bluuebunny/crossref_metadata_2025 huggingface dataset:
Plasmodium malariae Detected by Microscopy in the International Bordering Area of Mizoram, a Northeastern State of India
Authors: Singh Kuldeep , Bharti Praveen Kumar , Devi Naorem Chaoba , Ahmed Naseem , Sharma Amit
Published: August 2022

Northeastern states of India share international borders with Myanmar, China, Bangladesh, and Bhutan, contributing 7.45% of the overall malaria cases in the country. Mizoram accounts for the highest malaria burden in the northeastern states, with perennial transmission in the hilly and deep-forested areas. Plasmodium falciparum (93%) is the most prevalent human Plasmodium species, followed by P. vivax; however, information on P. ovale and P. malariae is negligible. Rapid diagnostic tests (RDTs) are the most preferred malaria diagnostic tool followed by microscopy in this high malaria-endemic region. The present epidemiological study was carried out in July and August 2019 to assess the malaria burden in and around the Chawngte primary health center, Lawngtlai District of Mizoram, using RDTs and microscopy as diagnostic tools. World Health Organization-certified level I microscopists examined the blood smears. Diagnosis using RDTs resulted in 151 malaria cases (P. falciparum: 136; P. vivax: 15) out of 948 screened fever cases. However, blood smear examination detected 179 cases (P. falciparum: 154; P. vivax: 17; mixed P. falciparum + P. vivax infection: 3; P. malariae: 5). Analysis revealed that the risk of malaria infection was higher in the ≥5-year-old subjects than in the under-5 age group. The mean parasite density of P. malariae (1455.00/μL blood) was the lowest; cf. with P. falciparum: 12,275.08/μL blood. Surveillance at the point-of-care level using microscopy was able to detect all the four human Plasmodium species and their mixed infections, including P. malariae, which were missed with RDTs. Thus, the quality of microscopy along with trained manpower should be strengthened to diagnose all human malaria parasite species (particularly P. malariae and P. ovale) until the molecular tools are deployed at the field level to achieve malaria elimination by 2030.
A Fused Deep Learning Architecture for the Detection of the Relationship between the Mandibular Third Molar and the Mandibular Canal
Authors: Buyuk Cansu , Akkaya Nurullah , Arsan Belde , Unsal Gurkan , Aksoy Secil , Orhan Kaan
Published: August 2022

The study aimed to generate a fused deep learning algorithm that detects and classifies the relationship between the mandibular third molar and mandibular canal on orthopantomographs. Radiographs (n = 1880) were randomly selected from the hospital archive. Two dentomaxillofacial radiologists annotated the data via MATLAB and classified them into four groups according to the overlap of the root of the mandibular third molar and mandibular canal. Each radiograph was segmented using a U-Net-like architecture. The segmented images were classified by AlexNet. Accuracy, the weighted intersection over union score, the dice coefficient, specificity, sensitivity, and area under curve metrics were used to quantify the performance of the models. Also, three dental practitioners were asked to classify the same test data, their success rate was assessed using the Intraclass Correlation Coefficient. The segmentation network achieved a global accuracy of 0.99 and a weighted intersection over union score of 0.98, average dice score overall images was 0.91. The classification network achieved an accuracy of 0.80, per class sensitivity of 0.74, 0.83, 0.86, 0.67, per class specificity of 0.92, 0.95, 0.88, 0.96 and AUC score of 0.85. The most successful dental practitioner achieved a success rate of 0.79. The fused segmentation and classification networks produced encouraging results. The final model achieved almost the same classification performance as dental practitioners. Better diagnostic accuracy of the combined artificial intelligence tools may help to improve the prediction of the risk factors, especially for recognizing such anatomical variations.
The Management of Pregnancy Complicated with the Previable Preterm and Preterm Premature Rupture of the Membranes: What about a Limit of Neonatal Viability?—A Review
Authors: Feduniw Stepan , Gaca Zuzanna , Malinowska Olga , Brunets Weronika , Zgliczyńska Magdalena , Włodarczyk Marta , Wójcikiewicz Anna , Ciebiera Michał
Published: August 2022

Preterm premature rupture of the membranes (PPROM) at the limit of viability is associated with low neonatal survival rates and a high rate of neonatal complications in survivors. It carries a major risk of maternal morbidity and mortality. The limit of viability can be defined as the earliest stage of fetal maturity when a fetus has a reasonable chance, although not a high likelihood, for extra-uterine survival. The study reviews available data on preventing preterm delivery caused by the previable PPROM, pregnancy latency, therapeutic options including the use of antibiotics and steroids, neonatal outcomes, and future directions and opportunities.
Detection of Autoantibodies in Saliva as New Avenue for the Diagnosis and Management of Autoimmune Patients
Authors: Sciascia Savino , Bentow Chelsea , Radin Massimo , Barinotti Alice , Cecchi Irene , Foddai Silvia , Roccatello Dario , Mahler Michael
Published: August 2022

