bluuebunny/crossref_metadata_2025 huggingface dataset:
Assessing the Zooplankton Metacommunity (Branchiopoda and Copepoda) from Mediterranean Wetlands in Agricultural Landscapes
Authors: Gilbert Juan Diego , Márquez Francisco J. , Guerrero Francisco
Published: March 2023

Mediterranean wetlands are suitable ecosystems for studying metacommunity theory, since they are isolated ecosystems within a land matrix with well-established limits, often with watersheds destined for agricultural uses. The zooplankton community of wetlands in agricultural landscapes is the result of processes that operate in a different multiscale context. We selected 24 ponds in Alto Guadalquivir region (SE Spain) with different local environmental variables (biological, limnological and land uses). The zooplankton community of the wetlands under study consists of a total of 60 species: 38 branchiopods and 22 copepods. This community (total, branchiopods and copepods) was analysed through two different and complementary metacommunity approaches. The pattern approach determines the species distribution along environmental gradients, and the mechanistic approach considers the involved processes, such as environmental control and dispersal limitation. The results indicated a nested metacommunity, in which five limnological variables, three land uses and six spatial variables are the main drivers that explain zooplankton distribution in these wetlands. In conclusion, species sorting and dispersal processes play a role in the structuring of the zooplankton metacommunity. This conclusion has implications for the development of adequate management policies on Mediterranean wetland protection and diversity conservation in agricultural contexts.
Irregularities in Meiotic Prophase I as Prerequisites for Reproductive Isolation in Experimental Hybrids Carrying Robertsonian Translocations
Authors: Kolomiets Oxana , Bakloushinskaya Irina , Pankin Mark , Tambovtseva Valentina , Matveevsky Sergey
Published: March 2023

The basic causes of postzygotic isolation can be elucidated if gametogenesis is studied, which is a drastically different process in males and females. As a step toward clarifying this problem, we obtained an experimental inbred lineage of the eastern mole vole Ellobius tancrei, whose founder animals were animals with identical diploid numbers 2n = 50 but with different Robertsonian translocations (Rb), namely 2Rb4.12 and 2Rb9.13 in the female and 2Rb.2.18 and 2Rb5.9 in the male. Here, we analyzed strictly inbred hybrids (F1, fertile and F10, sterile) using immunocytochemical methods in order to study spermatocytes during the meiotic prophase I. Previously, the presence of trivalents was assumed to have no significant effect on spermatogenesis and fertility in hybrids, but we demonstrated that spermatogenesis might be disturbed due to the cumulative effects of the retarded synapses of Rb bivalents as well as trivalents and their associations with XX sex bivalents. Alterations in the number of gametes due to the described processes led to a decrease in reproductive capacity up to sterility and can be examined as a mechanism for reproductive isolation, thus starting speciation.
Correlation between Sonographic Features and Central Neck Lymph Node Metastasis in Solitary Solid Papillary Thyroid Microcarcinoma with a Taller-Than-Wide Shape
Authors: Chen Shun-Ping , Jiang Xin , Zheng Wu-Wu , Luo Yin-Li
Published: March 2023

Purpose: This study aimed to investigate the correlation between sonographic features and central neck lymph node metastasis (CNLM) in solitary solid papillary thyroid microcarcinoma (PTMC) with a taller-than-wide shape. Methods: A total of 103 patients with solitary solid PTMC with a taller-than-wide shape on ultrasonography who underwent surgical histopathological examination were retrospectively selected. Based on the presence or absence of CNLM, patients with PTMC were divided into a CNLM (n = 45) or nonmetastatic (n = 58) group, respectively. Clinical findings and ultrasonographic features, including a suspicious thyroid capsule involvement sign (STCS, which is defined as PTMC abutment or a disrupted thyroid capsule), were compared between the two groups. Additionally, postoperative ultrasonography was performed to assess patients during the follow-up period. Results: Significant differences were observed in sex and the presence of STCS between the two groups (p < 0.05). The specificity and accuracy of the male sex for predicting CNLM were 86.21% (50/58 patients) and 64.08% (66/103 patients), respectively. The sensitivity, specificity, positive predictive value (PPV), and accuracy of STCS for predicting CNLM were 82.22% (37/45 patients), 70.69% (41/58 patients), 68.52% (37/54 patients), and 75.73% (78/103 patients), respectively. The specificity, PPV, and accuracy of the combination of sex and STCS for predicting CNLM were 96.55% (56/58 patients), 87.50% (14/16 patients), and 67.96% (70/103 patients), respectively. A total of 89 (86.4%) patients were followed up for a median of 4.6 years, with no patient having recurrence as detected on ultrasonography and pathological examination. Conclusions: STCS is a useful ultrasonographic feature for predicting CNLM in patients with solitary solid PTMC with a taller-than-wide shape, especially in male patients. Solitary solid PTMC with a taller-than-wide shape may have a good prognosis.
Blood Count-Derived Inflammatory Markers Correlate with Lengthier Hospital Stay and Are Predictors of Pneumothorax Risk in Thoracic Trauma Patients
Authors: Vunvulea Vlad , Melinte Răzvan Marian , Brinzaniuc Klara , Suciu Bogdan Andrei , Ivănescu Adrian Dumitru , Hălmaciu Ioana , Incze-Bartha Zsuzsanna , Pastorello Ylenia , Trâmbițaș Cristian , Mărginean Lucian , Kaller Réka , Kassas Ahmad , Hogea Timur
Published: March 2023

