longer sufficient (it is below 350 °C) for thermal decomposition of Mg(OH)2. As such, the optimal content of Mg(OH)2 is 10–15%. The obtained results allowed for the assessment of the impact of individual powder components on its extinguishing effect and will contribute to the development of science in the field of developing new types of extinguishing powders.
Influence of Industrial Metakaolin Waste on Autoclaved Fiber Cement Properties Changes in Standard Fire Environment
Authors: Veliseicik Tomas , Zurauskiene Ramune , Kligys Modestas , Dauksevic Mark
Published: May 2022

An investigation was conducted on the influence that industrial metakaolin waste (IMW) has on the properties of autoclaved fiber cement composition (FCC) samples. FCC samples were made from fiber cement plate’s typical components using the same proportions. In samples, IMW was used instead of cement in 10%, 20%, 30% proportions and in 50%, 100% proportions instead of ground quartz. Differential thermal analysis (DTG), thermogravimetric analysis (TGA), ultrasound pulse velocity (UPV), density, porosity and optical microscope (OM) research methods were used to identify the micro and macrostructure of samples. Mechanical properties were evaluated using flexural and compressive strength research methods. It was established that IMW was used instead of cement in fiber cement composition samples up to 10% and in fiber cement composition samples instead of ground quartz forms density microstructure structure because of Al-rich tobermorite. As a result, the flexural and compressive strength increased. Samples with higher content of IMW instead of cement had unreacted IMW and a less dense microstructure. In this case, flexural and compressive strength decreased. All FCC samples were fired in a standard fire curve (ISO 842) for 30 min. Samples of mechanical properties were established by doing flexural and compressive strength tests, and which results showed the same trends.
Finger Bending Sensing Based on Series-Connected Fiber Bragg Gratings
Authors: Lin Qijing , Yao Kun , Zhao Na , Jiao Yunjing , Wang Zelin , Tian Bian , Zhao Libo , Peng Gangding , Jiang Zhuangde
Published: May 2022

Smart wearable devices are occupying an increasingly important position in scientific research and people’s life fields. As an indispensable component of smart wearable devices, sensors play a crucial role in their sensing and feedback capabilities. In this paper, we investigate the bending gesture sensing for the most dexterous part of human anatomy, the finger. Based on series-connected fiber Bragg gratings (FBGs), recognition of finger bending posture is achieved by MATLAB modeling and the cubic spline interpolation.
Manufacturing of Complex Silicon–Carbon Structures: Exploring SixCy Materials
Authors: Oglesby Skyler , Ivanov Sergei A. , Londonõ-Calderon Alejandra , Pete Douglas , Pettes Michael Thompson , Jones Andrew Crandall , Chabi Sakineh
Published: May 2022

This paper reports on the manufacturing of complex three-dimensional Si/C structures via a chemical vapor deposition method. The structure and properties of the grown materials were characterized using various techniques including scanning electron microscopy, aberration-corrected transmission electron microscopy, confocal Raman spectroscopy, and X-ray photoelectron spectroscopy. The spectroscopy results revealed that the grown materials were composed of micro/nanostructures with various compositions and dimensions. These included two-dimensional silicon carbide (SiC), cubic silicon, and various SiC polytypes. The coexistence of these phases at the nano-level and their interfaces can benefit several Si/C-based applications ranging from ceramics and structural applications to power electronics, aerospace, and high-temperature applications. With an average density of 7 mg/cm3, the grown materials can be considered ultralightweight, as they are three orders of magnitude lighter than bulk Si/C materials. This study aims to impact how ceramic materials are manufactured, which may lead to the design of new carbide materials or Si/C-based lightweight structures with additional functionalities and desired properties.
Distributed Dynamic Predictive Control for Multi-AUV Target Searching and Hunting in Unknown Environments
Authors: Li Juan , Li Chengyue , Zhang Honghan
Published: May 2022

The research and development of the ocean has been gaining in popularity in recent years, and the problem of target searching and hunting in the unknown marine environment has been a pressing problem. To solve this problem, a distributed dynamic predictive control (DDPC) algorithm based on the idea of predictive control is proposed. The task-environment region information and the input of the AUV state update are obtained by predicting the state of multi-AUV systems and making online task optimization decisions and then locking the search area for the following moment. Once a moving target is found in the search process, the AUV conducts a distributed hunt based on the theory of potential points, which solves the problem of the reasonable distribution of potential points during the hunting process and realizes the formation of hunting rapidly. Compared with other methods, the simulation results show that the algorithm exhibits high efficiency and adaptability.
Digital Twins-Based Production Line Design and Simulation Optimization of Large-Scale Mobile Phone Assembly Workshop
Authors: Zhao Rongli , Zou Guangxin , Su Qianyi , Zou Shangwen , Deng Wenshun , Yu Ailin , Zhang Hao
Published: May 2022

