bluuebunny/crossref_metadata_2025 huggingface dataset:
The conversıon of ethanol to acetone on a ZnO-CaO catalyst in the presence of water vapor
Authors:   Azerbaijan State Oil and Industry University, Baghirova Narqiz N. , Mustafayeva Rena E. ,   Azerbaijan State Oil and Industry University
Published: October 2023

The main product of the conversion of ethanol to acetone on a ZnO-CaO catalyst is acetone, the yield of which strongly depends on the composition of the reaction environment. When oxygen is present, the yield of products of destructive and complete oxidation increases greatly. In contrast, when water vapor is present, both the selectivity and conversion of ethanol increase. Therefore, the conversion of ethanol is the limiting step in the overall process, which determines the selectivity of the conversion of ethanol to acetone. In this regard, it appeared suitable to investigate the effect of introducing water to the contact zone. As experiments indicated, the addition of water caused a significant effect on the conversion, selectivity, and acetone yield on the ZnO-CaO catalyst. As the partial pressure of water vapor increases, the conversion of ethanol and the acetone yield increase, while the yield of carbon dioxide decreases. The decrease in carbon dioxide is associated not only with the inhibition of the conversion of ethanol to CO2. In this study, the adsorption of water vapor and ammonia on the surface of the ZnO-CaO catalyst was examined by infrared spectroscopy method. It has been shown that water vapor at low temperatures is adsorbed on the catalyst surface in the molecular form, while at higher temperatures it is adsorbed in the dissociative form. Co-transformation reactions of ethanol with acetic acid, acetaldehyde with ethylene, and acetaldehyde with acetic acid have been studied. The obtained results indicated that acetone is formed mainly through the stage of complexation of acetaldehyde with ethylene. The isomerization reaction of 1-butene to 2-butene has been investigated. It was found that the yield of cis-2-butene in the absence of water vapor is higher, likely attributed to the molecular adsorption of water on Lewis centers. Based on these findings, a scheme for the vapor-phase conversion of ethanol into acetone on the studied catalysts was formulated.
The effect of flipbook-based digital books on elementary school students’ interest in learning
Authors: Nafiah Nafiah , Syamsul Ghufron  , Sri Hartatik  , Pance Mariati  , Afib Rulyansah
Published: October 2023

In school, interest plays a crucial role in students' learning activities because when students have a high interest in learning, it contributes to their happiness. This study aimed to examine the impact of flipbooks on students' learning interests in elementary schools. The research employed a pre-experimental design known as the One-Group Pretest-Posttest Design. This research was conducted at two schools in Indonesia, that is, State Elementary School 1 Tumenggungan Lamongan and Mulyoagung I State Elementary School Tuban. The data collection technique employed was a questionnaire, and the data analysis was conducted using the Paired Samples T-Test. The findings revealed that students' interest in learning was already good before using flipbooks. However, their interest significantly improved to a very good level after incorporating the use of flipbooks. These results indicate a strong and significant relationship between using flipbooks and students' learning interests.
Keywords: Digital book; flipbook; Interest in learning; learning; students
Analysis of public perception of national obesity management policy
Authors: Moon Bo-ra , Kang Jae-heon , Lee Ju-yul , Kong Ji-young
Published: October 2023

[Purpose] This study aimed to provide essential data necessary for shaping future obesity policy directions and strengthening the effectiveness of such measures. [Methods] A literature review and expert meetings were conducted to identify policy objectives that should be included in the comprehensive national obesity management plan. Based on these objectives, a questionnaire was developed, and a survey was conducted nationwide through an online panel targeting citizens aged 15-69.[Results] When analyzing the appropriateness of promoting national obesity policies, 38.6% of respondents answered “not appropriate,” while only 8.4% answered “appropriate.” We also assessed the importance of the four key areas of the national obesity management policy, with 36.9% considering “improvement of lifestyle to prevent obesity” as the most important. Additionally, we analyzed the significance of specific tasks. “Strengthening child and adolescent obesity prevention and management,” “enhancing group meal nutrition and hygiene,” “strengthening the operation of community-based obesity and exercise clinics,” and “advancing an integrated information platform for nutrition, dietary patterns, and physical activity” emerged as pivotal tasks within their respective areas.[Conclusion] The primary tasks identified as top priorities by the public in this study regarding national obesity policy initiatives can be incorporated into future obesity management strategies. Our approach has the potential to enhance the efficacy of these policies by aligning future obesity policy trajectories with public demands and expectations.
Effects of exercise timing and intensity on physiological circadian rhythm and sleep quality: a systematic review
Authors: Kim Nahyun , Ka Soonjo , Park Jonghoon
Published: October 2023

