bluuebunny/crossref_metadata_2025 huggingface dataset:
Profound Concerns about “Profound Autism”: Dangers of Severity Scales and Functioning Labels for Support Needs
Authors: Kapp Steven K.
Published: January 2023

Recently the Lancet published a Commission on the future of care and clinical research of autism, which included a side panel arguing for the adoption of “profound autism”, a term in- tended to describe autistic people who require constant supervision or care, thought to usually have significant intellectual disability, limited or no language, and an inability to advocate for themselves. This state-of-the-art review deconstructs problems with autism sublabels such as “profound autism” and low- and high-functioning labels. It then examines the communicative and cognitive capacities of minimally speaking autistic people, finding that such individuals can communicate (especially with responsive partners) and need nonverbal testing that allows them to demonstrate their potential strengths. It concludes with the ability of minimally speaking autistic people to self-advocate, and the influences of other people to both support and frustrate their communication.
Teacher-Developed Computer Games for Classroom and Online Reinforcement Learning for Early Childhood
Authors: Tárraga-Sánchez María de los Ángeles , Ballesteros-García María del Mar , Migallón Héctor
Published: January 2023

During the recent period of confinement, educational institutions and teachers worked together to provide online teaching to enable students to acquire the competencies of each educational level. Efforts mainly focused on secondary and higher education and, to a lesser extent, on primary education. Although these efforts have been useful, it is important to take advantage of them and continue using both the resources developed and the know-how obtained during this period. In this paper, we present an online education proposal with a focus on preschool education that was initially developed during the lockdown period for students between three and five years old, and which continues to form an important part of the curricular content in current face-to-face teaching. We discuss the adaptation and successful use of this proposal in the post-confinement period, in which a return to face-to-face education has taken place. It is important to note that this proposal is aimed at a generation of students who are already digital natives, and it is necessary to pay attention to both the content and the design of the proposed computer games, in addition to maintaining the motivation of the students. One of the differentiating characteristics of this proposal is that the interactive resources developed here were designed, developed and adapted by the preschool children’s teachers themselves, without requiring computer science skills. The proposed methodology provides dynamic resources that evolve alongside the students. Therefore, our proposal is composed of both the methodology for the development of the computer games of the game-based part of our curricular project, and the project itself. Two examples of this project are presented. We show how the methodology allows the design and adaptation of computer games for specific school groups at specific learning stages.
How Can Social Capital Become a Facilitator of Inclusion?
Authors: Hrabéczy Anett , Ceglédi Tímea , Bacskai Katinka , Pusztai Gabriella
Published: January 2023

Students with special educational needs are a diverse group. Promoting their learning success is particularly challenging, even in practice for inclusive schools. At the same time, parents are often left alone with diagnosis and treatment. Therefore, the focus of our study was on the families of successful students with special educational needs and the networks around their families. Our research question is: What are the differences in social capital between parents of successful students with and without learning, behavioural and emotional disorders, and difficulties (SEN B)? We analysed the survey Value-Creating Education 2020 (n = 1156). Parents of 10-year-old children were asked whether their child needs special education services because of difficulties in learning. We used separate ordinal regression models to examine predictors of academic achievement in the two subsamples of parents of students with and without special educational needs (SEN B). Our results showed that factors supporting success differed between the two groups. Family background and involvement of professional helpers (teachers, psychologists, special education teachers) in child-raising were not among the predictors of academic success for students who need special education services because of learning problems, but the availability of an extensive network of the family had a positive significant effect.
The Use of Mobile Instant Messaging in English Language Teaching: The Case of South Korea
Authors: Chung Sun-Joo , Choi Lee Jin
Published: January 2023