The mobile phone is a typical 3C electronic product characterized by frequent replacement, multiple product specifications, high flexibility, high-frequency production line switching, and urgent delivery time during production. Therefore, the optimized design of the mobile phone production workshop is crucial. This paper takes the assembly process of a specific type of mobile phone assembly as the research object and adopts the heuristic balance method to combine the production procedures. Moreover, it considers the automation degree of the process and the demand for production line rhythm to carry out station division and working hours design for the assembly process. The advantages and disadvantages of the plug-and-play production line and unit production line architecture are integrated, aiming at the production line’s construction cost and unit area capacity. A hybrid workshop with a mixed combination of two types of production lines is designed and an optimization model of hybrid workshop design is established. The semi-physical simulation technology of digital twins is utilized to verify the proposed design scheme to achieve the balance optimization of the production line, improve production efficiency, and reduce production costs. This work provides a technical scheme for designing and optimizing large-scale mobile phone assembly workshops with multi-batch and high-frequency production changes.
Measuring Variable Importance in Generalized Linear Models for Modeling Size of Loss Distributions
Authors: Xie Shengkun , Luo Rebecca
Published: May 2022

Predictive modeling is a critical technique in many real-world applications, including auto insurance rate-making and the decision making of rate filings review for regulation purposes. It is also important in predicting financial and economic risk in business and economics. Unlike testing hypotheses in statistical inference, results obtained from predictive modeling serve as statistical evidence for the decision making of the underlying problem and discovering the functional relationship between the response variable and the predictors. As a result of this, the variable importance measures become an essential aspect of helping to better understand the contributions of predictors to the built model. In this work, we focus on the study of using generalized linear models (GLM) for the size of loss distributions. In addition, we address the problem of measuring the importance of the variables used in the GLM to further evaluate their potential impact on insurance pricing. In this regard, we propose to shift the focus from variable importance measures of factor levels to factors themselves and to develop variable importance measures for factors included in the model. Therefore, this work is exclusively for modeling with categorical variables as predictors. This work contributes to the further development of GLM modeling to make it even more practical due to this added value. This study also aims to provide benchmark estimates to allow for the regulation of insurance rates using GLM from the variable importance aspect.
Generation of Higher-Order Hermite–Gaussian Modes via Cascaded Phase-Only Spatial Light Modulators
Authors: Yan Manjun , Ma Long
Published: May 2022

The spatial distribution of higher-order Hermite–Gaussian (HG) modes is more complicated than the fundamental mode, and the characteristics of different modes and their orthogonal characteristics have essential applications in the fields of measurement, imaging, and large-capacity communications. The main issue in future applications is how to efficiently generate higher-order HG modes. The spatial light modulator has high spatial resolution and excellent maneuverability, so it is a simple and effective way to generate higher-order HG modes. Here, the efficient generation of higher-order HG modes via cascaded spatial light modulators was experimentally investigated. For the HG90 mode, the conversion efficiency is 61%. The method with high conversion efficiency has promising application potentials in biophotonics, laser physics, and quantum information.
Geometric Metric Learning for Multi-Output Learning
Authors: Gao Huiping , Ma Zhongchen
Published: May 2022

Due to its wide applications, multi-output learning that predicts multiple output values for a single input at the same time is becoming more and more attractive. As one of the most popular frameworks for dealing with multi-output learning, the performance of the k-nearest neighbor (kNN) algorithm mainly depends on the metric used to compute the distance between different instances. In this paper, we propose a novel cost-weighted geometric mean metric learning method for multi-output learning. Specifically, this method learns a geometric mean metric which can make the distance between the input embedding and its correct output be smaller than the distance between the input embedding and the outputs of its nearest neighbors. The learned geometric mean metric can discover output dependencies and move the instances with different outputs far away in the embedding space. In addition, our objective function has a closed solution, and thus the calculation speed is very fast. Compared with state-of-the-art methods, it is easier to explain and also has a faster calculation speed. Experiments conducted on two multi-output learning tasks (i.e., multi-label classification and multi-objective regression) have confirmed that our method provides better results than state-of-the-art methods.
Fisher, Bayes, and Predictive Inference
Authors: Zabell Sandy
Published: May 2022

We review historically the position of Sir R.A. Fisher towards Bayesian inference and, particularly, the classical Bayes–Laplace paradigm. We focus on his Fiducial Argument.
Developed Gorilla Troops Technique for Optimal Power Flow Problem in Electrical Power Systems
Authors: Shaheen Abdullah , Ginidi Ahmed , El-Sehiemy Ragab , Elsayed Abdallah , Elattar Ehab , Dorrah Hassen T.
Published: May 2022