(1) Background: Trauma is one of the leading causes of death worldwide, with the chest being the third most frequent body part injured after abdominal and head trauma. Identifying and predicting injuries related to the trauma mechanism is the initial step in managing significant thoracic trauma. The purpose of this study is to assess the predictive capabilities of blood count-derived inflammatory markers at admission. (2) Materials and Methods: The current study was designed as an observational, analytical, retrospective cohort study. It included all patients over the age of 18 diagnosed with thoracic trauma, confirmed with a CT scan, and admitted to the Clinical Emergency Hospital of Targu Mureş, Romania. (3) Results: The occurrence of posttraumatic pneumothorax is highly linked to age (p = 0.002), tobacco use (p = 0.01), and obesity (p = 0.01). Furthermore, high values of all hematological ratios, such as the NLR, MLR, PLR, SII, SIRI, and AISI, are directly associated with the occurrence of pneumothorax (p < 0.001). Furthermore, increased values of the NLR, SII, SIRI, and AISI at admission predict a lengthier hospitalization (p = 0.003). (4) Conclusions: Increased neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), systemic inflammatory index (SII), aggregate inflammatory systemic index (AISI), and systemic inflammatory response index (SIRI) levels at admission highly predict the occurrence of pneumothorax, according to our data.
α- and β-Genotyping of Thalassemia Patients Based on a Multimodal Liver MRI Radiomics Model: A Preliminary Study in Two Centers
Authors: Xu Fengming , Feng Qing , Yi Jixing , Tang Cheng , Lin Huashan , Liang Bumin , Luo Chaotian , Guan Kaiming , Li Tao , Peng Peng
Published: March 2023

Background: So far, there is no non-invasive method that can popularize the genetic testing of thalassemia (TM) patients on a large scale. The purpose of the study was to investigate the value of predicting the α- and β- genotypes of TM patients based on a liver MRI radiomics model. Methods: Radiomics features of liver MRI image data and clinical data of 175 TM patients were extracted using Analysis Kinetics (AK) software. The radiomics model with optimal predictive performance was combined with the clinical model to construct a joint model. The predictive performance of the model was evaluated in terms of AUC, accuracy, sensitivity, and specificity. Results: The T2 model showed the best predictive performance: the AUC, accuracy, sensitivity, and specificity of the validation group were 0.88, 0.865, 0.875, and 0.833, respectively. The joint model constructed from T2 image features and clinical features showed higher predictive performance: the AUC, accuracy, sensitivity, and specificity of the validation group were 0.91, 0.846, 0.9, and 0.667, respectively. Conclusion: The liver MRI radiomics model is feasible and reliable for predicting α- and β-genotypes in TM patients.
On Countermeasures against Cooperative Fly of UAV Swarms
Authors: Zhang Xia , Bai Yijie , He Kai
Published: March 2023

Aiming at anti Unmanned Aerial Vehicle (UAV) swarm, this paper studies the detection and suppression mechanisms of emergence in cooperative flight. Cooperative fly is one of the critical operations for UAV swarm in both military and civilian utilities, which allows individual UAVs to distributed adjust their velocity to head for a common destination as well as avoid a collision. This process is viewed as the emergence of complex systems. An emergence detection algorithm based on double thresholds is proposed. It simultaneously monitors the cooperative flight process and system connectivity to accurately identify the occurrence, achievement, or failure of cooperative fly, which provides a solid prerequisite for the suppression mechanism. For suppression, in-band radio interference is designed under the constraint of average power, and the effect is modeled from the perspective of degrading the communication performance of the target system. It is found that low-intensity continuous interference can effectively delay the cooperative fly process and has better concealment, while medium-intensity continuous interference can rapidly stop that process. Based on the above analysis, for the first time, two countermeasures for the UAV swarm’s cooperative fly are designed for the operation intent of delay and disruption of the target UAC swarms, respectively. Simulation results show the effectiveness of the countermeasures.
Fault Diagnosis for Complex Equipment Based on Belief Rule Base with Adaptive Nonlinear Membership Function
Authors: Lian Zheng , Zhou Zhijie , Zhang Xin , Feng Zhichao , Han Xiaoxia , Hu Changhua
Published: March 2023

Fault diagnosis of complex equipment has become a hot field in recent years. Due to excellent uncertainty processing capability and small sample problem modeling capability, belief rule base (BRB) has been widely used in the fault diagnosis. However, previous BRB models almost did not consider the diverse distributions of observation data which may reduce diagnostic accuracy. In this paper, a new fault diagnosis model based on BRB is proposed. Considering that the previous triangular membership function cannot address the diverse distribution of observation data, a new nonlinear membership function is proposed to transform the input information. Then, since the model parameters initially determined by experts are inaccurate, a new parameter optimization model with the parameters of the nonlinear membership function is proposed and driven by the gradient descent method to prevent the expert knowledge from being destroyed. A fault diagnosis case of laser gyro is used to verify the validity of the proposed model. In the case study, the diagnosis accuracy of the new BRB-based fault diagnosis model reached 95.56%, which shows better fault diagnosis performance than other methods.
Two Features of the GINAR(1) Process and Their Impact on the Run-Length Performance of Geometric Control Charts
Authors: Morais Manuel Cabral
Published: March 2023