(1) Background: Autoimmune diseases are characterized by autoantibodies directed to a large number of antigenic targets and are measured using serum as sample matrix. Although serum is a very common specimen type, it comes with certain drawbacks. Most importantly, it depends on venous puncture and requires medical personnel for sampling. This is of particular importance in light of the limited healthcare access of patients with autoimmune diseases during the COVID-19 pandemic. Consequently, alternative sample matrices are being explored for the measurement of autoantibodies. Our study aimed to establish the feasibility of measuring autoantibodies in saliva samples using a novel and highly sensitive method for the detection of autoantibodies. (2) Methods: A total of 48 serum/saliva pairs were collected and tested using a novel particle-based multi-analyte technology (PMAT) system for the presence of a wide range of autoantibodies. (3) Results: A high level of correlation was observed between the results obtained with serum and saliva (Spearman’s rho = 0.725). Study participants clearly preferred saliva over serum sampling as part of the usability assessment. (4) Conclusions: Saliva represents a promising alternative sample matrix for the detection of autoantibodies. The usability study showed a clear preference of saliva over serum as a sample matrix.
Multi-Scale Hybrid Network for Polyp Detection in Wireless Capsule Endoscopy and Colonoscopy Images
Authors: Souaidi Meryem , El Ansari Mohamed
Published: August 2022

The trade-off between speed and precision is a key step in the detection of small polyps in wireless capsule endoscopy (WCE) images. In this paper, we propose a hybrid network of an inception v4 architecture-based single-shot multibox detector (Hyb-SSDNet) to detect small polyp regions in both WCE and colonoscopy frames. Medical privacy concerns are considered the main barriers to WCE image acquisition. To satisfy the object detection requirements, we enlarged the training datasets and investigated deep transfer learning techniques. The Hyb-SSDNet framework adopts inception blocks to alleviate the inherent limitations of the convolution operation to incorporate contextual features and semantic information into deep networks. It consists of four main components: (a) multi-scale encoding of small polyp regions, (b) using the inception v4 backbone to enhance more contextual features in shallow and middle layers, and (c) concatenating weighted features of mid-level feature maps, giving them more importance to highly extract semantic information. Then, the feature map fusion is delivered to the next layer, followed by some downsampling blocks to generate new pyramidal layers. Finally, the feature maps are fed to multibox detectors, consistent with the SSD process-based VGG16 network. The Hyb-SSDNet achieved a 93.29% mean average precision (mAP) and a testing speed of 44.5 FPS on the WCE dataset. This work proves that deep learning has the potential to develop future research in polyp detection and classification tasks.
The Bathy-Drone: An Autonomous Unmanned Drone-Tethered Sonar System
Authors: Diaz Antonio L. , Ortega Andrew E. , Tingle Henry , Pulido Andres , Cordero Orlando , Nelson Marisa , Cocoves Nicholas E. , Shin Jaejeong , Carthy Raymond R. , Wilkinson Benjamin E. , Ifju Peter G.
Published: August 2022

A unique drone-based system for underwater mapping (bathymetry) was developed at the University of Florida. The system, called the “Bathy-drone”, comprises a drone that drags, via a tether, a small vessel on the water surface in a raster pattern. The vessel is equipped with a recreational commercial off-the-shelf (COTS) sonar unit that has down-scan, side-scan, and chirp capabilities and logs GPS-referenced sonar data onboard or transmitted in real time with a telemetry link. Data can then be retrieved post mission and plotted in various ways. The system provides both isobaths and contours of bottom hardness. Extensive testing of the system was conducted on a 5 acre pond located at the University of Florida Plant Science and Education Unit in Citra, FL. Prior to performing scans of the pond, ground-truth data were acquired with an RTK GNSS unit on a pole to precisely measure the location of the bottom at over 300 locations. An assessment of the accuracy and resolution of the system was performed by comparison to the ground-truth data. The pond ground truth had an average depth of 2.30 m while the Bathy-drone measured an average 21.6 cm deeper than the ground truth, repeatable to within 2.6 cm. The results justify integration of RTK and IMU corrections. During testing, it was found that there are numerous advantages of the Bathy-drone system compared to conventional methods including ease of implementation and the ability to initiate surveys from the land by flying the system to the water or placing the platform in the water. The system is also inexpensive, lightweight, and low-volume, thus making transport convenient. The Bathy-drone can collect data at speeds of 0–24 km/h (0–15 mph) and, thus, can be used in waters with swift currents. Additionally, there are no propellers or control surfaces underwater; hence, the vessel does not tend to snag on floating vegetation and can be dragged over sandbars. An area of more than 10 acres was surveyed using the Bathy-drone in one battery charge and in less than 25 min.
Optimal Maneuvering for Autonomous Vehicle Self-Localization
Authors: McGuire John L. , Law Yee Wei , Doğançay Kutluyıl , Ho Sook-Ying , Chahl Javaan
Published: August 2022