While learning management systems and video conferencing platforms have become a pivotal means for implementing emergency remote learning during the COVID-19 pandemic, the integration of mobile technologies into online teaching has been largely recommended in order to create an interactive educational environment. Focusing on the case of an English Language Program in South Korea, this study investigates the actual use of mobile instant messaging (MIM) applications as a learning aid in online language classrooms and how this was implemented in creating interactive language learning environments during the current outbreak. Based on a questionnaire survey collected from 979 students, it then compares students’ level of perceived satisfaction with their language learning and communication in online language classrooms between the group of students that used MIM during instruction and the group that did not. The discussion presented in this paper provides language educators, school administrators and policymakers at all levels with practical suggestions and ideas to consider, given that our daily communication has become highly dependent on and is increasingly mediated by mobile digital communication technologies and new media.
Methodological Proposal for the Analysis of Urban Mobility Using Wi-Fi Data and Artificial Intelligence Techniques: The Case of Palma
Authors: Salas Pau , Ramos Vicente , Ruiz-Pérez Maurici , Alorda-Ladaria Bartomeu
Published: January 2023

Knowing and modeling mobility in smart city spaces is important for both planning and managing city resources. The optimization of public resources and the improvement of their management are some of the main concerns in the development of sustainable urban development policies. This study proposes the application of several artificial intelligence methodologies to support mobility planning based on data provided by public Wi-Fi infrastructures in the city. Considering that Wi-Fi networks provide high-frequency data about the devices under their coverage radius, three classification techniques are proposed: by frequency of occurrence of the devices, by estimation of the mode of transport, and by estimation of the most common travel routes. As a case study, the city of Palma (Mallorca, Spain), an international tourist destination where mobility is of singular importance, is selected. This study shows the results obtained from a Wi-Fi network with wide coverage that is integrated into the urban space. It provides novel and updatable information on the mobility model of the city by taking advantage of public high-frequency monitoring resources.
Combined DC-Link Fed Parallel-VSI-Based DSTATCOM for Power Quality Improvement of a Solar DG Integrated System
Authors: Satyanarayana P.V.V. , Radhika A. , Reddy Ch. Rami , Pangedaiah B. , Martirano Luigi , Massaccesi Andrea , Flah Aymen , Jasiński Michał
Published: January 2023

In present day power systems, Power Quality (PQ) issues are causing great concern owing to the increased use of power electronic controlled drives and fluctuating and other non-linear loads. This problem is further aggravated by a steady increase in the integration of renewable energy-based Distribution Generation (DG), employing power electronic converters to distribution systems. Custom power devices with suitable control strategies provide an effective solution to these power quality issues. In this work, a typical three-phase distribution system supplying non-linear load and with DG integration is considered. A shunt connected DSTATCOM at PCC of the system is employed to mitigate power quality concerns. Initially, a parallel-VSI based DSTATCOM configuration, employing individual DC-Link and working basically on the principle of current sharing, has been proposed. The analysis is carried out for variable load conditions for PQ enhancement making use of a more effective control theory viz. Instantaneous Real-Reactive Power (IRP) theory for the generation of suitable switching patterns to the individual VSIs of the parallel DSTATCOM. Further, an improvement over the above configuration viz. combined/common DC-Link-fed parallel DSTATCOM is proposed. This configuration has the advantages of minimized sensing elements, reliable operation and low-cost compensation. A similar analysis is carried out for PQ improvement, making use of the same IRP theory with some modifications (known as MIRP theory). The effectiveness of this configuration is established from the simulation results. In all the above cases, the analyses are carried out using MATLAB/Simulink platform and the simulation results are presented in detail. Thus, the proposed parallel VSIs-based DSTATCOM configurations employing suitable control strategies provide effective solutions for power quality issues under varying load conditions in conventional distribution systems.
Experimental Machine Learning Approach for Optical Turbulence and FSO Outage Performance Modeling
Authors: Lionis Antonios , Sklavounos Antonios , Stassinakis Argyris , Cohn Keith , Tsigopoulos Andreas , Peppas Kostas , Aidinis Konstantinos , Nistazakis Hector
Published: January 2023