The geometric first-order integer-valued autoregressive process (GINAR(1)) can be particularly useful to model relevant discrete-valued time series, namely in statistical process control. We resort to stochastic ordering to prove that the GINAR(1) process is a discrete-time Markov chain governed by a totally positive order 2 (TP2) transition matrix.Stochastic ordering is also used to compare transition matrices referring to pairs of GINAR(1) processes with different values of the marginal mean. We assess and illustrate the implications of these two stochastic ordering results, namely on the properties of the run length of geometric charts for monitoring GINAR(1) counts.
The Impact of the COVID-19 Crisis on the Digital Transformation of Organizations
Authors: Burlea-Schiopoiu Adriana , Borcan Ioana , Dragan Cristian Ovidiu
Published: March 2023

The paper aims to analyze the digital transformation process’s defining elements in the COVID-19 crisis. Starting from our main objective, which consists of a critical analysis of the defining elements of the digital transformation process in the conditions of the COVID-19 crisis, we formulate the following specific objectives: to analyze the contribution of external organizational factors to put into practice the new opportunities created by the organization’s digital transformation; to evaluate the impact of digital competencies on the digital transformation of organizations; and to analyze the role of new technologies in developing digital competencies. We used the partial least squares structural equation modeling (PLS-SEM) and the bootstrapped method to evaluate the model fit, and the model was tested by SmartPLS4 software. Our research is based on information from 203 employees with authority for decision making about the digital transformation strategy in their organizations undergoing a digital transformation process. Our findings revealed that organizations, regardless of size, profile, or field of activity, are affected by changes induced by new technologies and the crisis generated by COVID-19. Therefore, formulating a digital transformation strategy must aim to minimize the risks of obsolescence and maximize the results from exploiting new digital resources. However, our results do not prove that COVID-19 crises directly and positively influence the development of digital competencies. This leads us to conclude that developing these competencies is a continuous process unaffected by disruptive factors such as crises. Instead, the development of digital competencies is influenced by new technologies. Therefore, the COVID-19 crisis directly and positively influences organizations’ developing and implementing a digital transformation strategy and new technologies. The theoretical contribution of our research consists of an explanation of the role of perturbator factors, such as the crisis generated by COVID-19, in developing digital competencies and improving digital transformation. The practical contributions are dedicated to managers that should have a different approach to the negative phenomena that will be considered catalytic factors of the digital transformation and disruptive factors of the organizational climate.
Optimized Synchronous Pulse Width Modulation Strategy Based on Discontinuous Carriers
Authors: Jin Xuefeng , Liu Jiahao , Chen Wei , Shi Tingna
Published: March 2023

This article proposes a new technique called optimized discontinuous carrier pulse width modulation (ODCPWM), whose main objective is to solve the issue of significant output voltage harmonics of conventional synchronous carrier modulation at low carrier wave ratios. Based on the symmetry principle, the fundamental wave period is divided into regions; the carriers in adjacent regions are flipped, and the carrier width is changed symmetrically in each region to generate an unequal-width optimized discontinuous carrier pulse width modulation. In addition, using the weighted total harmonic distortion (WTHD) of the line voltage as an evaluation index, an optimized multi-mode PWM strategy is proposed to satisfy the system to operate stably in the whole speed range. The experimental results verify the effectiveness of the proposed strategy. The results show that ODCPWM proposed in this article can eliminate harmonics and multiples of three harmonics in line voltage harmonics. The VWTHD is lower, which improves the quality of the output waveform and makes the system operation more stable and reliable. The proposed multi-mode PWM strategy is smooth and shock-free during switching.
Low-Density Polyethylene Degradation and Energy Yield Using Dielectric Barrier Discharge under Various Electrical Conditions
Authors: Kim Seong-Hun , Yun Ung-Hui , Kim Jin-Gyu
Published: March 2023

The increased use of plastics has seen the emergence of microplastics, which have become progressively more problematic. Although many degradation studies have been conducted to address the problem of microplastics, their impact has not been significant, and much time has been consumed. In this study, low-density polyethylene (LDPE) was degraded using a dielectric barrier discharge (DBD) plasma under various electrical conditions. The experimental results showed that after 120 min of treatment, the removal efficiency reached 5.44%, the carbonyl index (CI) was 1.7308, and the O/C ratio was 0.028. The degree of degradation shown in previous studies was achieved rapidly, and experimental results showed that the degree of LDPE degradation and energy yield was proportional to the voltage and frequency—more specifically, the degree of LDPE surface and internal degradation differed, which should be considered in terms of reducing the extent of mass loss. The results of this study should be helpful for future studies on microplastic degradation using DBD techniques.
XGBoost-Based Intelligent Decision Making of HVDC System with Knowledge Graph
Authors: Li Qiang , Chen Qian , Wu Jiyang , Qiu Youqiang , Zhang Changhong , Huang Yilong , Guo Jianbao , Yang Bo
Published: March 2023