We consider the problem of optimal maneuvering, where an autonomous vehicle, an unmanned aerial vehicle (UAV) for example, must maneuver to maximize or minimize an objective function. We consider a vehicle navigating in a Global Navigation Satellite System (GNSS)-denied environment that self-localizes in two dimensions using angle-of-arrival (AOA) measurements from stationary beacons at known locations. The objective of the vehicle is to travel along the path that minimizes its position and heading estimation error. This article presents an informative path planning (IPP) algorithm that (i) uses the determinant of the self-localization estimation error covariance matrix of an unscented Kalman filter as the objective function; (ii) applies an l-step look-ahead (LSLA) algorithm to determine the optimal heading for a constant-speed vehicle. The novel algorithm takes into account the kinematic constraints of the vehicle and the AOA means of measurement. We evaluate the performance of the algorithm in five scenarios involving stationary and mobile beacons and we find the estimation error approaches the lower bound for the estimator. The simulations show the vehicle maneuvers to locations that allow for minimum estimation uncertainty, even when beacon placement is not conducive to accurate estimation.
CRC-Aided Adaptive BP Decoding of PAC Codes
Authors: Zhang Xianwen , Jiang Ming , Zhu Mingyang , Liu Kailin , Zhao Chunming
Published: August 2022

Although long polar codes with successive cancellation decoding can asymptotically achieve channel capacity, the performance of short blocklength polar codes is far from optimal. Recently, Arıkan proposed employing a convolutional pre-transformation before the polarization network, called polarization-adjusted convolutional (PAC) codes. In this paper, we focus on improving the performance of short PAC codes concatenated with a cyclic redundancy check (CRC) outer code, CRC-PAC codes, since error detection capability is essential in practical applications, such as the polar coding scheme for the control channel. We propose an enhanced adaptive belief propagation (ABP) decoding algorithm with the assistance of CRC bits for PAC codes. We also derive joint parity-check matrices of CRC-PAC codes suitable for iterative BP decoding. The proposed CRC-aided ABP (CA-ABP) decoding can effectively improve error performance when partial CRC bits are used in the decoding. Meanwhile, the error detection ability can still be guaranteed by the remaining CRC bits and adaptive decoding parameters. Moreover, compared with the conventional CRC-aided list (CA-List) decoding, our proposed scheme can significantly reduce computational complexity, to achieve a better trade-off between the performance and complexity for short PAC codes.
Consensus Problem and Formation Control for Heterogeneous Multi-Agent Systems with Switching Topologies
Authors: Wang Chunping , Wang Jiaqi , Wu Ping , Gao Jinfeng
Published: August 2022

The cooperative control problem of discrete-time multi-agent systems (MASs) is discussed, and bounded uncertain time-delays and directed switching topologies are considered. By applying model transformations and matrix theory, an augmented system method is introduced to handle a heterogeneous time-delay MAS. Then, the consensus problem of the system is turned to the convergence issue of the product of innumerable row stochastic matrices. Sufficient conditions for asymptotic consensus of the system under directed switching topologies are obtained. Moreover, a novel consensus-based formation control strategy is designed to gain sufficient and necessary conditions for the formation control of a second-order differential robot system. Finally, the effectiveness of the obtained results is verified through simulations.
Dynamic Multi-View Coupled Graph Convolution Network for Urban Travel Demand Forecasting
Authors: Liu Zhi , Bian Jixin , Zhang Deju , Chen Yang , Shen Guojiang , Kong Xiangjie
Published: August 2022

Accurate urban travel demand forecasting can help organize traffic flow, improve traffic utilization, reduce passenger waiting time, etc. It plays an important role in intelligent transportation systems. Most of the existing research methods construct static graphs from a single perspective or two perspectives, without considering the dynamic impact of time changes and various factors on traffic demand. Moreover, travel demand is also affected by regional functions such as weather, etc. To address these issues, we propose an urban travel demand prediction framework based on dynamic multi-view coupled graph convolution (DMV-GCN). Specifically, we dynamically construct demand similarity graphs based on node features to model the dynamic correlation of demand. Then we combine it with the predefined geographic similarity graph, functional similarity graph, and road similarity graph. We use coupled graph convolution network and gated recurrent units (GRU), to model the spatio-temporal correlation in traffic. We conduct extensive experiments over two large real-world datasets. The results verify the superior performance of our proposed approach for the urban travel demand forecasting task.
Single-Objective Particle Swarm Optimization-Based Chaotic Image Encryption Scheme
Authors: Wang Jingya , Song Xianhua , El-Latif Ahmed A. Abd
Published: August 2022

High security has always been the ultimate goal of image encryption, and the closer the ciphertext image is to the true random number, the higher the security. Aiming at popular chaotic image encryption methods, particle swarm optimization (PSO) is studied to select the parameters and initial values of chaotic systems so that the chaotic sequence has higher entropy. Different from the other PSO-based image encryption methods, the proposed method takes the parameters and initial values of the chaotic system as particles instead of encrypted images, which makes it have lower complexity and therefore easier to be applied in real-time scenarios. To validate the optimization framework, this paper designs a new image encryption scheme. The algorithm mainly includes key selection, chaotic sequence preprocessing, block scrambling, expansion, confusion, and diffusion. The key is selected by PSO and brought into the chaotic map, and the generated chaotic sequence is preprocessed. Based on block theory, a new intrablock and interblock scrambling method is designed, which is combined with image expansion to encrypt the image. Subsequently, the confusion and diffusion framework is used as the last step of the encryption process, including row confusion diffusion and column confusion diffusion, which makes security go a step further. Several experimental tests manifest that the scenario has good encryption performance and higher security compared with some popular image encryption methods.
Heat Transfer Enhancement through Thermodynamical Activity of H2O/Clay Nanofluid Flow over an Infinite Upright Plate with Caputo Fractional-Order Derivative
Authors: Kayalvizhi J. , Vijaya Kumar A. G. , Öztop Hakan F. , Sene Ndolane , Abu-Hamdeh Nidal H.
Published: August 2022