[Purpose] Humans show near-24-h physiological and behavioral rhythms, which encompass the daily cycle of sleep and wakefulness. Exercise stimulates circadian rhythms, including those of cortisol, melatonin, and core body temperature, and affects sleep quality. We systematically reviewed studies that examined the effects of exercise intensity and timing on physiological circadian rhythms and sleep quality.[Methods] In this systematic review, we used the online databases PubMed, Science Direct, Web of Science, and Embase. This review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Two independent and experienced systematic reviewers performed the search and selected relevant studies. The participant, intervention, comparison, and outcome characteristics were: (1) adults; (2) exercise treatment; (3) no exercise treatment or different types of exercise (pre-exercise baseline); (4) cortisol, melatonin, or core body temperature measurement, and subjective or objective sleep quality assessments.[Results] We identified 9 relevant articles involving 201 participants (77.1% of whom were male). Our review revealed that short-term evening exercise delayed melatonin rhythm and increased nocturnal core body temperature; however, no negative effects on non-rapid eye movement sleep and sleep efficiency were observed. Moreover, no differences in sleep quality were observed between acute high-intensity and moderate-intensity exercises. With long exercise durations, the core body temperature tended to increase and return to baseline levels at 30–120 min.[Conclusion] Our review showed that short-term evening exercise and high-intensity exercise did not have a significant negative effect on sleep quality but physiological circadian rhythm tended to alter. Longterm morning exercise tended to decrease cortisol concentrations after awakening and improve sleep quality. Future studies should examine the effects of long-term exercise timing and intensity on circadian rhythm and sleep.
Mechanisation of pre-flowering leaf removal under temperate climate conditions
Authors: Verdenal Thibaut , Zufferey Vivian , Dienes-Nagy Ágnes , Bourdin Gilles , Spring Jean-Laurent
Published: October 2023

Grapevine leaf removal (LR) in the cluster area is a common practice in temperate and cool climates, usually done between berry-set and cluster closure to create a less favourable microclimate for fungal diseases and to improve grape ripening. When applied before flowering, LR affects berry-set and is, therefore, an effective yield-control tool, reducing time-consuming manual cluster thinning; it also improves berry structure and composition (i.e., total soluble sugars [TSS], titratable acidity [TA] and polyphenols) (VanderWeide et al., 2021). The present five-year trial follows a previous study about pre-flowering LR under identical environmental conditions (Verdenal et al., 2019); it validates the sustainability of moderate pre-flowering LR and its possible mechanisation under Swiss climatic conditions, using low-pressure double airflow.
Research on a Grading Evaluation System for Water Inflow in Three-Bore Parallel Subsea Tunnels Considering Inter-Tunnel Influence
Authors: Han Zhiming , Yan Keyu , Zhu Zhengguo , Cui Huimin
Published: October 2023

The analysis of water inflow is a key issue in the construction of subsea tunnels. However, present research on the water inflow of subsea tunnels is predominantly focused on single-bore tunnels. Given the current practices in engineering, it is common to see a parallel configuration of three bores. In such cases, the proximity of tunnels to one another might result in alterations to the water inflow due to the interplay of seepage fields. This paper begins by conducting a numerical simulation to assess the water inflow characteristics of a three-bore parallel subsea tunnel. The study then investigates the impact of many factors, including the permeability coefficient of the surrounding rock, the depth of the seawater, the depth of the tunnel, the spacing between tunnels, and the relative size of the tunnels, on the water inflow phenomenon. Furthermore, based on the principles of the analytic hierarchy process and fuzzy mathematics, a comprehensive assessment framework is developed to evaluate the water inflow of three-bore parallel subsea tunnels. Ultimately, this grade of water inflow is used in practical engineering. The results show that there is mutual influence between the three parallel tunnels, and the predicted water inflow will be too large if the single tunnel model is adopted. The interaction between tunnels should be considered in the water inflow grade evaluation system of the three-hole parallel submarine tunnel. Engineering cases show that using a single-hole tunnel model without considering the interaction between tunnels will lead to higher water inflow grades. The research results of this paper can provide guidance for the waterproofing and drainage design of three parallel subsea tunnels and the stability analysis of surrounding rocks.
A Procedure for Assessing the Effect of Climate Change on Organizational Cash Flows in Developing Countries
Authors: Sánchez González Carlos Andres , Lochmuller Christian , Builes-Vélez Ana , Osorio Ana M.
Published: October 2023

Climate change and net zero are expected to have a significant impact on eco-nomic activity in developing countries, and thus, on the financial cash flow of organizations. In this paper, we propose a procedure for assessing the financial impact of climate change on organizational cash flow in developing countries. Our study contributes to the research on scenario-based climate change impact analysis. The applied research design is exploratory and mainly qualitative, constructing financial impact scenarios combined with narratives to determine the impact of climate change on individual cash flow line items. The narra-tives rationalize cash flow variations and enrich the estimates by adding expert knowledge, in the form of financial micro-stories and descriptions to the pro-posed procedure. We present a hypothetical citrus farming company in a de-veloping country to demonstrate the application of the proposed measurement procedure. The results obtained suggest that (1) the procedure is practical be-cause financial cash flows are known and widely used in financial analysis and because they can be implemented in a spreadsheet; that (2) the procedure pro-vides flexibility because it can be adapted to suit the specific needs of different companies, depending on a selected climate change scenario, the company’s exposure to climate change, its resilience and vulnerability; (3) that the prac-tice of thinking in terms of financial worst-case, base-case and best-case sce-narios, which reflect different levels of uncertainty, helps to model the finan-cial impacts of climate change and provides a forward-looking perspective on how much a company’s cash flow could change.
Recent Advances on Electrochemical Sensors for Detection of Contaminants of Emerging Concern (CECs)
Authors: Gibi Chinchu , Liu Cheng-Hua , Anandan Sambandam , Wu And Jerry J.
Published: October 2023