This study aims to achieve intelligent decision making in HVDC systems in the framework of knowledge graphs (KGs). First, the whole life cycle KG of an HVDC system was established by combining intelligent decision making. Then, fault diagnosis was studied as a typical case study, and an intelligent decision-making method for HVDC systems based on XGBoost that significantly improved the speed, accuracy, and robustness of fault diagnosis was designed. It is noteworthy that the dataset used in this study was extracted in the framework of KGs, and the intelligent decision making of KG and HVDC systems was accordingly combined. Four kinds of fault data extracted from KGs were firstly preprocessed, and their features were simultaneously trained. Then, sensitive weights were set, and the pre-computed sample weights were put into the XGBoost model for training. Finally, the trained test set was substituted into the XGBoost classification model after training to obtain the classification results, and the recognition accuracy was calculated by means of a comparison with the standard labels. To further verify the effectiveness of the proposed method, back propagation (BP) neural network, probabilistic neural network (PNN), and classification tree were adopted for validation on the same fault dataset. The experimental results show that the XGBoost used in this paper could achieve accuracy of over 87% in multiple groups of tests, with recognition accuracy and robustness being higher than those of its competitors. Therefore, the method proposed in this paper can effectively identify and diagnose faults in HVDC systems under different operation conditions.
Deep Neural Network for Predicting Changing Market Demands in the Energy Sector for a Sustainable Economy
Authors: Wen Mingming , Zhou Changshi , Konstantin Mamonov
Published: March 2023

Increasing access to power, enhancing clean cooking fuels, decreasing wasteful energy subsidies, and limiting fatal air pollution are just a few of the sustainable development goals that all revolve around energy (E). Energy-specific sustainable development objectives were a turning point in the global shift towards a more sustainable and just system. By understanding energy resources, markets, regulations, and scientific studies, the country can progress more quickly towards a sustainable economy (SE). Investment in renewable energy industries is hampered by institutional obstacles such as market-controlled procedures and inconsistent supporting policies. Power plant building is currently incompatible with existing transmission and distribution networks, posing significant risks to investors. Deep neural networks (DNN) are specifically investigated in this article for energy demand forecasting at the individual building level. Other relevant information is supplied into fully connected layers along with the convolutional output. A single customer’s power usage data were used and analyzed for the final fuel and electricity consumption by various energy sources and consumer groups to test the DNN-SE technique. The energy intensity and labor productivity indexes for several economic sectors are displayed. A wide range of economic activities are examined to determine their impact on environmental pollution indicators, greenhouse gas emissions, and other air pollutants. A more effective and comprehensive energy efficiency strategy should be implemented to lower emission levels at lower prices. Research-based conclusions must be enhanced to help policymaking. The results of the experiment using the proposed method show that it is possible to predict 98.1%, grow at 96.8%, meet 98.5% of electricity demand, use 97.6% of power, and have a renewable energy ratio of 96.2%.
An Optimal Scheduling Method of Shared Energy Storage System Considering Distribution Network Operation Risk
Authors: Chen Jiahao , Sun Bing , Zeng Yuan , Jing Ruipeng , Dong Shimeng , Wang Jingran
Published: March 2023

Shared energy storage systems (SESS) have been gradually developed and applied to distribution networks (DN). There are electrical connections between SESSs and multiple DN nodes; SESSs could significantly improve the power restoration potential and reduce the power interruption cost during fault periods. Currently, a major challenge exists in terms of how to consider both the efficiency of the operation and the reliability cost when formulating the SESS scheduling scheme. A SESS optimal scheduling method that considers the DN operation risk is proposed in this paper. First, a multi-objective day-ahead scheduling model for SESS is developed, where the user’s interruption cost is regarded as the reliability cost and it is the product of the occurrence probability of the expected accident and the loss of power outage. Then, an island partition model with SESS was established in order to accurately calculate the reliability cost. Via the maximum island partition and island optimal rectification, the SESS was carefully integrated into the power restoration system. Furthermore, in order to minimize the comprehensive operation cost, an improved genetic algorithm for the island partition was designed to solve the complex SESS optimal scheduling model. Finally, a case study on the improved PG&E 69 bus system was analyzed. Moreover, we found that the DN’s comprehensive operation cost decreased by 6.6% using the proposed method.
The Law of Liquid–Solid Carrying in the Wellbore of Natural Gas Hydrate Gas Well under the Condition of Foam Drainage Gas Recovery
Authors: Li Haitao , Wei Na , Hu Haiyu , Ge Zhaolong , Jiang Lin , Liu Fengjun , Wang Xiaoran , Zhang Chao , Xu Hanming , Pei Jun , Kvamme Bjørn
Published: March 2023