This paper presents a developed solution based on gorilla troops optimization technique for OPFP in EPSs. The GTOT is motivated by gorillas’ group behaviors in which several methods are replicated, such as migration to an unfamiliar location, traveling to other gorillas, migration toward a specific spot, accompanying the silverback, and competing for adult females. The multi-dimension OPFP in EPSs is examined in this article with numerous optimizing objectives of fuel cost, power losses, and harmful pollutants. The system’s power demand and transmission losses must be met as well. The developed GTOT’s evaluation is conducted using an IEEE standard 30-bus EPS and practical EPS from Egypt. The created GTOT is employed in numerous evaluations and statistical analyses using many modern methods such as CST, GWT, ISHT, NBT, and SST. When compared to other similar approaches in the literature, the simulated results demonstrate the GTOT’s solution efficiency and robustness.
Return on Advertising Spend Prediction with Task Decomposition-Based LSTM Model
Authors: Moon Hyeonseok , Lee Taemin , Seo Jaehyung , Park Chanjun , Eo Sugyeong , Aiyanyo Imatitikua D. , Park Jeongbae , So Aram , Ok Kyoungwha , Park Kinam
Published: May 2022

Return on advertising spend (ROAS) refers to the ratio of revenue generated by advertising projects to its expense. It is used to assess the effectiveness of advertising marketing. Several simulation-based controlled experiments, such as geo experiments, have been proposed recently. This refers to calculating ROAS by dividing a geographic region into a control group and a treatment group and comparing the ROAS generated in each group. However, the data collected through these experiments can only be used to analyze previously constructed data, making it difficult to use in an inductive process that predicts future profits or costs. Furthermore, to obtain ROAS for each advertising group, data must be collected under a new experimental setting each time, suggesting that there is a limitation in using previously collected data. Considering these, we present a method for predicting ROAS that does not require controlled experiments in data acquisition and validates its effectiveness through comparative experiments. Specifically, we propose a task deposition method that divides the end-to-end prediction task into the two-stage process: occurrence prediction and occurred ROAS regression. Through comparative experiments, we reveal that these approaches can effectively deal with the advertising data, in which the label is mainly set to zero-label.
Capacity-Oriented Train Scheduling of High-Speed Railway Considering the Operation and Maintenance of Rolling Stock
Authors: Zhou Wenliang , Li Sha , Kang Jing , Huang Yu
Published: May 2022

The capacity of some busy rail lines is increasingly tight and passenger demand far exceeds the railway capacity. To schedule as many trains as possible in order to satisfy more transportation demands, we studied the capacity-oriented train scheduling problem. While most approaches focus only on increasing the capacity of the rail line, this research considers both the time-space distribution of transportation demands and the operation and maintenance of rolling stock. To solve this problem, we first constructed a time-space network to describe the time-space path of rolling stock. We then proposed an integer planning model with rolling stock maintenance and the OD service frequency constraints to maximize the number of running arcs in rail sections. After decomposing this model by introducing some Lagrangian multipliers to relax its hard constraints, we proposed a Lagrangian relaxation-based decomposition algorithm, including two path search sub-algorithms for rolling stock to optimize both the relaxed and the feasible solutions. Finally, we conducted a computation study on a practical double-track high-speed railway line to test the performance of this algorithm. It reports that the train timetables and the operation of rolling stock are well managed.
A New Case-Mix Classification Method for Medical Insurance Payment
Authors: Liu Hongliang , Tan Jinpeng , Jon Kyongson , Zhu Wensheng
Published: May 2022

Rapidly rising medical expenses can be controlled by a well-designed medical insurance payment system with the ability to ensure the stability and development of medical insurance funds. At present, China is in the stage of exploring the reform of the medical insurance payment system. One of the significant tasks is to establish an appropriate reimbursement model for disease treatment expenses, so as to meet the needs of patients for medical services. In this paper, we propose a case-mixed decision tree method that considers the homogeneity within the same case subgroup as well as the heterogeneity between different case subgroups. The optimal case mix is determined by maximizing the inter-group difference and minimizing the intra-group difference. In order to handle the instability of the tree-based method with a small amount of data, we propose a multi-model ensemble decision tree method. This method first extracts and merges the inherent rules of the data by the stacking-based ensemble learning method, then generates a new sample set by aggregating the original data with the additional samples obtained by applying these rules, and finally trains the case-mix decision tree with the augmented dataset. The proposed method ensures the interpretability of the grouping rules and the stability of the grouping at the same time. The experimental results on real-world data demonstrate that our case-mix method can provide reasonable medical insurance payment standards and the appropriate medical insurance compensation payment for different patient groups.
A Hash-Based Quantum-Resistant Designated Verifier Signature Scheme
Authors: Thanalakshmi P. , Anitha R. , Anbazhagan N. , Park Chulho , Joshi Gyanendra Prasad , Seo Changho
Published: May 2022