This paper presents a modelling of nanofluid flow using Caputo fractional derivatives through conservative equations of mass and momentum, and provides an exact solution on un-steady convective flow over a vertical plate with the mass diffusion effect, in association with an energy equation. H2O is the base liquid with clay nanoparticles floating in it in a uniform way. Boussinessq’s approach is used in the momentum equation for pressure gradient. The non-dimensional fluid temperature, species concentration and fluid transport are derived together with Jacob Fourier sine and Laplace transform techniques in terms of exponential decay function, and the inverse is computed further in terms of the Mittag-Leffler function. The impact of various physical quantities is interpreted with the fractional order of the Caputo derivatives. The obtained temperature, transport and species concentration profiles show behaviors for 0 < α < 1, where α is the fractional parameter. The rate of heat and mass transfer coefficients for the significance of physical quantities of interest are also obtained and presented through graphs. The impact of the nanoparticle volume fraction on the flow field is observed. At larger values of the fractional parameter, the velocity, temperature, and concentration distributions grow more quickly. In addition to that, it is found the concentration profiles behave in the opposite way for the volume fraction of nanofluids.
Intelligent Optimization of Switched Reluctance Motor Using Genetic Aggregation Response Surface and Multi-Objective Genetic Algorithm for Improved Performance
Authors: Abunike Chiweta Emmanuel , Okoro Ogbonnaya Inya , Aphale Sumeet S.
Published: August 2022

In this paper, a thorough framework for multiobjective design optimization of switched reluctance motor (SRM) is proposed. Selection of stator and rotor pole embrace coefficients is an essential step in the SRM design process since it influences torque output and torque ripple in SRM. The problem of determining optimal pole embrace is formulated as a multi-objective optimization problem with the objective of optimizing average torque, efficiency and torque ripple, and response surface models were obtained based on the genetic aggregation method. The results obtained by genetic aggregation response surface (GARS) and the non-dominated genetic algorithm (NSGA-II) were validated with the finite element method (FEM) model of the initial SRM. The optimized model displayed better efficiency profile over a wide speed range. The initial and optimized models recorded maximum efficiencies of 85% and 94.05%, respectively, at 2000 rpm. The efficiency values of 93.97–94.05% were achieved for the three pareto optimal candidates. The findings indicate the viability of the suggested strategy and support the use of GARS and NSGA-II as useful methods for addressing SRM key challenges.
Measures for Assessing the Effectiveness of Investments for Electricity and Heat Generation from the Hybrid Cooperation of a Photovoltaic Installation with a Heat Pump on the Example of a Household
Authors: Niekurzak Mariusz , Lewicki Wojciech , Drożdż Wojciech , Miązek Paweł
Published: August 2022

In recent years, one of the key postulates in the European Union’s policy has become the development of renewable energy sources. In order to achieve the desired synergy effect, the idea of combining two selected sources of energy appeared. This article presents a technical and economic analysis of a hybrid connection of a ground source heat pump with a photovoltaic installation. Taking into account the heat demand of the building, a ground heat pump with a catalog nominal heating power of 25 kW was selected. This article presents the problem of the economic profitability of using a hybrid combination of a heat pump and photovoltaic panels in domestic hot water and central heating systems. The justification for the use of such heat sources in these installations is due to global trends and the gradual departure from conventional energy sources such as oil or gas boilers. This paper presents the economic and ecological results of using the pump heat connected together with photovoltaic panels. In the economic analysis, with the assumed installation costs related to the use of the considered heat pump and PV, two parameters commonly used in the investment analysis (static and dynamic) were used, namely, the simple payback period and the net present value of the investment. For the adopted assumptions, the usable area of the facility and the number of years of use were indicated, at which the investment in question is competitive with other alternative investment interest methods and will start to bring tangible benefits. The performed analysis also has measurable environmental benefits in the form of a reduction in carbon dioxide emissions at the level of 2893 kg/year into the atmosphere. The presented solution will help future investors understand the investment profitability mechanism for their households.
Generalized Average Modeling of a Dual Active Bridge DC-DC Converter with Triple-Phase-Shift Modulation
Authors: Rolak Michał , Twardy Maciej , Soból Cezary
Published: August 2022