During the trial production of marine gas hydrate in the former Soviet Union, Canada, North Slope of Alaska, South Sea Trough of Japan and Shenhu Sea of South China Sea, the problem of sand and water production cannot be avoided. The problems of sand production and water production in the process of natural gas hydrate depressurization exploitation have seriously restricted the exploitation efficiency and production of natural gas hydrate. The problems of sand production and water production are some of the main factors that prevent natural gas hydrate being commercially exploited. Therefore, it is urgent to carry out useful, relevant and cutting-edge research on the efficient drainage of sand and water from the wellbore in the process of natural gas hydrate mining. This paper innovatively proposes liquid-carrying and solid-carrying technology under foam circulation purging to address the existing problems of sand removal and drainage technology in hydrate mining. At present, no scholar has used this technology to solve the problem of sand removal and drainage in hydrate mining. Therefore, the research on efficient drainage is imperative. In this paper, We mainly studied the liquid-carrying and solid-carrying of vertical wellbore under the condition of foam cycle purging. We have revealed the relevant the liquid-carrying law and solid-carrying law through the above research.
Pump-Valve Combined Control of a HVAC Chilled Water System Using an Artificial Neural Network Model
Authors: Gao Bo , Ni Ji , Yuan Zhongyuan , Yu Nanyang
Published: March 2023

A chilled water system transports cooling functionality from refrigerators to users via heating, ventilation, and air conditioning (HVAC) systems. This paper investigated an optimal control strategy to regulate the volume flow rate of each user branch in a chilled water system, considering the minimum resistance operation to reduce energy consumption. An artificial neural network (ANN) was adopted to establish the nonlinear relationship between the volume flow rate of each user branch, pump frequency, and valve opening of each user branch. An optimal control strategy for a chilled water HVAC system is proposed in this article, according to the pump-valve combined control (PVCC) principle and an ANN model, i.e., pump-valve combined control using an artificial neural network model (PVCC-ANN). A series of tests were conducted to collect data to train the ANN model and analyze the performance of the PVCC-ANN in an experimental chilled water system. The results show that the trained ANN model has good prediction performance. A minimum resistance operation can be achieved to control the volume flow rate of each user branch independently by using the PVCC-ANN model. Moreover, the proposed PVCC-ANN method shows good energy-saving performance in chilled water systems, which can be attributed to the minimum resistance operation. Taking the energy consumption of the pump’s constant frequency operation as the reference, the energy saving rate using the PVCC-ANN is between 14.3% and 58.6% under 10 operating conditions, as reported in this paper.
Advanced Method of Variable Refrigerant Flow (VRF) System Design to Forecast on Site Operation—Part 3: Optimal Solutions to Minimize Sizes
Authors: Radchenko Mykola , Radchenko Andrii , Trushliakov Eugeniy , Pavlenko Anatoliy , Radchenko Roman
Published: March 2023

Outdoor air conditioning systems (ACS) are used as autonomic systems as well as in combined outdoor and indoor ACS of the variable refrigerant flow (VRF) type, with variable speed compressors (VSC) as their advanced version. Methods for determining the optimal value of refrigeration capacity and providing the maximum rate of the summarized annual refrigeration energy generation increment, according to its needs at minimum compressor sizes and rational values, are applied to reveal the reserves for reducing the designed (installed) refrigeration capacity, thus enabling us to practically achieve maximum annual refrigeration energy generation as the primary criterion at the second stage of the general design methodology previously developed by the authors. The principle of sharing the total thermal load on the ACS between the ranges of changeable loads for outdoor air precooling, and a relatively stable load range for further processing air are used as its basis. According to this principle, the changeable thermal load range is chosen as the object for energy saving by recuperating the excessive refrigeration generated at lowered loading in order to compensate for the increased loads, thereby matching actual duties at a reduced designed refrigeration capacity. The method allows us to determine the corresponding level of regulated loads (LRL) of SRC and the load range of compressor operation to minimize sizes.
Characterization of Anatomical and Non-Anatomical Properties for the Identification of Six Commercial Wood Species from Vietnamese Plantation Forests
Authors: Savero Alvin Muhammad , Kim Jong Ho , Purusatama Byantara Darsan , Prasetia Denni , Park Se Hwi , Van Duong Doan , Kim Nam Hun
Published: March 2023

This study investigated the anatomical and non-anatomical characteristics of six wood species, Acacia mangium, Acacia hybrid, Dillenia pentagyna, Anacardium occidentale, Hevea brasiliensis, and Melaleuca cajuputi, from a plantation in Vietnam. The anatomical characteristics and non-anatomical characteristics were observed following the International Association of Wood Anatomists (IAWA) list. All species showed diffuse porosity and non-septate fibers. Exclusively solitary vessels were only observed in M. cajuputi. Vestured pits were observed in A. mangium, A. hybrid, and M. cajuputi, and tyloses were found in A. occidentale and H. brasiliensis. We observed vasicentric axial parenchyma in A. mangium, A. hybrid, A. occidentale, and H. brasiliensis, whereas diffuse axial parenchyma was observed in D. pentagyna and M. cajuputi. Further, prismatic crystals in the axial parenchyma cells existed in A. mangium, A. hybrid, and H. brasiliensis, and raphides in ray cells were observed in D. pentagyna. Silica bodies in ray cells were found in A. occidentale and M. cajuputi. H. brasiliensis exhibited the greatest vessel diameter and ray height, with D. pentagyna exhibiting the greatest fiber length and wall thickness. All the species showed considerable differences in heartwood fluorescence, water and ethanol extract colors, and froth test reactions.
The Psychological Effects and Benefits of Using Green Spaces in the City: A Field Experiment with Young Polish Adults
Authors: Janeczko Emilia , Czyżyk Krzysztof , Korcz Natalia , Woźnicka Małgorzata , Bielinis Ernest
Published: March 2023