Contaminants of Emerging Concern (CECs), a new category of contaminants in limelight, is a major issue of global concern. The pervasive nature of CECs and its harmful effects, such as cancer, reproductive disorders, neurotoxicity etc., make the situation alarming. The perilous nature of CECs lies in the fact that even very small concentration of CECs can cause great impacts on living beings. It also has a nature of bioaccumulation. Thus, it is the ultimate need to have efficient sensors for detection of CECs to ensure safe living environment. Electrochemical sensors are an efficient platform for CEC detection as they are highly selective, sensitive, stable, reproducible, and prompt, and can detect very low concentrations of analyte. Major classes of CECs are pharmaceuticals, illicit drugs, personal care products, endocrine disruptors, newly registered pesticides, and disinfection by-products. This review focusses on CECs, including their sources and pathways, health effects caused by them, and electrochemical sensors as reported in literatures under each category for the detection of major CECs.
Biological Properties and Biomedical Applications of Pectin and Pectin-Based Composites: A Review
Authors: Sultana Naznin
Published: October 2023

Due to its distinctive chemical and biological properties, pectin has recently drawn much attention in biomedical and tissue engineering applications. Polymers like pectin with cell-instructive properties are attractive natural biomaterials for tissue repair and regeneration. Besides, bioactive pectin and pectin-based composites exhibit improved characteristics to deliver active molecules. Pectin and pectin-based composites serve as interactive matrices or scaffolds by stimulating cell adhesion and cell proliferation and enhancing tissue remodeling by forming an extracellular matrix in vivo. Several bioactive properties, such as immunoregulatory, antibacterial, anti-inflammatory, anti-tumor, and antioxidant activities, contribute to the pectin's and pectin-based composite's enhanced applications in tissue engineering and drug delivery systems.This paper reviews the promising characteristics of pectin or pectic polysaccharides and highlights its potential applications in drug delivery and tissue engineering. Tissue engineering scaffolds containing pectin and pectin-based conjugates or composites demonstrate essential features such as non-toxicity, tunable mechanical properties, biodegradability, and suitable surface properties. The design and fabrication of pectic composites are versatile for tissue engineering and drug delivery applications.
Recent Progresses in Signal Processing for Alzheimer's Disease Detection
Authors: Zhao Mengyao
Published: October 2023

Alzheimer's Disease (AD) is a neurodegenerative disease that is common in the elderly. This paper introduces the overview of Alzheimer's disease and the application of relevant signal processing methods in its detection. Signal processing is a technique that converts raw data into meaningful information and is widely used in the medical field. This paper lists common signal processing techniques, including Fourier transform, time-frequency analysis and statistical signal processing, and discusses their applications in the detection of Alzheimer's disease. Fourier transform can convert time domain signals into frequency domain representations, providing an effective tool for the study of EEG in Alzheimer's disease. Time-frequency analysis can perform a combined time and frequency analysis of the signal to help detect the signal characteristics of Alzheimer's disease. Statistical signal processing methods can be used to identify the features of Alzheimer's disease by building mathematical models. Finally, the challenges of Alzheimer's disease detection are discussed, including signal noise, diversity, and insufficient data volume. Through in-depth research and development of signal processing methods, it is expected to improve the accuracy and efficiency of early detection of Alzheimer's disease.
Navigating the Complexities of Traumatic Encephalopathy Syndrome (TES): Current State and Future Challenges
Authors: Fesharaki-Zadeh Arman F
Published: October 2023

Chronic traumatic encephalopathy (CTE) is a unique neurodegenerative disease that is associated with repetitive head impacts (RHI) in both civilian and military settings. In 2014, the research criteria for the clinical manifestation of CTE, traumatic encephalopathy syndrome (TES) were proposed to improve the clinical identification and understanding of the complex neuropathological phenomena underlying CTE. This review provides a comprehensive overview of the current understanding of the neuropathological and clinical features of CTE, proposed biomarkers of traumatic brain injury (TBI) in both research and clinical settings, and a range of treatments based on previous preclinical and clinical research studies. Due to the heterogeneity of TBI, there is no universally agreed-upon serum, CSF, or neuroimaging marker for its diagnosis. However, as our understanding of this complex disease continues to evolve, it is likely that there will be more robust, early diagnostic methods and effective clinical treatments. This is especially important given the increasing evidence of a correlation between TBI and neurodegenerative conditions, such as Alzheimer's disease and CTE1. As public awareness of these conditions grows, it is imperative to prioritize both basic and clinical research, as well as the implementation of necessary safe and preventative measures.
Low Platinum Content Exchange-Coupled CoPt Nanoalloys with Enhanced Magnetic Properties
Authors: Basina Georgia , Alexandrakis Vasileios , Panagiotopoulos Ioannis , Niarchos Dimitrios , Devlin Eamonn , Gjoka Margarit , Hadjipanayis George C. , Tzitzios Vasileios
Published: October 2023