This paper shows an elaboration of an equivalent electrical circuit of a Dual Active Bridge (DAB) and its application as a versatile tool for steady-states analysis in wide range of operating conditions. This work analyses the converter which is controlled with a coherently defined Triple Phase-Shift (TPS) modulation which allows appropriate switching functions to be written, thus enabling the circuit’s state-space equations to be derived. Due to this approach, a Fourier series expansion may be easily applied to utilize Generalized Averaged Modeling (GAM)—a convenient method for modeling resonant and quasi-resonant power converters. Moreover, this paper shows the utilization of the GAM model higher harmonics’ complex magnitudes to calculate the steady-state power characteristics for bidirectional operation; additionally, a method for a particular state variable waveform signal reconstruction is presented. All the discussed model properites are validated with a 1.5 kW 100 kHz SiC-based DAB prototype.
Guidelines for Determining the Initial Shape and Specifications of High-Speed AFPM Based on Recent Research
Authors: Kang Jae-Beom , Lee Ji-Young , Lee Ji-Heon
Published: August 2022

This paper presents guidelines for determining the initial shape and specifications of a high-speed axial-flux permanent-magnet (AFPM) machine in a hybrid-electric propulsion system in two steps based on previous studies and product review results related to high-speed AFPMs. In the first step, three characteristics to be considered when designing AFPMs were classified as: electromagnetic, thermal, and mechanical. Then, the factors that should be considered in the design process to satisfy each characteristic were organized. In the second step, “the speed–output power” relationship was defined to predict the limits of applying AFPMs to high-speed applications, allowing an estimation of the limits of the speed range that can be used within the proposed output power.
Effect of Leptographium terebrantis on Foliage, New Root Dynamics, and Stemwood Growth in a Loblolly Pine (Pinus taeda L.) Plantation
Authors: Mensah John K. , Sayer Mary Anne S. , Nadel Ryan L. , Duwadi Shrijana , Fan Zhaofei , Carter Emily A. , Eckhardt Lori G.
Published: August 2022

The course of the bark beetle-vectored fungus, Leptographium terebrantis S. J. Barras and T. J. Perry, in stemwood growth loss of declining pines in the southeastern United States was assessed in a 13-year-old loblolly pine (Pinus taeda L.) plantation near Eufaula, Alabama, U.S.A. Using stem inoculation as a surrogate for root infection, we hypothesized that L. terebrantis infection impairs sapwood function and thus limits the tree leaf area (AL), new root production, and stemwood growth. Sterile toothpicks colonized by L. terebrantis at varying inoculum densities was used to elicit host growth responses. In the third year after inoculation, the root pathogen reduced the foliage moisture content, whole-tree leaf area (AL), the ratio of AL to tree sapwood area (AS), and stemwood growth in trees receiving the high inoculation treatment relative to those receiving the low or medium inoculation treatments, or the wound or control treatments after seven months of water deficit. The absence of a similar response to water deficit among trees that were noninoculated, wounded, or inoculated at the low or medium densities suggests that, in the loblolly pine–L. terebrantis pathosystem at our study site, the physiological stress caused by water deficit and the high inoculum density was required for the pathogen to elicit a stemwood growth loss. Thus, in loblolly pine forests of the southeastern United States, where climate and soil conditions yield prolonged periods of physiological stress, the presence of L. terebrantis has the potential to reduce stand volume and widen the gap between the predicted and actual stemwood production.
Variation in Water Uptake Dynamics of Dominant Wood Plants of Pinus taiwanensis Hayata Communities Based on Stable Isotopes
Authors: Wen Linsheng , Peng Yun , Deng Wenping , Liu Yuanqiu , Bai Tianjun , Zou Qin , Liu Xiaojun , Zhang Ling , Jia Guodong
Published: August 2022

Plant community formation is determined by plant competition, while the water uptake depth of vegetation is regarded as a critical factor in maintaining species coexistence under competition. However, the source variation of montane plant water uptake remains poorly understood, especially under the condition of climate change. We introduced stable hydrogen and oxygen isotopes to investigate the water uptake pattern of the trees and shrubs in a Pinus taiwanensis Hayata community in subtropical mountains. The results showed that the main sources of water uptake in plants varied with soil water content, due to variations in annual precipitation distribution. In July and September, under extremely wet conditions, the evergreen conifer species P. taiwanensis and the shrub Eurya muricata mainly absorbed water from the deep soil layer (40–80 cm, more than 70%). By contrast, the deciduous shrub Rhododendron dilatatum largely relied on upper soil water (0–40 cm, 75.4%) in July but the same deep water source in September. In August and the non-growing season (January), when soil moisture content was low, plants preferred surface layer soil water (0–20 cm, above 50%). In October, the soil water in the middle (20–40 cm) and deep layers (40–80 cm) were the main water source of the three plants. However, the plant water sources showed great difference between P. taiwanensis and shrubs in November: P. taiwanensis absorbed more water from the soil surface layers (89.5%), while R. dilatatum mainly took up surface soil water (54.2%) and E. muricata predominantly obtained water from surface soil water (49.6%) and the deep soil layer (39.3%). These findings suggest that the water uptake of dominant woody plants in a P. taiwanensis community has great plasticity, and its water uptake depth varies with soil water content. In addition, these co-existing species generally absorbed water from similar soil layers in the P. taiwanensis community and exhibited a hydrological niche overlap, indicating a very possible competition between species in future water-limited conditions caused by climate change.
Secondary Metabolites Produced by Trees and Fungi: Achievements So Far and Challenges Remaining
Authors: Nawrot-Chorabik Katarzyna , Sułkowska Małgorzata , Gumulak Natalia
Published: August 2022