Green spaces in cities are places where city dwellers can have contact with nature, which, according to the research to date, can have a very beneficial effect on their mental well-being. However, it is still not entirely clear which characteristics of green spaces are most beneficial in terms of their positive impact on people. In this study, we focus on identifying the restorative attributes of tree canopy sites (forests, street greenery) and open green spaces (water, meadows). Four psychometric tests were used to examine the subjects’ reactions before and after exposure to the analyzed environments (the control environment was the room in which the pre-test was conducted). The experiment was conducted with 55 young adult university students. It was shown that, compared to the post-housing (control) environment, all green spaces influenced the subjects’ well-being. The water environment had the most beneficial effect, followed by a meadow, a forest, and a housing estate with the presence of urban greenery. A short walk amid open urban green spaces, which provide more opportunities for observation, has a better impact on the well-being of the respondents compared to tree canopy sites such as forests or street greenery.
Pilot Scale Evaluation of Wild Saccharomyces cerevisiae Strains in Aglianico
Authors: Gottardi Davide , Siesto Gabriella , Bevilacqua Antonio , Patrignani Francesca , Campaniello Daniela , Speranza Barbara , Lanciotti Rosalba , Capece Angela , Romano Patrizia
Published: March 2023

In winemaking, the influence of Saccharomyces cerevisiae strains on the aromatic components of wine is well recognized on a laboratory scale, but few studies deal with the comparison of numerous strains on a pilot scale fermentation. In this scenario, the present work aimed to validate the fermentative behavior of seven wild S. cerevisiae strains on pilot-scale fermentations to evaluate their impact on the aromatic profiles of the resulting wines. The strains, isolated from grapes of different Italian regional varieties, were tested in pilot-scale fermentation trials performed in the cellar in 1 hL of Aglianico grape must. Then, wines were analyzed for their microbiological cell loads, main chemical parameters of enological interest (ethanol, total sugars, fructose, glucose, total and volatile acidity, malic and lactic acids) and volatile aroma profiles by GC/MS/SPME. Seventy-six volatile compounds belonging to six different classes (esters, alcohols, terpenes, aldehydes, acids, and ketones) were identified. The seven strains showed different trends and significant differences, and for each class of compounds, high-producing and low-producing strains were found. Since the present work was performed at a pilot-scale level, mimicking as much as possible real working conditions, the results obtained can be considered as a validation of the screened S. cerevisiae strains and a strategy to discriminate in real closed conditions strains able to impart desired wine sensory features.
Relational Action Bank with Semantic–Visual Attention for Few-Shot Action Recognition
Authors: Liang Haoming , Du Jinze , Zhang Hongchen , Han Bing , Ma Yan
Published: March 2023

Recently, few-shot learning has attracted significant attention in the field of video action recognition, owing to its data-efficient learning paradigm. Despite the encouraging progress, identifying ways to further improve the few-shot learning performance by exploring additional or auxiliary information for video action recognition remains an ongoing challenge. To address this problem, in this paper we make the first attempt to propose a relational action bank with semantic–visual attention for few-shot action recognition. Specifically, we introduce a relational action bank as the auxiliary library to assist the network in understanding the actions in novel classes. Meanwhile, the semantic–visual attention is devised to adaptively capture the connections to the foregone actions via both semantic correlation and visual similarity. We extensively evaluate our approach via two backbone models (ResNet-50 and C3D) on HMDB and Kinetics datasets, and demonstrate that the proposed model can obtain significantly better performance compared against state-of-the-art methods. Notably, our results demonstrate an average improvement of about 6.2% when compared to the second-best method on the Kinetics dataset.
Network Pharmacology Combined with an Experimental Validation Study to Reveal the Effect and Mechanism of Eucommia ulmoides Leaf Polysaccharide against Immunomodulation
Authors: Cui Enhui , Tang Pan , Zhu Xiaoyan , Lv Mengyuan , Wang Shuai , Xue Yuhuan , Li Cixia , Zhao Shanting
Published: March 2023

In the present study, the immuno-enhancing effect of Eucommia ulmoides leaf polysaccharide (ELP) was investigated in immunosuppressed mice induced by cyclophosphamide (CTX). To evaluate the immune enhancement mechanism of ELP, the immunoregulation effect of ELP was evaluated in vitro and in vivo. ELP is primarily composed of arabinose (26.61%), galacturonic acid (25.1%), galactose (19.35%), rhamnose (16.13%), and a small amount of glucose (12.9%). At 1000~5000 μg·mL−1, ELP could significantly enhance the proliferation and the phagocytosis of macrophages in vitro. Additionally, ELP could protect immune organs, reduce pathological damage, and reverse the decrease in the hematological indices. Moreover, ELP significantly increased the phagocytic index, enhanced the ear swelling response, augmented the production of inflammatory cytokines, and markedly up-regulated the expression of IL-1β, IL-6, and TNF-α mRNA levels. Furthermore, ELP improved phosphorylated p38, ERK1/2, and JNK levels, suggesting that MAPKs might be involved in immunomodulatory effects. The results provide a theoretical foundation for exploring the immune modulation function of ELP as a functional food.
Validation of an LC-MS/MS Method for the Determination of Abscisic Acid Concentration in a Real-World Setting
Authors: Schiano Elisabetta , Neri Ilaria , Maisto Maria , Novellino Ettore , Iannuzzo Fortuna , Piccolo Vincenzo , Summa Vincenzo , Grumetto Lucia , Tenore Gian Carlo
Published: March 2023