Digital signatures are unsuitable for specific applications that are sensitive on a personal or commercial level because they are universally verifiable. Jakobsson et al. proposed the Designated Verifier Signature (DVS) system, which only allows the intended verifier to validate a message’s signature. It prohibits the disclosure of a conviction to a third party. This functionality is useful in applications that require both authenticity and signer privacy, such as electronic voting and tender calls. The vast majority of current DVS schemes are based on difficult number theory problems such as integer factorization or discrete log problems over various groups. The development of a large-scale quantum computer would render these schemes unsafe. As a result, it is critical to develop quantum-resistant DVS methods. In both quantum and classical computers, signatures based on one-way functions are more efficient and secure. They have several advantages over digital signatures based on trapdoor functions. As a result, hash-based signatures are now considered viable alternatives to number-theoretic signatures. Existing hash-based signatures, on the other hand, are easily verifiable by anyone. As a result, they do not protect the signer’s identity. In addition, they are one-time signatures. This paper presents a hash-based multi-time designated verifier signature scheme that ensures signer anonymity. The unforgeability of the signature scheme is also tested in the random oracle model under chosen message attack. The properties such as non-transferability and non-delegatability are investigated.
Estimation of Linear Regression with the Dimensional Analysis Method
Authors: Pérez-Domínguez Luis , Garg Harish , Luviano-Cruz David , García Alcaraz Jorge Luis
Published: May 2022

Dimensional Analysis (DA) is a mathematical method that manipulates the data to be analyzed in a homogenized manner. Likewise, linear regression is a potent method for analyzing data in diverse fields. At the same time, data visualization has gained attention in tendency study. In addition, linear regression is an important topic to address predictive models and patterns in data study. However, it is still pending to attack the manipulation of uncertainty related to the data transformation. In this sense, this work presents a new contribution with linear regression, combining the Dimensional Analysis (DA) to address instability and error issues. In addition, our method provides a second contribution related to including the decision maker’s attitude involved in the study. Therefore, the experimentation shows that DA manipulates the regression problem under a complex situation that the outcome may have in the investigation. A real-life case study is used to demonstrate our proposal.
Effects of Magnetic Fields, Coupled Stefan Blowing and Thermodiffusion on Ferrofluid Transport Phenomena
Authors: Hamid Rohana Abdul , Nazar Roslinda , Naganthran Kohilavani , Pop Ioan
Published: May 2022

The paramagnetic feature of ferrofluid allows it to be utilised in electronic devices and improvise fluid circulation in transformer windings. Hence, the present article aims to conduct the numerical study of ferrofluid boundary layer flow along with the Stefan blowing, velocity and thermal slip, and Soret effects within the stagnation region over a stretching/shrinking surface. The governing equations were solved numerically using the bvp4c function in the MATLAB computing package. Based on the results, a stronger magnetic field of ferrofluid was needed to identify the numerical solutions past the shrinking surface, while the Stefan blowing diminished the solution’s availability. More than one solution is acquired for some specific values of the shrinking parameter, and the stability analysis validated that only one solution is reliable and stable.
Estimating Forward-Looking Stock Correlations from Risk Factors
Authors: Schadner Wolfgang , Traut Joshua
Published: May 2022

This study provides fully mathematically and economically feasible solutions to estimating implied correlation matrices in equity markets. Factor analysis is combined with option data to receive ex ante beliefs for cross-sectional correlations. Necessary conditions for implied correlation matrices to be realistic, both in a mathematical and in an economical sense, are developed. An evaluation of existing models reveals that none can comply with the developed conditions consistently. This study overcomes this pitfall and provides two estimation models via exploiting the underlying factor structure of returns. The first solution reformulates the task into a constrained nearest correlation matrix problem. This method can be used either as a stand-alone instrument or as a repair tool to re-establish the feasibility of another model’s estimate. One of these properties is matrix invertibility, which is especially valuable for portfolio optimization tasks. The second solution transforms common risk factors into an implied correlation matrix. The solutions are evaluated upon empirical experiments of S&P 100 and S&P 500 data. They turn out to require modest computational power and comply with the developed constraints. Thus, they provide practitioners with a reliable method to estimate realistic implied correlation matrices.
Approximation of Real Functions by a Generalization of Ismail–May Operator
Authors: Holhoş Adrian
Published: May 2022

In this paper, we generalize a sequence of positive linear operators introduced by Ismail and May and we study some of their approximation properties for different classes of continuous functions. First, we estimate the error of approximation in terms of the usual modulus of continuity and the second-order modulus of Ditzian and Totik. Then, we characterize the bounded functions that can be approximated uniformly by these new operators. In the last section, we obtain the most important results of the paper. We give the complete asymptotic expansion for the operators and we deduce a Voronovskaya-type theorem, results that hold true for smooth functions with exponential growth.
Thermodynamic Interpretation of a Machine-Learning-Based Response Surface Model and Its Application to Pharmacodynamic Synergy between Propofol and Opioids
Authors: Wang Hsin-Yi , Liou Jing-Yang , Lin Chen , Ting Chien-Kun , Chang Wen-Kuei , Lo Men-Tzung , Chen Chien-Chang
Published: May 2022