Secondary metabolites are ubiquitous substances occurring naturally in trees and microorganisms. They are produced in various metabolic pathways which determine their structure and biochemical proprieties. However, the biological functions of many secondary metabolites remain undetermined. Usually, the amounts of secondary metabolites produced by trees under natural conditions are limited, which makes their mass production difficult and not cost-effective. Metabolites occurring naturally in plants, including gymnosperm and angiosperm trees, as well as in fungi, are important biologically active substances used by many industries and in modern medicine. The huge variability and potential of biological activity present in secondary metabolites make it possible to replace most of them with compounds of completely natural origin. The current breakdown of metabolites, together with the most important examples of compounds and their uses, are presented in this overview. The possibility of increasing the number of secondary metabolites in a specific environment through interaction with the most known biotic factors is discussed. The use of in vitro culture for the production of secondary metabolites and their extraction, as well as the possibility of subsequent analysis, are described. The current literature on the metabolites produced by individual species is presented.
Highlighting a New Morphospecies within the Dialium Genus Using Leaves and Wood Traits
Authors: Doucet Robin , Bibang Bengono Gaël , Ruwet Marius , Van De Vreken Isabelle , Lecart Brieuc , Doucet Jean-Louis , Fernandez Pierna Juan Antonio , Lejeune Philippe , Jourez Benoit , Souza Alain , Richel Aurore
Published: August 2022

During inventories of lesser-known timber species in eastern Gabon, a new Dialium morphospecies was discovered. To discriminate it from the two other 2–5 leaflets Dialium species, 25 leaf traits were measured on 45 trees (16 Dialium pachyphyllum, 14 Dialium lopense, 15 Dialium sp. nov.). Nine wood chemical traits, as well as infrared spectra, were also examined on harvestable trees (four Dialium pachyphyllum and four Dialium sp. nov.). This study revealed seven discriminant leaf traits that allowed to create a field identification key. Nine significant differences (five in sapwood and four in heartwood) in terms of wood composition were highlighted. The use of the PLS-DA technique on FT-IR wood spectra allowed to accurately identify the new morphospecies. These results provide strong support for describing a new species in this genus. Implications for sustainable management of its populations are also discussed.
Evaluation of Gas Production, Fermentation Parameters, and Nutrient Degradability in Different Proportions of Sorghum Straw and Ammoniated Wheat Straw
Authors: Wang Jing , Zhang Zhendong , Liu Huihui , Xu Jianfeng , Liu Ting , Wang Cailian , Zheng Chen
Published: August 2022

The purpose of this study was to investigate the optimum proportion of sorghum straw and ammoniated wheat straw in vitro and in vivo to apply in ruminant diets. One-factor and two-factor experimental designs were used in the in vitro tests, with different ratios of sorghum straw to ammoniated wheat straw (S:AWS) of 2:8, 3:7, 4:6, 5:5, 6:4, 7:3, and 8:2 to measure the in vitro total gas production, CH4 production, in vitro dry matter degradability (IVDMD), in vitro organic matter degradability (IVOMD) and in vitro fermentation parameters. Additionally, the nylon bag technique was used to determine the dynamic degradation of these different ratios of mixed feedstuffs for incubating in sheep rumen for 6 h, 12 h, 24 h, and 48 h. The results show that IVDMD, IVOMD, and the molar ratio of propionate were the highest when the ratio of S:AWS was 8:2 (p < 0.05) in vitro; however, this ratio released much more CH4 (p < 0.05). In addition, the degradability of DM, OM, CP, and ash and the effective degradability of DM and CP were the highest when the ratio of S:AWS was 8:2 cultured in sheep rumen for 48 h (p < 0.05). In the in vitro and in situ nylon bag tests, IVDMD, IVOMD, rumen nutrient degradability, and effective degradability of DM and CP increased with the increase in the sorghum straw proportion. In conclusion, the higher the proportion of sorghum straw, the higher the nutrient degradability in vivo and in vitro, but also the higher the emissions of CH4. Therefore, when the ratio of S:AWS is 8:2, ruminants can effectively utilize nutrients in feed.
A Blockchain-Based Framework to Enhance Anonymous Services with Accountability Guarantees
Authors: Buccafurri Francesco , De Angelis Vincenzo , Lazzaro  Sara
Published: August 2022