One of the most relevant aspects in evaluating the impact of natural bioactive compounds on human health is the assessment of their bioavailability. In this regard, abscisic acid (ABA) has attracted particular interest as a plant-derived molecule mainly involved in the regulation of plant physiology. Remarkably, ABA was also found in mammals as an endogenous hormone involved in the upstream control of glucose homeostasis, as evidenced by its increase after glucose load. The present work focused on the development and validation of a method for the determination of ABA in biological samples through liquid–liquid extraction (LLE), followed by liquid mass spectrometry (LC-MS) of the extract. To test method suitability, this optimized and validated method was applied to a pilot study on eight healthy volunteers’ serum levels to evaluate ABA concentration after consumption of a standardized test meal (STM) and the administration of an ABA-rich nutraceutical product. The results obtained could meet the demands of clinical laboratories to determine the response to a glucose-containing meal in terms of ABA concentration. Interestingly, the detection of this endogenous hormone in such a real-world setting could represent a useful tool to investigate the occurrence of impaired ABA release in dysglycemic individuals and to monitor its eventual improvement in response to chronic nutraceutical supplementation.
Essential Oils: Recent Advances on Their Dual Role as Food Preservatives and Nutraceuticals against the Metabolic Syndrome
Authors: Chávez-Delgado Emily L. , Jacobo-Velázquez Daniel A.
Published: March 2023

Essential oils (EO) are compounds synthesized by plants as secondary products and are a complex mixture of volatile molecules. Studies have demonstrated their pharmacological activity in the prevention and treatment of metabolic syndrome (MetS). Moreover, they have been used as antimicrobial and antioxidant food additives. The first part of this review discusses the role of EO as nutraceuticals to prevent metabolic syndrome-related disorders (i.e., obesity, diabetes, and neurodegenerative diseases), showing results from in vitro and in vivo studies. Likewise, the second part describes the bioavailability and mechanisms of action of EO in preventing chronic diseases. The third part presents the application of EO as food additives, pointing out their antimicrobial and antioxidant activity in food formulations. Finally, the last part explains the stability and methods for encapsulating EO. In conclusion, EO dual role as nutraceuticals and food additives makes them excellent candidates to formulate dietary supplements and functional foods. However, further investigation is needed to understand EO interaction mechanisms with human metabolic pathways and to develop novel technological approaches to enhance EO stability in food systems to scale up these processes and, in this way, to overcome current health problems.
Day Ahead Electric Load Forecast: A Comprehensive LSTM-EMD Methodology and Several Diverse Case Studies
Authors: Wood Michael , Ogliari Emanuele , Nespoli Alfredo , Simpkins Travis , Leva Sonia
Published: March 2023

Optimal behind-the-meter energy management often requires a day-ahead electric load forecast capable of learning non-linear and non-stationary patterns, due to the spatial disaggregation of loads and concept drift associated with time-varying physics and behavior. There are many promising machine learning techniques in the literature, but black box models lack explainability and therefore confidence in the models’ robustness can’t be achieved without thorough testing on data sets with varying and representative statistical properties. Therefore this work adopts and builds on some of the highest-performing load forecasting tools in the literature, which are Long Short-Term Memory recurrent networks, Empirical Mode Decomposition for feature engineering, and k-means clustering for outlier detection, and tests a combined methodology on seven different load data sets from six different load sectors. Forecast test set results are benchmarked against a seasonal naive model and SARIMA. The resultant skill scores range from −6.3% to 73%, indicating that the methodology adopted is often but not exclusively effective relative to the benchmarks.
Interplay between microRNAs, Serum Proprotein Convertase Subtilisin/Kexin Type 9 (PCSK9), and Lipid Parameters in Patients with Very High Lipoprotein(a) Treated with PCSK9 Inhibitors
Authors: Levstek Tina , Karun Tina , Rehberger Likozar Andreja , Šebeštjen Miran , Trebušak Podkrajšek Katarina
Published: March 2023