Bimetallic colloidal CoPt nanoalloys, with a very low platinum content, were successfully synthesized following a modified polyol approach. Powder X-ray diffraction, IR spectroscopy, thermogravimetric analysis, and Transmission Electron Microscopy studies were performed to estimate the crystal structure, morphology and surface functionalization of the colloids respectively, while the room temperature magnetic properties were measured using Vibrating Sample Magnetometer. The particles exhibit excellent uniformity, with a narrow size distribution, and display strong room temperature hysteretic ferromagnetic behavior even in the as-made form. Upon annealing at elevated temperatures, progressive formation and co-existence of exchange coupled both chemically ordered and disordered phases, significantly enhance the room temperature coercivity.
Efficient Formulation for Vendor–Buyer System Considering Optimal Allocation Fraction of Green Production
Authors: Alamri Adel A.
Published: October 2023

The classical joint economic lot-sizing (JELS) policy in a single-vendor single-buyer system generates an equal production quantity in all cycles, where the input parameters remain static indefinitely. In this paper, a new two-echelon supply chain inventory model is developed involving a hybrid production system that simultaneously focuses on green and regular production methods with optimal allocation fraction of green and regular productions. Unlike the classical mathematical formulation, each cycle is independent from the previous one, and consequently, the input parameters can be adjusted to be responsive to the dynamic nature of demand rate and price fluctuation. A rigorous heuristic approach is used to derive a global optimal solution for a joint hybrid production system. The model accounts for carbon emissions from production and storage activities related to green and regular produced items along with transportation activity under a multi-level emission-taxing scheme. The results emphasize the significant impact of green production on emissions. That is, the higher the allocation fraction of green production the lower the total amount of emissions generated by the system, i.e., the system becoming more sustainable. Adopting a hybrid production method not only decreases the greenhouse gas (GHG) emissions dramatically, but also reduces the per unit time total cost when compared with regular production. One of the main findings is that the total system cost generated by the base closed-form formula of the proposed model is considerably lower than that of the existing literature i.e., 33.59% (16.13%) lower in the first cycle (subsequent cycles) when the regular production method is assumed. Moreover, the optimal production rate generated by the proposed model is the one that minimizes the emissions production function. Illustrative examples and special cases that reflect different realistic situations are compared to outline managerial insights.
Stochastic Claims Reserve in the Healthcare System: A New Methodology Applied in Italy
Authors: Mazzi Claudio , Damone Angelo , Vandelli Andrea , Ciuti Gastone , Vainieri Milena
Published: October 2023

One of the challenges in the healthcare sector is making accurate forecasts across insurance years for claims reserve. The state-of-the-art envisages various methods for estimating the claims reserve but without being applied to systems that do not present huge variability and heterogeneity, such as the healthcare sector. The methodology is based on generalized linear models using the Overdispersed Poisson distribution as shown in the state-of-the-art. In this context, we developed a method to estimate the parameters of the quasi-likelihood function using a Gauss-Newton algorithm optimized through a genetic algorithm. The genetic algorithm plays a crucial role in glimpsing the position of the global minimum to ensure a correct convergence of the Gauss-Newton method, where the choice of the initial guess is fundamental. The proposed methodology has been entirely developed using MATLAB and has been applied to estimate the claims reserve in the healthcare system of the Tuscany Region in Italy, as case study. The results obtained were validated by comparing them with the state-of-the-art by measuring the confidence intervals of the Overdispersed Poisson distribution parameters. Therefore local healthcare authorities could use the proposed and improved methodology to allocate the resources dedicated to healthcare and global management.
An Experimental Study Investigating The Effects of Data Pre-processing Methods on Deep Learning Based Time Series Data Prediction
Authors: Aktas Mehmet , Yilmaz Mustafa Bugra , Karabacak Abdulkadir
Published: October 2023