Anonymous service delivery has attracted the interest of research and the industry for many decades. To obtain effective solutions, anonymity should be guaranteed against the service provider itself. However, if the full anonymity of users is implemented, no accountability mechanism can be provided. This represents a problem, especially when referring to scenarios in which a user, protected by anonymity, may perform illegally when leveraging the anonymous service. In this paper, we propose a blockchain-based solution to the trade-off between anonymity and accountability. In particular, our solution relies on three independent parties (one of which is the service provider itself) such that only the collaboration of all three actors allows for the disclosure of the real identity of the user. In all other cases, anonymity is guaranteed. To show the feasibility of the proposal, we developed a prototype with user-friendly interfaces that minimize the client-side operations. Our solution is then also effective from the point of view of usability.
Association Analysis for Some Biochemical Traits in Wild Relatives of Wheat under Drought Stress Conditions
Authors: Pour-Aboughadareh Alireza , Jadidi Omid , Shooshtari Lia , Poczai Peter , Mehrabi Ali Ashraf
Published: August 2022

In the present study, we estimated genetic diversity and population structure in 186 accessions of Triticum and Aegilops species using 24 simple sequence repeat markers (SSR). Furthermore, an association analysis was performed for antioxidant activities, including guaiacol peroxidase (GPX), ascorbate peroxidase (APX), peroxidase (POX), catalase (CAT), and dry matter (DM) under two control and drought stress conditions. Our findings showed that drought treatment significantly decreased DM, whereas activities of all antioxidant enzymes were increased compared to the control conditions. The results of correlation analysis indicated that, under drought stress conditions, all biochemical traits had a positive and significant association with each other and with dry matter. In the molecular section, the results of the analysis of molecular variance (AMOVA) indicated that the molecular variation within species is more than within them. The dendrogram obtained by cluster analysis showed that grouping the investigated accessions was in accordance with their genomic constitutions. The results of association analysis revealed 8 and 9 significant marker–trait associations (MTA) under control and drought stress conditions, respectively. Among identified MTAs, two associations were simultaneously found in both growing conditions. Moreover, several SSR markers were associated with multiple traits across both conditions. In conclusion, our results could provide worthwhile information regarding marker-assisted selection for the activity of antioxidant enzymes in future breeding programs.
Identification of Alkaline Salt Tolerance Genes in Brassica napus L. by Transcriptome Analysis
Authors: Xu Yu , Tao Shunxian , Zhu Yunlin , Zhang Qi , Li Ping , Wang Han , Zhang Yan , Bakirov Aldiyar , Cao Hanming , Qin Mengfan , Wang Kai , Shi Yiji , Liu Xiang , Zheng Lin , Xu Aixia , Huang Zhen
Published: August 2022

Soil salt alkalization is one major abiotic factor reducing the productivity of crops, including rapeseed, an indispensable oil crop and vegetable. The mechanism studies of alkali salt tolerance can help breed highly resistant varieties. In the current study, rapeseed (B. napus) line 2205 exhibited more tolerance to alkaline salt than line 1423 did. In line 2205, the lesser plasma membrane damage index, the accumulated osmotic solute, and higher antioxidant enzyme activities contributed to alkaline tolerance. A more integrated mesophyll-cell structure was revealed under alkali salt stress by ultrastructure observation in line 2205, which also implied a lesser injury. Transcriptome analysis showed that more genes responded to alkaline salt in line 2205. The expression of specific-response genes in line 1423 was lower than in line 2205. However, most of the specific-response genes in line 2205 had higher expression, which was mainly enriched in carbohydrate metabolism, photosynthetic processes, ROS regulating, and response to salt stress. It can be seen that the tolerance to alkaline salt is attributed to the high expression of some genes in these pathways. Based on these, twelve cross-differentially expressed genes were proposed as candidates. They provide clues for further analysis of the resistance mechanism of rapeseed.
A Comparison of Three Machine Learning Methods for Multivariate Genomic Prediction Using the Sparse Kernels Method (SKM) Library
Authors: Montesinos-López Osval A. , Montesinos-López Abelardo , Cano-Paez Bernabe , Hernández-Suárez Carlos Moisés , Santana-Mancilla Pedro C. , Crossa José
Published: August 2022

Genomic selection (GS) changed the way plant breeders select genotypes. GS takes advantage of phenotypic and genotypic information to training a statistical machine learning model, which is used to predict phenotypic (or breeding) values of new lines for which only genotypic information is available. Therefore, many statistical machine learning methods have been proposed for this task. Multi-trait (MT) genomic prediction models take advantage of correlated traits to improve prediction accuracy. Therefore, some multivariate statistical machine learning methods are popular for GS. In this paper, we compare the prediction performance of three MT methods: the MT genomic best linear unbiased predictor (GBLUP), the MT partial least squares (PLS) and the multi-trait random forest (RF) methods. Benchmarking was performed with six real datasets. We found that the three investigated methods produce similar results, but under predictors with genotype (G) and environment (E), that is, E + G, the MT GBLUP achieved superior performance, whereas under predictors E + G + genotype × environment (GE) and G + GE, random forest achieved the best results. We also found that the best predictions were achieved under the predictors E + G and E + G + GE. Here, we also provide the R code for the implementation of these three statistical machine learning methods in the sparse kernel method (SKM) library, which offers not only options for single-trait prediction with various statistical machine learning methods but also some options for MT predictions that can help to capture improved complex patterns in datasets that are common in genomic selection.
MiR-18a-5p Targets Connective Tissue Growth Factor Expression and Inhibits Transforming Growth Factor β2-Induced Trabecular Meshwork Cell Contractility
Authors: Knox John , Bou-Gharios George , Hamill Kevin J. , Willoughby Colin E.
Published: August 2022