Propofol and fentanyl are commonly used agents for the induction of anesthesia, and are often associated with hemodynamic disturbances. Understanding pharmacodynamic impacts is vital for parasympathetic and sympathetic tones during the anesthesia induction period. Inspired by the thermodynamic interaction between drug concentrations and effects, we established a machine-learning-based response surface model (MLRSM) to address this predicament. Then, we investigated and modeled the biomedical phenomena in the autonomic nervous system. Our study prospectively enrolled 60 patients, and the participants were assigned to two groups randomly and equally. Group 1 received propofol first, followed by fentanyl, and the drug sequence followed an inverse procedure in Group 2. Then, we extracted and analyzed the spectrograms of electrocardiography (ECG) and pulse photoplethysmography (PPG) signals after induction of propofol and fentanyl. Eventually, we utilized the proposed MLRSM to evaluate the relationship between anesthetics and the integrity/balance of sympathetic and parasympathetic activity by employing the power of high-frequency (HF) and low-frequency (LF) bands and PPG amplitude (PPGA). It is worth emphasizing that the proposed MLRSM exhibits a similar mathematical form to the conventional Greco model, but with better computational performance. Furthermore, the MLRSM has a theoretical foundation and flexibility for arbitrary numbers of drug combinations. The modeling results are consistent with the previous literature. We employed the bootstrap algorithm to inspect the results’ consistency and measure the various statistical fluctuations. Then, the comparison between the modeling and the bootstrapping results was used to validate the statistical stability and the feasibility of the proposed MLRSM.
Joint Universality in Short Intervals with Generalized Shifts for the Riemann Zeta-Function
Authors: Laurinčikas Antanas
Published: May 2022

In the paper, the simultaneous approximation of a tuple of analytic functions in the strip {s=σ+it∈C:1/2<σ<1} by shifts (ζ(s+iφ1(τ)),…,ζ(s+iφr(τ))) of the Riemann zeta-function ζ(s) with a certain class of continuously differentiable increasing functions φ1,…,φr is considered. This class of functions φ1,…,φr is characterized by the growth of their derivatives. It is proved that the set of mentioned shifts in the interval [T,T+H] with H=o(T) has a positive lower density. The precise expression for H is described by the functions (φj(τ))1/3(logφj(τ))26/15 and derivatives φj′(τ). The density problem is also discussed. An example of the approximation by a composition F(ζ(s+iφ1(τ)),…,ζ(s+iφr(τ))) with a certain continuous operator F in the space of analytic functions is given.
In Vivo Nutritional Assessment of the Microalga Nannochloropsis gaditana and Evaluation of the Antioxidant and Antiproliferative Capacity of Its Functional Extracts
Authors: Martínez Rosario , García-Beltrán Alejandro , Kapravelou Garyfallia , Mesas Cristina , Cabeza Laura , Perazzoli Gloria , Guarnizo Palmira , Rodríguez-López Alberto , Andrés Vallejo Roberto , Galisteo Milagros , Aranda Pilar , Prados Jose , López-Jurado María , Melguizo Consolación , Porres Jesus M.
Published: May 2022

Nannochloropsis gaditana is a microalga with interesting nutritional and functional value due to its high content of protein, polyunsaturated fatty acids, and bioactive compounds. However, the hardness of its cell wall prevents accessibility to these components. This work aimed to study the effect of a treatment to increase the fragility of the cell wall on the bioavailability of its nutrients and functional compounds. The antioxidant and antiproliferative capacity of functional extracts from treated and untreated N. gaditana was assessed, and the profile of bioactive compounds was characterized. Furthermore, to study the effect of treatment on its nutrient availability and functional capacity, an in vivo experiment was carried out using a rat experimental model and a 20% dietary inclusion level of microalgae. Functional extracts from treated N. gaditana exhibited higher antioxidant activity than the untreated control. Furthermore, the treated microalga induced hypoglycemic action, higher nitrogen digestibility, and increased hepatic antioxidant activity. In conclusion, N. gaditana has interesting hepatoprotective, antioxidant, and anti-inflammatory potential, thus proving itself an ideal functional food candidate, especially if the microalga is treated to increase the fragility of its cell wall before consumption.
Clinical Study of Serum Serotonin as a Screening Marker for Anxiety and Depression in Patients with Type 2 Diabetes
Authors: Moroianu Lavinia-Alexandra , Cecilia Curis , Ardeleanu Valeriu , Pantea Stoian Anca , Cristescu Vasilica , Barbu Raisa-Eloise , Moroianu Marius
Published: May 2022