A laser beam propagating in the free space suffers numerous degradation effects. In the context of free space optical communications (FSOCs), this results in reduced availability of the link. This study provides a comprehensive comparison between six machine learning (ML) regression algorithms for modeling the refractive index structure parameter (Cn2). A single neural network (ANN), a random forest (RF), a decision tree (DT), a gradient boosting regressor (GBR), a k-nearest neighbors (KNN) and a deep neural network (DNN) model are applied to estimate Cn2 from experimentally measured macroscopic meteorological parameters obtained from several devices installed at the Naval Postgraduate School (NPS) campus over a period of 11 months. The data set was divided into four quarters and the performance of each algorithm in every quarter was determined based on the R2 and the RMSE metric. The corresponding RMSE were 0.091 for ANN, 0.064 for RF, 0.075 for GBR, 0.073 for KNN, 0.083 for DT and 0.085 for DNN. The second part of the study investigated the influence of atmospheric turbulence in the availability of a notional FSOC link, by calculating the outage probability (Pout) assuming a gamma gamma (GG) modeled turbulent channel. A threshold value of 99% availability was assumed for the link to be functional. A DNN classification algorithm was then developed to model the link status (On-Off) based on the previously mentioned meteorological parameters.
Rice Disease Identification Method Based on Attention Mechanism and Deep Dense Network
Authors: Jiang Minlan , Feng Changguang , Fang Xiaosheng , Huang Qi , Zhang Changjiang , Shi Xiaowei
Published: January 2023

It is of great practical significance to quickly, accurately, and effectively identify the effects of rice diseases on rice yield. This paper proposes a rice disease identification method based on an improved DenseNet network (DenseNet). This method uses DenseNet as the benchmark model and uses the channel attention mechanism squeeze-and-excitation to strengthen the favorable features, while suppressing the unfavorable features. Then, depth wise separable convolutions are introduced to replace some standard convolutions in the dense network to improve the parameter utilization and training speed. Using the AdaBound algorithm, combined with the adaptive optimization method, the parameter adjustment time reduces. In the experiments on five kinds of rice disease datasets, the average classification accuracy of the method in this paper is 99.4%, which is 13.8 percentage points higher than the original model. At the same time, it is compared with other existing recognition methods, such as ResNet, VGG, and Vision Transformer. The recognition accuracy of this method is higher, realizes the effective classification of rice disease images, and provides a new method for the development of crop disease identification technology and smart agriculture.
Dual-Channel Secure Communication Based on Wideband Optical Chaos in Semiconductor Lasers Subject to Intensity Modulation Optical Injection
Authors: Wang Youming , Huang Yu , Zhou Pei , Li Nianqiang
Published: January 2023

Chaotic optical communication was initially proposed to provide advanced physical layer security for optical communication. Here, we propose and numerically demonstrate an optical chaos communication scheme based on semiconductor lasers subject to intensity modulation optical injection for secure transmission of quadrature amplitude modulation (QAM) messages. In this scheme, two chaotic sources were generated with different modulation parameters and acted as chaotic carriers at the transmitter side, which were subsequently used to drive two receivers in two separate channels. Numerical results demonstrate that this scheme allows for broadband chaos generation and high-quality chaos synchronization can be achieved to simultaneously encrypt two messages for secure communication; a 20 GBaud 16-QAM message was recovered correctly with a transmission distance in standard single mode fiber (SMF) over 120-km, while the other 20 GBaud 64-QAM message was limited to a 20-km fiber transmission distance. The system performance was systematically evaluated by analyzing the bit error ratio (BER) of the recovered message versus the masking coefficient and the transmission distance. Furthermore, our simulations justify the robustness against the mismatch of parameters. Therefore, we hope that this scheme can be experimentally implemented for high-speed chaos communication and secure key distribution.
Data-Driven Fault Early Warning Model of Automobile Engines Based on Soft Classification
Authors: Li Xiufeng , Wang Ning , Lyu Yelin , Duan Yan , Zhao Jiaqi
Published: January 2023