Time-series analysis is a widely used technique across various fields and industries, as it helps in understanding, predicting, and forecasting the behavior of data points over time. These fields include but are not limited to finance, economics, healthcare, transportation, etc. In the case of this paper, we have focused on finance. Predicting future values of financial time series offers several benefits. Accurate forecasts can help investors make better decisions about their investments. To predict future values, deep learning algorithms are commonly used since it is an effective method with complex data. In this study, we conduct a study that investigates the use of different data pre-processing techniques on deep learning algorithms in predicting the time series values. To conduct this experimental study, we utilize an open source software, which using long short-term memory technique as the representative deep learning technique, published in github software code repository platform. With this study, we investigate the effects of autoencoder and discrete wavelet transform data pre-processing techniques in time-series prediction. We discuss the details of the experimental study and report our results. The results show that time series prediction (using backtesting methodology) without any data pre-processing leads to 12.6% for mean absolute percentage error. The results also show that, time series prediction with the data preprocessing techniques (Wavelet Transform and Stacked Autoencoder) lead to 3.4%
The Significance of the Factors Increasing the Asphalt Pavement Recycling Rate in the Country, Determined by MCDM Methods
Authors: Sivilevičius Henrikas , Martišius Mindaugas
Published: October 2023

Transport infrastructure’s asphalt pavement deteriorates under the influence of destructive factors. Damages which have been occurred during its exploitation period are repaired, and when their further rehabilitation is economically and technically irrational, the asphalt pavement is recycled. The material from the asphalt pavement layer that has reached its limit state is milled out or broken and crushed and then is repeatedly used in the production of hot-mix asphalt (HMA) or warm-mix asphalt (WMA) mixtures. In this paper, the dynamics of the percentage recycling ratio (RR) of old asphalt pavement material was investigated. RR represents the quantity of reclaimed asphalt pavement (RAP) used in the production of HMA and WMA mixtures in Europe and the USA, divided by the total amount of RAP prepared in the country. Factors and goals affecting it are analyzed. An original system of 10 criteria that increase the RR country has been created. By applying different multiple criteria decision making (MCDM) methods and using the importance given to these criteria by 14 experts, the normalized subjective weights of the criteria were determined. Analytic Hierarchy Process (AHP), rank correlation, Average Rank Transformation into Weight - Linear (ARTIW-L) and Non-linear (ARTIW-N), Direct Percentage Weight (DPW) methods were used in the study. The results display that the RAP recycle rate is close to 100% in countries with a sustainable economic background. In the Baltic countries, it is mostly increased by the adequacy of regulatory documents, the strategy promoting asphalt recycling in the country, and the homogeneity and classifying of RAP. The number and capacity of RAP stocks, the number and productivity of asphalt milling equipment and the wear and tear of the asphalt pavement have the least influence on the increase of RR. The opinions of experts in assessing the significance of all criteria are consistent. The averages of the weights of criteria determined by four MCDM methods (AHP, ARTIW-L, ARTIW-N, DPW) made it possible to obtain more reliable results. These results can be used to make strategic decisions and to create a plan of practical actions to increase the RAP recycling rate in the developing countries.
Hyperbaric Oxygen in Post STroke Patients (HOST): A Feasibility Study
Authors: Schmutz Jörg , Gelsomino Marco , Schmucki Patrick , Peters Nils , Engelter Stefan T
Published: October 2023

Keywords: Post-Stroke; Hyperbaric oxygen therapy; Sequelae; Feasibility; Out-patient.
STAGES OF REHABILITATION FOR WOMEN AFTER EARLY REPRODUCTIVE LOSS
Authors:   City Clinical Hospital No. 8, Ryazan, ALESHKINA OKSANA S. , KONOVALOV OLEG E. ,   Peoples’ Friendship University of Russia named after Patrice Lumumba, SHULAYEV ALEXEY V. ,   Kazan State Medical University, PRISTUPA EVGENIA M. ,   Ryazan State Medical University, BREUSOV ALEXEY V. ,   Peoples’ Friendship University of Russia named after Patrice Lumumba
Published: October 2023

Introduction. For all early reproductive losses, the need for restorative treatment is common. Aim. The purpose of the study is to analyze the experience of the gynecological hospital in Ryazan on a 3-stage comprehensive rehabilitation of women with early reproductive losses. Material and Methods. The development of this algorithm was carried out on the basis of an analysis of the results of research and the experience of leading research centers. A sociological survey was carried out among 128 obstetrician-gynecologists working in the gynecological department of the hospital and antenatal clinics in Ryazan. Results and discussion. The results of a sociological survey among obstetricians-gynecologists confirmed the importance of rehabilitation measures after early reproductive loss, as well as assessing the health status of women, including in terms of psycho-emotional status. At the same time, 44.8 % of respondents believed that the rehabilitation of women after early pregnancy loss should be carried out in a day hospital, 23.9% in a round-the-clock hospital, 21.6% - on an outpatient basis, 9.7% of the surveyed doctors found it difficult to answer. A description is given of the content of each of the three stages (stationary, restorative and supportive) of the developed and tested scheme of complex rehabilitation. Based on the results of the third stage, the doctor gives a comprehensive assessment of the woman’s reproductive health after the loss of pregnancy, together with the patient determines her further reproductive plan: either prescribe reliable contraception or prenatal preparation. Conclusion. Implementation The three-stage rehabilitation scheme makes it possible to provide full-scale specialized medical care for the restoration of reproductive health and psycho-emotional sphere to women with early reproductive loss, as well as to form their further reproductive plans.
PRESCHOOL CHILDREN DENTOALVEOLAR DEFORMITIES DEPENDING ON FAMILY TYPES AND MORPHOFUNCTIONAL CHILD DEVELOPMENT
Authors:   Network of dental clinics ", KHADYEVA MADINA N. ,   UniDen",   , Kazan, GALIULLIN AFGAT N. ,   Kazan State Medical University, YAKIMOVA JULIA YU. ,   Kazan Federal University
Published: October 2023