Over time, studies have shown the importance of determining serotonin levels to diagnose somatic and psychiatric disorders. There are theoretical premises and practical ways to achieve a subtle correlation between the existence of comorbid psychiatric disorders and somatic diseases caused by the changes observed in serotonin levels. The present study, classified as retrospective and quantitative, provides evidence for determining the serotonin levels in patients with diabetes and anxiety or depression. A total of 48 patients with diabetes type 2 were enrolled in the study. Blood glucose level, glycated haemoglobin, and serum serotonin were noted, and they completed Hamilton A and Beck Depression Inventory questionnaires. We found robust correlations between serum serotonin and blood glucose (Sig. = 0.008), serum serotonin and HbA1c (Sig. = 0.007), serum serotonin and anxiety (Sig. = 0.000), and serum serotonin and depression (Sig. = 0.000). It is also noteworthy that women recorded extreme values higher than men for glycated haemoglobin (95% confidence interval: 6.92–7.79 in women and 6.30–7.23 in men). In conclusion, using serotonin as a marker of the mentioned diseases in clinical practice is of significant utility, considering the benefits in terms of the evolution and prognosis of comorbidities in patients with type 2 diabetes and anxiety and depressive symptoms.
Value of Serum Sirtuin-1 (SIRT1) Levels and SIRT1 Gene Variants in Periodontitis Patients
Authors: Kriaučiūnas Albertas , Liutkevičienė Rasa , Gedvilaitė Greta , Kaikarytė Kristė , Vilkevičiūtė Alvita , Gleiznys Darius , Pacauskienė Ingrida , Žekonis Gediminas
Published: May 2022

Background and Objectives: Periodontitis is a multifactorial inflammatory disease associated with biofilm dysbiosis and is defined by progressive periodontium destruction. Genes largely regulate this entire process. SIRTs are a group of histone deacetylases (HDACs) intimately involved in cell metabolism and are responsible for altering and regulating numerous cell functions. Understanding SIRTs and their functions in periodontitis may be useful for therapeutic treatment strategies in the future. The aim of our study was to investigate the associations amid SIRT1 single-gene nucleotide polymorphisms (rs3818292, rs3758391, and rs7895833) and SIRT1 serum levels for patients affected by periodontitis in the Caucasian population. Materials and Methods: The study included 201 patients affected by periodontitis and 500 healthy controls. DNA extraction from peripheral leukocytes was carried out using commercial kits. The real-time PCR method was selected for the determination of the genotype of the periodontitis patients and the control group. The ELISA method was used to measure the SIRT1 concentration. A statistical data analysis was performed using “BM SPSS Statistics 27.0” software. Results: The SIRT1 rs3818292 AG genotype was associated with a 2-fold and 1.9-fold increase in the development of periodontitis under the codominant and overdominant models (OR = 1.959; CI = 1.239–3.098; p = 0.004; and OR = 1.944; CI = 1.230–3.073; p = 0.004, respectively). The serum SIRT1 levels were not statistically significantly different between subjects in the periodontitis and control groups (0.984 (5.159) ng/mL vs. 0.514 (7.705) ng/mL, p = 0.792). Conclusions: in our study, the genotypes and alleles of SIRT1 rs3818292, rs3758391, and rs7895833 statistically significantly differed between the periodontitis and control groups, exclusively in the male population and subjects older than 60 years.
In Utero Electroporation for Manipulation of Specific Neuronal Populations
Authors: Yamashiro Kotaro , Ikegaya Yuji , Matsumoto Nobuyoshi
Published: May 2022

The complexity of brain functions is supported by the heterogeneity of brain tissue and millisecond-scale information processing. Understanding how complex neural circuits control animal behavior requires the precise manipulation of specific neuronal subtypes at high spatiotemporal resolution. In utero electroporation, when combined with optogenetics, is a powerful method for precisely controlling the activity of specific neurons. Optogenetics allows for the control of cellular membrane potentials through light-sensitive ion channels artificially expressed in the plasma membrane of neurons. Here, we first review the basic mechanisms and characteristics of in utero electroporation. Then, we discuss recent applications of in utero electroporation combined with optogenetics to investigate the functions and characteristics of specific regions, layers, and cell types. These techniques will pave the way for further advances in understanding the complex neuronal and circuit mechanisms that underlie behavioral outputs.
Microforming a Miniature Cup-Shaped Internal Gear Using a Cold Lateral Extrusion Process
Authors: Jiang Cho-Pei , Chen Po-Shen , Erisov Yaroslav , Chen Chang-Cheng
Published: May 2022