Increased trabecular meshwork (TM) cell and tissue contractility is a driver of the reduced outflow facility and elevation of intraocular pressure (IOP) associated with primary open-angle glaucoma (POAG). Connective tissue growth factor (CTGF) is an established mediator of TM cell contractility, and its expression is increased in POAG due to transforming growth factor β 2 (TGFβ2) signalling. Inhibiting CTGF upregulation using microRNA (miRNA) mimetics could represent a new treatment option for POAG. A combination of in silico predictive tools and a literature review identified a panel of putative CTGF-targeting miRNAs. Treatment of primary human TM cells with 5 ng/mL TGFβ2 for 24 h identified miR-18a-5p as a consistent responder, being upregulated in cells from five different human donors. Transfection of primary donor TM cells with 20 nM synthetic miR-18a-5p mimic reduced TGFβ2-induced CTGF protein expression, and stable lentiviral-mediated overexpression of this miRNA reduced TGFβ2-induced contraction of collagen gels. Together, these findings identify miR-18a-5p as a mediator of the TGFβ2 response and a candidate therapeutic agent for glaucoma via its ability to inhibit CTGF-associated increased TM contractility.
Short-Term Effects of Side-Stream Smoke on Nerve Growth Factor and Its Receptors TrKA and p75NTR in a Group of Non-Smokers
Authors: Stabile Anna Maria , Pistilli Alessandra , Bartolini Desirée , Angelucci Eleonora , Dell’Omo Marco , Di Sante Gabriele , Rende Mario
Published: August 2022

Environmental tobacco smoke remains a major risk factor, for both smokers and non-smokers, able to trigger the initiation and/or the progression of several human diseases. Although in recent times governments have acted with the aim of banning or strongly reducing its impact within public places and common spaces, environmental tobacco smoke remains a major pollutant in private places, such as the home environment or cars. Several inflammatory and long-term biomarkers have been analysed and well-described, but the list of mediators modulated during the early phases of inhalation of environmental tobacco smoke needs to be expanded. The aim of this study was to measure the short-term effects after exposure to side-stream smoke on Nerve Growth Factor and its receptors Tropomyosin-related kinase A and neurotrophin p75, molecules already described in health conditions and respiratory diseases. Twenty-one non-smokers were exposed to a home-standardized level of SS as well as to control smoke-free air. Nerve Growth Factor and inflammatory cytokines levels, as well the expression of Tropomyosin-related kinase A and neurotrophin receptor p75, were analysed in white blood cells. The present study demonstrates that during early phases, side-stream smoke exposure induced increases in the percentage of neurotrophin receptor p75-positive white blood cells, in their mean fluorescent intensity, and in gene expression. In addition, we found a positive correlation between the urine cotinine level and the percentage of neurotrophin receptor-positive white blood cells. For the first time, the evidence that short-term exposure to side-stream smoke is able to increase neurotrophin receptor p75 expression confirms the very early involvement of this receptor, not only among active smokers but also among non-smokers exposed to SS. Furthermore, the correlation between cotinine levels in urine and the increase in neurotrophin receptor p75-positive white blood cells could represent a potential novel molecule to be investigated for the detection of SS exposure at early time points.
A Preliminary Evaluation of the Cultural Appropriateness of the Tuning in to Kids Parenting Program in Germany, Turkey, Iran and China
Authors: Havighurst Sophie S. , Choy Rachel , Ulker Ayca , Otterpohl Nantje , Aghaie Meybodi Fateme , Edrissi Forough , Qiu Chen , Kar-man Shum Kathy , Radovini Alessandra , Hosn Dana A. , Kehoe Christiane E.
Published: August 2022

Background: Parenting interventions based on emotion socialization (ES) theory offer an important theoretically driven approach to improve children’s emotional competence and behavioral functioning. Whether such approaches are effective in different cultural contexts, and whether the methods of delivery used are appropriate and acceptable, is an important empirical question. This paper reports on the preliminary evaluation of an ES parenting intervention, Tuning in to Kids (TIK), in Germany, Turkey, Iran, and China. Pilot studies of TIK have been conducted in each country with mothers of 4–6-year-old children. Method: The current study used qualitative methods with thematic analysis to explore the cultural appropriateness of the program in each site. Results: Culture-specific challenges were found across all sites in changing parents’ beliefs about the value of encouraging children’s emotional expression and supportive emotion discussions. Emotion literacy of parents depended on their access to emotion terms in their language, but also to parents’ experiences with emotions in their family of origin and culture-related beliefs about emotions. Adaptations were required to slow the speed of delivery, to address issues of trust with parents in seeking help, and to provide more opportunities to practice the skills and integrate different beliefs about parenting. Conclusion: While this ES parenting intervention has been developed in a Western cultural context, slight adaptations to the delivery methods (rather than change to the content) appeared to contribute to cultural appropriateness. The next step will be to quantitatively evaluate these adaptations of TIK in the different countries using randomized controlled studies.