Introduction. Dentоfacial deformities in preschool children do not show any downtrend. Studying how various factors affect their occurrence and development is of undoubted interest. Our aim was to study the impact of family types on the prevalence and nosology of dental system diseases. Materials and Methods. 2,556 children were examined, aged one to six years, of both genders, and from families of different types. To statistically process the study findings, descriptive statistics methods were used. Integrity was assessed in the compared groups by averaging and computing error in mean, using Student’s t-test. Results and Discussion. Prevalence of dental abnormalities among preschool children was higher among boys of all ages (63.6±1.353%), as compared to girls (57.5± 1.376%). It was found that children from substitute families were most susceptible to dental abnormalities. Prevalence of dentoalveolar deformities was in 100% of cases in all age groups in children from adoptive families. High prevalence of dentoalveolar anomalies was also recorded in preschool children living in incomplete families, i.e., in 82±2.78% of cases. The lowest prevalence of dentoalveolar deformities was found in children living in full families, i.e., in 56.1±1.129% of cases, and in extended families, i.e., in 59.2±3.367% of cases. In children living in reconstituted families, dentoalveolar abnormalities are found less frequently (78.9±3.167%) than in children living in substitute and one-parent families, but more frequently than in children living in nuclear and extended families. When analyzing the structure of dentoalveolar anomalies, it was found that most often there were bite pathologies (prognatic and deep bites), as well as abnormalities of dental arches. The least common pathology of the jawbone system in the examined children turned out to be the cross-bite pathology. Older age group children (aged 4.6-6 years) are most susceptible to dentoalveolar abnormalities as compared to other ages of preschool children. Conclusions. Data presented in this article are of practical importance for implementing and developing preventive measures, considering the type of family and the morphofunctional development of the child.
Computational design of highly signaling active membrane receptors through de novo solvent-mediated allosteric networks
Authors: Chen Kuang-Yui , Lai Jason , Wang Jing , Russell Anna Maria , Conners Kris , Rutter Marc Edward , Condon Bradley , Tung Frances , Kodandapani Lalitha , Chau Betty , Zhao Xun , Benach Jordi , Baker Kent , Hembre Erik , Barth Patrick
Published: October 2023

Protein catalysis and allostery require the atomic-level orchestration and motion of residues, ligand, solvent and protein effector molecules, but the ability to design protein activity through precise protein-solvent cooperative interactions has not been demonstrated. Here, we report the design of a dozen novel membrane receptors catalyzing G-protein nucleotide exchange through diverse de novo engineered allosteric pathways mediated by cooperative networks of intra-protein, protein-ligand and solvent molecule interactions. Consistent with the predictions, designed protein activities correlated well with the level of plasticity of the network at flexible transmembrane helical interfaces. Several designs displayed considerably enhanced thermostability and activity compared to related natural receptors. The most stable and active variant crystallized in an unforeseen signaling active conformation, in excellent agreement with the design models. The allosteric network topologies of the best designs bear limited similarity to those of natural receptors and reveal a space of allosteric interactions larger than previously inferred from natural proteins. The approach should prove useful for engineering proteins with novel complex protein binding, catalytic and signaling activities.
Problem of integrating Blockchain Technologies into Wireless Mesh Networks: Application to Community Wireless Networks
Authors: NDIÉ Thomas DJOTIO , DOBE Abel
Published: October 2023

Wireless mesh networks (WMNs), because of their low installation costs compared to the network infrastructure, were seen as a relevant alternative to connect remote areas and poor regions where telephone companies have great apprehension to invest. However, WMNs have security vulnerabilities, including denial of service (DoS) and identity theft attacks. The most common methods for securing mesh networks are centralized systems, while WMNs are decentralized, open and flexible by design. The usual blockchain integration in WMNs is more oriented towards the construction of online payment platforms. This paper proposes BlockWMN, a model for integrating blockchain technology into WMNs with the ultimate goal of protecting them from the abovementioned attacks. Fundamentally, we address a consensus issue or a so-called "Byzantine Generals" or "Byzantine Fault Tolerance" (BFT) problem. Our approach uses the blockchain as a secure database to save the network graph and all the network nodes’ credentials in real time. Each node has the ability to check in the blockchain all signaling information received from other nodes. Unlike other approaches, our solution is decentralized, open and flexible. The limits of our model are inherent to the nature of blockchains: high energy consumption for the calculation of the proof of work and memory space for the storage of blockchain information.
Quantum-noise-limited optical neural networks operating at a few quanta per activation
Authors: Ma Shi-Yuan , Wang Tianyu , Laydevant Jérémie , Wright Logan , McMahon Peter
Published: October 2023