This study determines the micro forming of copper alloy to form a cup-shaped internal gear. The as received material, copper alloy C1100, is annealed to obtain the initial grains and to determine the effect of the initial grain size on the mechanical properties, the deformability and the filling rate for a tooth cavity. The experimental results show that the specimen that is annealed at a temperature of 500 °C has an initial grain size of 25.5 µm, which increases ductility and allows a cup-shaped internal gear to be formed with the highest filling rate of 99.2%. Except for the as received material, the Vickers hardness, the extrusion force and the filling rate decrease as the initial grain size increases. The hardness is approximately homogeneous along the addendum and dedendum edges but gradually becomes less homogeneous along the edge of the tooth profile from the addendum to dedendum.
The Obesogenic and Glycemic Effect of Bariatric Surgery in a Family with a Melanocortin 4 Receptor Loss-of-Function Mutation
Authors: Grinbaum Ronit , Beglaibter Nahum , Mitrani-Rosenbaum Stella , Kaplan Lee M. , Ben-Zvi Danny
Published: May 2022

We report the long-term response to bariatric surgery in a singular family of four adolescents with severe obesity (41–82 kg/m2), homozygous for the C271R loss-of-function mutation in the melanocortin 4 receptor (MC4R), and three adults heterozygous for the same mutation. All patients had similar sociodemographic backgrounds and were followed for an average of 7 years. Three of the four homozygous patients regained their full weight (42–77 kg/m2), while the fourth lost weight but remained obese with a body mass index of 60 kg/m2. Weight regain was associated with relapse of most comorbidities, yet hyperglycemia did not relapse or was delayed. A1c levels were reduced in homozygous and heterozygous patients. The long-term follow-up data on this very unique genetic setting show that weight loss and amelioration of obesity following bariatric surgery require active MC4R signaling, while the improvement in glycemia is in part independent of weight loss. The study validates animal models and demonstrates the importance of biological signaling in the regulation of weight, even after bariatric surgery.
Review of Treatments for Oropharyngeal Fungal Infections in HIV/AIDS Patients
Authors: Noël de Tilly Alexandre , Tharmalingam Sujeenthar
Published: May 2022

HIV and AIDS patients are susceptible to opportunistic infections. Oral candidiasis or thrush is the primary manifestation of fungal infection in these patients. The primary objective of this literature review was to summarize established and novel treatment options for oropharyngeal fungal infections in HIV/AIDS patients. Azoles and polyenes are the two primary antifungal drug classes employed for the treatment of oral candidiasis. A literature review was conducted on Medline and Google Scholar in October of 2021 using the keywords “Oral”, “Fungal”, “HIV”, and “Treatment”. Included studies were clinical trials, meta-analyses, and randomized controlled trials. Nineteen studies regarding azoles, polyenes, and novel treatments for oropharyngeal fungal infections in HIV/AIDS patients were examined in this review. The primary concern demonstrated from these studies is increased reports of resistance to antifungals, especially development of fluconazole resistance. Additionally, studies demonstrated that fluconazole had different relapse durations comparative to other medications, and that posaconazole could possibly act as an alternate form of treatment. Nystatin was indicated as a first-line therapy for thrush in multiple studies but could be upstaged by miconazole nitrate in resource-poor settings. Amphotericin B was an effective treatment option and was shown to be resilient in terms of fungal resistance, however potent adverse side effects were reported. Alternative treatments, such as immunoglobulin antibodies and lemon grass, revealed promising antifungal effects for immunocompromised individuals. Taken together, this review provides a thorough summary of treatment options of oropharyngeal fungal infections in HIV/AIDS patients.
Cyanobacterial Root Associations of Leafless Epiphytic Orchids
Authors: Tsavkelova Elena A. , Glukhareva Irina D. , Volynchikova Elena A. , Egorova Maria A. , Leontieva Maria R. , Malakhova Dina V. , Kolomeitseva Galina L. , Netrusov Alexander I.
Published: May 2022