Proprotein convertase subtilisin/kexin type 9 (PCSK9) has an important function in the regulation of lipid metabolism. PCSK9 reduces hepatic low-density lipoprotein receptors, thereby increasing low-density lipoprotein cholesterol levels. However, its regulation remains to be elucidated, including post-transcriptional regulation by microRNAs (miRNAs). We aimed to explore the interplay between miRNAs, total serum PCSK9, and lipids during treatment with PCSK9 inhibitors. A total of 64 patients with stable coronary artery disease and very high lipoprotein(a) levels and 16 sex- and age-matched control subjects were enrolled. Patients received a PCSK9 inhibitor (evolocumab or alirocumab). Total serum PCSK9 levels were measured by immunoassay. RNA was isolated from plasma using magnetic beads, and expression of selected miRNAs was analyzed by quantitative PCR. Total serum PCSK9 levels were significantly higher in control subjects compared with patients. After 6 months of treatment with PCSK9 inhibitors, total serum PCSK9 levels increased significantly. The expression of miR-191-5p was significantly lower, and the expression of miR-224-5p and miR-483-5p was significantly higher in patients compared with control subjects. Using linear regression, the expression of miR-483-5p significantly predicted the serum PCSK9 level at baseline. After the 6-month period of therapy, the expression of miR-191-5p and miR-483-5p significantly increased. Our results support a role for miR-483-5p in regulating circulating PCSK9 in vivo. The difference in expression of miR-191-5p, miR-224-5p, and miR-337-3p between patients and control subjects suggests their possible role in the pathogenesis of coronary artery disease.
Quantitative Evaluation of Dental Students’ Perceptions of the Roleplay-Video Teaching Modality in Clinical Courses of Dentistry: A Pilot Study
Authors: Ganji Kiran Kumar , Nagarajappa Anil Kumar , Sghaireen Mohammed G , Srivastava Kumar Chandan , Alam Mohammad Khursheed , Nashwan Shadi , Al-Qerem Ahmad , Khader Yousef
Published: March 2023

In the modern era of dentistry, role modeling/roleplaying is one of the most prevalent and recommended methods of dental education. Working on video production projects and using student-centred learning also help students create feelings of ownership and self-esteem. This study aimed to compare students’ perceptions of roleplay videos among genders, different disciplines of dentistry, and different levels of dental students. This study included 180 third- and fourth-year dental students registered in courses such as ‘Introduction to Dental Practice’ and ‘Surgical management of oral and maxillofacial diseases’, respectively, at the College of Dentistry at Jouf University. Four groups of recruited participants were pre-tested using a questionnaire about their clinical and communication skills. The students were tested again using the same questionnaire at the end of the workshop to evaluate improvements in their skills. The students were then assigned to create roleplay videos with respect to demonstrated skills related to all three disciplines (Periodontics, Oral Surgery, and Oral Radiology) in a week’s time. Students’ perceptions of the roleplay video assignments were collected through a questionnaire survey. The Kruskal–Wallis test was used to compare responses for each section of the questionnaire (p < 0.05). Improvements in problem-solving and project management skills during video production were reported by 90% of the participants. No significant difference (p > 0.05) in the mean scores of the responses was found with respect to the type of discipline involved in the process. There was a significant difference in the mean scores of the responses between male and female students (p < 0.05). The fourth year participants demonstrated increased mean scores and significantly higher (p < 0.05) mean scores than third-year participants. Students’ perceptions of roleplay videos differed by gender and the level of the students, but not by the type of discipline.
Barriers to Couplet Care of the Infant Requiring Additional Care: Integrative Review
Authors: Curley Amanda , Jones Linda K. , Staff Lynette
Published: March 2023

Background: Historically, once the baby was born, the mother and baby were separated shortly after birth into a postnatal ward and a baby nursery. Overtime, with advances in neonatology led to an increasing number of neonates being separated from their mothers at birth for specialised neonatal care if they required additional needs. As more research has been undertaken there is an increasing focus that mothers and babies should be kept together from birth, termed couplet care. Couplet care refers to keeping the mother and baby together. Despite this evidence, in practice, this is not happening. Aim: to examine the barriers to nurses and midwives providing couplet care of the infant requiring additional needs in postnatal and nursery. Methods: A thorough literature review relies on a well-developed search strategy. This resulted in a total of 20 papers that were included in this review. Results: This review revealed five main themes or barriers to nurses and midwives providing couplet care: models of care, systems and other barriers, safety, resistance, and education. Discussion: Resistance to couplet care was discussed as being caused by feelings of lack of confidence and competence, concerns around maternal and infant safety and an under-recognition of the benefits of couplet care. Conclusion: The conclusion is that there is still a paucity of research in relation to nursing and midwifery barriers to couplet care. Although this review discusses barriers to couplet care, more specific original research on what nurses and midwives themselves perceive to be the barriers to couplet care in Australia is needed. The recommendation is therefore to undertake research into this area and interview nurses and midwives to ascertain their perspectives.
Genetic Algorithm for Solving the No-Wait Three-Stage Surgery Scheduling Problem
Authors: Lin Yang-Kuei , Yen Chen-Hao
Published: March 2023

In this research, we consider a deterministic three-stage operating room surgery scheduling problem. The three successive stages are pre-surgery, surgery, and post-surgery. The no-wait constraint is considered among the three stages. Surgeries are known in advance (elective). Multiple resources are considered throughout the surgical process: PHU (preoperative holding unit) beds in the first stage, ORs (operating rooms) in the second stage, and PACU (post-anesthesia care unit) beds in the third stage. The objective is to minimize the makespan. The makespan is defined as the maximum end time of the last activity in stage 3. Minimizing the makespan not only maximizes the utilization of ORs but also improves patient satisfaction by allowing treatments to be delivered to patients in a timely manner. We proposed a genetic algorithm (GA) for solving the operating room scheduling problem. Randomly generated problem instances were tested to evaluate the performance of the proposed GA. The computational results show that overall, the GA deviated from the lower bound (LB) by 3.25% on average, and the average computation time of the GA was 10.71 s. We conclude that the GA can efficiently find near-optimal solutions to the daily three-stage operating room surgery scheduling problem.