A practical limit to energy efficiency in computation is ultimately from noise, with quantum noise [1] as the fundamental floor. Analog physical neural networks [2], which hold promise for improved energy efficiency and speed compared to digital electronic neural networks, are nevertheless typically operated in a relatively high-power regime so that the signal-to-noise ratio (SNR) is large (>10). We study optical neural networks [3] operated in the limit where all layers except the last use only a single photon to cause a neuron activation. In this regime, activations are dominated by quantum noise from the fundamentally probabilistic nature of single-photon detection. We show that it is possible to perform accurate machine-learning inference in spite of the extremely high noise (signal-to-noise ratio ~1). We experimentally demonstrated MNIST handwritten-digit classification with a test accuracy of 98% using an optical neural network with a hidden layer operating in the single-photon regime; the optical energy used to perform the classification corresponds to 0.008 photons per multiply-accumulate (MAC) operation, which is equivalent to 0.003 attojoules of optical energy per MAC. Our experiment also used >40× fewer photons per inference than previous state-of-the-art low-optical-energy demonstrations [4, 5] to achieve the same accuracy of >90%. Our training approach, which directly models the system’s stochastic behavior, might also prove useful with non-optical ultra-low-power hardware.
Exploiting Hidden Information Leakages in Backward Privacyfor Dynamic Searchable Symmetric Encryption
Authors: Yoon Hyundo , Yu Muncheon , Hahn Changhee , Koo Dongyoung , Hur Junbeom
Published: October 2023

Dynamic searchable symmetric encryption (DSSE) enables searches over encrypted data as well as data dynamics such as flexible data addition and deletion operations.A major security concern in DSSE is how to preserve forward and backward privacy, which are typically achieved by removing the linkability between the newly added data and previous queries, and between the deleted data and future queries, respectively. After information leakage types were formally defined for different levels of backward privacy (i.e., Type-I, II, III), many backward-private DSSE schemes have been constructed under the definitions. However, we observed that the backward privacy can be violated by leveraging additional secondary leakage which is typically leaked in specific constructions of schemes in spite of their theoretical guarantees.In this paper, in order to understand the security gap between the theoretical definitions and practical constructions, we conduct an in-depth analysis of the root cause for the secondary leakage, and demonstrate how it can be abused to violate Type-II backward privacy (e.g., the exposure of the deletion history) of DSSE constructions in practice.
We then propose a novel Type-II backward private DSSE scheme based on Intel SGX which is resilient to the secondary leakage abuse attack. According to the comparative analysis of our scheme with the state-of-the-art SGX-based DSSE schemes, Bunker-B (EuroSec'19) and SGX-SE1 (ACNS'20),our scheme shows higher efficiency in terms of the search latency with a negligible utility loss under the same security level (cf. Bunker-B); while showing similar efficiency with a higher security level (cf. SGX-SE1). Finally, we formally prove that our scheme guarantees Type-II backward privacy.
Adult skull bone marrow is an expanding and resilient hematopoietic reservoir
Authors: Adams Ralf , Koh Bong-Ihn , Mohanakrishnan Vishal , Jeong Hyun-Woo , Park Hongryeol , Choi Young Jun , Nieminen-Kelhä Melina , Pereira Raquel , Adams Susanne , Lee Hyuek Jong , Bixel M. Gabriele , Vajkoczy Peter , Krause Daniela
Published: October 2023

The bone marrow microenvironment is a critical regulator of hematopoietic stem cell self-renewal and fate. While it is appreciated that aging, chronic inflammation and other insults compromise bone marrow function and thereby negatively affect hematopoiesis, it is not known whether different bone compartments exhibit distinct microenvironmental properties and functional resilience. Here, we have employed imaging, pharmacological approaches, and mouse genetics to uncover specialized and highly surprising properties of bone marrow in adult and aging skull. Specifically, we show that the skull bone marrow undergoes lifelong expansion involving vascular growth, which results in an increasing contribution to total hematopoietic output. Furthermore, skull is largely protected against major hallmarks of aging, including upregulation of inflammatory cytokines, adipogenesis and loss of vascular integrity. Striking dynamic and rapid changes to the skull vasculature and bone marrow are induced by physiological alterations, namely pregnancy, but also pathological challenges, such as stroke and experimental chronic myeloid leukemia. These responses are highly distinct from femur, the most extensively studied bone marrow compartment. We propose that skull harbors a protected and dynamically expanding bone marrow microenvironment, which is relevant for experimental studies but, potentially, also clinical treatments in humans.
Diversity and spatial genetic structure of the common opossum (Didelphis marsupialis) in an urban matrix of Northwestern Colombia
Authors: Henao-Sáenz Carolina , Herrera-Pérez Juliana , Soto-Calderón Iván Darío
Published: October 2023