The leafless orchids are rare epiphytic plants with extremely reduced leaves, and their aerial roots adopted for photosynthesis. The beneficial plant–microbial interactions contribute significantly to host nutrition, fitness, and growth. However, there are no data available on the bacterial associations, inhabiting leafless orchids. Here, we describe the diversity of cyanobacteria, which colonize the roots of greenhouse Microcoelia moreauae and Chiloschista parishii. The biodiversity and structure of the cyanobacterial community were analyzed using a complex approach, comprising traditional cultivable techniques, denaturing gradient gel electrophoresis (DGGE), and phylogenetic analysis, as well as the light and scanning electron microscopy (SEM). A wide diversity of associated bacteria colonize the root surface, forming massive biofilms on the aerial roots. The dominant populations of filamentous nitrogen-fixing cyanobacteria belonged to the orders Oscillatoriales, Synechococcales, and Nostocales. The composition of the cyanobacterial community varied, depending on the nitrogen supply. Two major groups prevailed under nitrogen-limiting conditions, belonging to Leptolyngbya sp. and Komarekiella sp. The latter was characterized by DGGE profiling and sequencing, as well as by its distinctive features of morphological plasticity. The leading role of these phototrophophic and diazotrophic cyanobacteria is discussed in terms of the epiphytic lifestyle of the leafless orchids.
XAC4296 Is a Multifunctional and Exclusive Xanthomonadaceae Gene Containing a Fusion of Lytic Transglycosylase and Epimerase Domains
Authors: de Oliveira Amanda C. P. , Ferreira Rafael M. , Ferro Maria Inês T. , Ferro Jesus A. , Zamuner Caio , Ferreira Henrique , Varani Alessandro M.
Published: May 2022

Microorganisms have a limited and highly adaptable repertoire of genes capable of encoding proteins containing single or variable multidomains. The phytopathogenic bacteria Xanthomonas citri subsp. citri (X. citri) (Xanthomonadaceae family), the etiological agent of Citrus Canker (CC), presents a collection of multidomain and multifunctional enzymes (MFEs) that remains to be explored. Recent studies have shown that multidomain enzymes that act on the metabolism of the peptidoglycan and bacterial cell wall, belonging to the Lytic Transglycosylases (LTs) superfamily, play an essential role in X. citri biology. One of these LTs, named XAC4296, apart from the Transglycosylase SLT_2 and Peptidoglycan binding-like domains, contains an unexpected aldose 1-epimerase domain linked to the central metabolism; therefore, resembling a canonical MFE. In this work, we experimentally characterized XAC4296 revealing its role as an MFE and demonstrating its probable gene fusion origin and evolutionary history. The XAC4296 is expressed during plant-pathogen interaction, and the Δ4296 mutant impacts CC progression. Moreover, Δ4296 exhibited chromosome segregation and cell division errors, and sensitivity to ampicillin, suggesting not only LT activity but also that the XAC4296 may also contribute to resistance to β-lactams. However, both Δ4296 phenotypes can be restored when the mutant is supplemented with sucrose or glutamic acid as a carbon and nitrogen source, respectively; therefore, supporting the epimerase domain’s functional relationship with the central carbon and cell wall metabolism. Taken together, these results elucidate the role of XAC4296 as an MFE in X. citri, also bringing new insights into the evolution of multidomain proteins and antimicrobial resistance in the Xanthomonadaceae family.
Hospital-Onset Bloodstream Infections Caused by Eight Sentinel Bacteria: A Nationwide Study in Israel, 2018–2019
Authors: Nutman Amir , Wullfhart Liat , Temkin Elizabeth , Feldman Sarah F. , Schechner Vered , Schwaber Mitchell J. , Carmeli Yehuda
Published: May 2022

Nationwide studies on hospital-onset bloodstream infections (HO-BSIs) are scarce. To describe incidence, mortality and antimicrobial resistance (AMR) of HO-BSI caused by eight sentinel bacteria in Israel, we used laboratory-based BSI surveillance data from 1 January 2018 to 31 December 2019. All hospitals reported positive blood cultures growing Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, Acinetobacter baumannii, Streptococcus pneumoniae, Staphylococcus aureus, Enterococcus faecalis and Enterococcus faecium. We calculated HO-BSI incidence and 14-day, 30-day and 1-year mortality in adults. We performed multivariable logistic regression to identify predictors of 30-day mortality. The study included 6752 HO-BSI events: K. pneumoniae (1659, 22.1%), E. coli (1491, 19.8%), S. aureus (1315, 17.5%), P. aeruginosa (1175, 15.6%), E. faecalis (778, 10.4%), A. baumannii (654, 8.7%), E. faecium (405, 5.4%) and S. pneumoniae (43, 0.6%). Overall incidence was 2.84/1000 admissions (95% CI: 2.77–2.91) and 6.88/10,000 patient-days (95% CI: 6.72–7.05). AMR isolates accounted for 44.2% of events. Fourteen-day, thirty-day and one-year mortality were 30.6% (95% CI: 28.5%–32.8%), 40.2% (95% CI: 38.2%–42.1%) and 66.5% (95% CI: 64.7%–68.3%), respectively. Organisms with highest risk for 30-day mortality (compared with E. coli) were A. baumannii (OR 2.85; 95% CI: 2.3–3.55), E. faecium (OR 2.16; 95% CI: 1.66–2.79) and S. pneumoniae (OR 2.36; 95% CI: 1.21–4.59). Mortality was higher in AMR isolates (OR 1.57; 95% CI: 1.4–1.77). This study highlights the incidence, associated high mortality and important role of antibiotic resistance in HO-BSI.