The common opossum is a marsupial widely distributed in the Neotropics, where it lives in urbanized environments. The apparent scarcity and fragmentation of available habitat, and high rates of vehicle collisions, may represent barriers to dispersal. To assess the functional connectivity of this species and its potential use as a model in urban ecology, we evaluated the structure and genetic diversity of opossums in the metropolitan area of the Aburrá Valley (AMVA), Colombia, using sequences of the mitochondrial Cytochrome B (Cytb) gene and nine autosomal microsatellite loci. Although Cytb presented low levels of variation, microsatellite markers revealed high genetic diversity (He = 0.852 and Ho = 0.698). The geographic distribution of mitochondrial lineages and a spatial principal component analysis (sPCA) of microsatellites showed the absence of genetic structure and effective barriers to dispersal of opossums in the study area. This scenario suggests that hostile landscapes such as those in urban environments may be suitable enough to allow the effective connectivity of some species such as D. marsupialis and others with high dispersal ability in urbanized areas. Nonetheless, it is necessary to evaluate the impact of releases of rescued fauna made by the environmental authority on the population structure of urban opossums.
Perception of Faculty in the Community Health Sciences Colleges towards Simulation-based Education in Clinical Nutrition Undergraduate Practical Courses: A National-level, Observational Study in Saudi Arabia
Authors: Dayel Iman Bin , Alahmad Shahad
Published: October 2023

Background
Simulation in medical healthcare practice and education has been applied since the early twentieth century. Simulation now is widely used for training and education in different fields including healthcare education. Medicine and healthcare students can be trained in a secure, efficient, and engaging setting by Simulation-based Education (SBE). Therefore, this study aimed to assess the perception of faculty members in the community health departments towards SBE to be used in practical subjects for clinical nutrition undergraduate courses.
Method
This national-level observational study was conducted among community health sciences faculty members. The perception was assessed using a questionnaire that included three sections; the first section included socio-demographic questions, the second section included questions to assess teachers’ perceptions of SBE, and the last section was an open-ended question to explore perceived barriers towards SBE.
Results
This questionnaire was completed by 125 faculty members, of whom 36 (28.8%) were male, and 89 (71.2%) were female. Overall, faculty members had positive perception, with a mean score of 3.86 ± 0.74, but high level of anxiety toward SBE, with a mean score of 3.42 ± 0.75. There was a statistically significant difference between the responses of the faculty members based on their received training in simulation (P = 0.001).
Conclusion
The study results indicate that community health sciences faculty members’ perception of SBE in Saudi Arabia is generally positive. However, the results show high levels of anxiety among faculty members toward SBE.
Structural insights into ligand recognition and activation of melanin-concentrating hormone receptor MCHR1
Authors: Gong Weimin , Liu Haiping , Ye Xiaofan , Liu Guibing , Li Xiu
Published: October 2023

Melanin-concentrating hormone (MCH) is a 19-amino acid cyclic neuropeptide playing a crucial role in energy homeostasis, sleep, and other physiological functions. In rodents and humans, MCH promotes feeding through the G protein-coupled receptor MCHR1, making it a promising therapeutical target for metabolic disorders. However, mechanisms for ligand recognition and activation of MCHR1 remains obscure due to the lack of structural information. In this study, we report the cryo-EM structures of MCHR1-Gi1 complex in the MCH-bound state and the ligand-free state. We revealed the specific recognition mechanism of MCH by MCHR1 as well as multiple conformational states of the signaling complex. Distinct distribution of different states in the presence and absence of MCH highlights the relevance of conformational tuning of the complex in MCHR1 activation. Our study provides structural insights into ligand recognition and activation mechanisms of MCHR1 and will facilitate the development of drugs targeting the MCH system.
Application of Optimized Kalman Filtering in Target Tracking Based on Improved Gray Wolf Algorithm
Authors: Pang Zheming , Wang Yajun , Yang Fang
Published: October 2023

High precision is a very important index in target tracking. In order to improve the prediction accuracy of target tracking, an optimized Kalman filter approach based on improved Gray Wolf algorithm (IGWO-OKF) is proposed in this paper. Since the convergence speed of traditional Gray Wolf algorithm is slow, meanwhile, the number of gray wolves and the choice of the maximum number of iterations has a great influence on the algorithm, a nonlinear control parameter combination adjustment strategy is proposed. An improved Grey Wolf Optimization algorithm (IGWO) is formed by determining the best combination of adjustment parameters through the fastest iteration speed of the algorithm. The improved Grey Wolf Optimization algorithm (IGWO) is formed, and the process noise covariance matrix and observation noise covariance matrix in Kalman filter are optimized by IGWO. The proposed approach is applied into. The experiment results show that the proposed IGWO-OKF approach has low error, high accuracy and good prediction effect.