Since automobile engine fault is the main factor leading to a vehicle breaking down, engine fault diagnosis has captured a lot of attention. Fault diagnosis identifies fault types to facilitate maintenance. However, the method of the warning before the fault occurs is more attractive to users and is more challenging. Therefore, this study would like to explore the feasibility of implementing automobile engine fault early warning based on the fault diagnosis model. First, the theoretical method of a fault domain is established, and the state of the engine is regarded as a point in n-dimensional space. The normal or fault of the engine will correspond to different state domains in this space. Second, to diagnose multiple fault types at the same time, an ensemble model based on multiple machine learning methods is established. The probability outputs by the ensemble model measure the distance between the point and each fault domain in the space. Finally, considering the temporal factor, an early warning threshold is established based on the probability, and a fault warning model is established by using the dual probability structure. Comparative experiments show that the proposed method can greatly reduce the calculation time based on ensuring the accuracy of early warning and is suitable for real-time early warning of multiple faults.
Analysis of Congestion Control Mechanisms for Cooperative Awareness in IoV Environments
Authors: Ouladdjedid Lakhdar Kamel , Calafate Carlos Tavares , Kerrache Chaker Abdelaziz , Guellouma Younes
Published: January 2023

Traditional vehicle ad hoc networks (VANETs) have evolved toward the Internet of Vehicles (IoV) during the past ten years with the introduction of 5G communication technology and the growing number of vehicles linked to the Internet. The coexistence of IEEE 802.11p and 5G becomes critical to build a heterogeneous IoV system that benefits from both technologies, being that the IEEE 802.11p standard remains the best option for direct communications and safety-critical applications. The IEEE 1609 standard family and the ETSI ITS-G5 standard family both use the IEEE 802.11p standard as a MAC mechanism. To avoid dangerous situations, vehicles require the periodic exchange of awareness messages. With the increase in vehicle density, the MAC layer will suffer from radio channel congestion problems, which in turn will have a negative impact on the safety application requirements. Therefore, the decentralized congestion control (DCC) mechanism has been specified by ETSI to mitigate channel congestion; this was achieved by adapting transmission parameters such as transmit power and data rate. However, several studies have demonstrated that DCC has drawbacks and suffers from poor performance when the channel load is very high. This paper investigates a new promising DCC technique called transmission timing control (TTC), to reduce the channel load for periodic cooperative awareness. It consists of spreading the transmissions over time to avoid contention on the transmission channel. The objective of the paper is to propose an analytical study to calculate the probability of successful transmission using TTC. Obtained results showed a convergence between the applied experiments and our mathematical model, achieving an error margin of only 5%, which confirms the validity of the equation proposed.
Optimal Feature Selection through Search-Based Optimizer in Cross Project
Authors: Faiz Rizwan bin , Shaheen Saman , Sharaf Mohamed , Rauf Hafiz Tayyab
Published: January 2023

Cross project defect prediction (CPDP) is a key method for estimating defect-prone modules of software products. CPDP is a tempting approach since it provides information about predicted defects for those projects in which data are insufficient. Recent studies specifically include instructions on how to pick training data from large datasets using feature selection (FS) process which contributes the most in the end results. The classifier helps classify the picked-up dataset in specified classes in order to predict the defective and non-defective classes. The aim of our research is to select the optimal set of features from multi-class data through a search-based optimizer for CPDP. We used the explanatory research type and quantitative approach for our experimentation. We have F1 measure as our dependent variable while as independent variables we have KNN filter, ANN filter, random forest ensemble (RFE) model, genetic algorithm (GA), and classifiers as manipulative independent variables. Our experiment follows 1 factor 1 treatment (1F1T) for RQ1 whereas for RQ2, RQ3, and RQ4, there are 1 factor 2 treatments (1F2T) design. We first carried out the explanatory data analysis (EDA) to know the nature of our dataset. Then we pre-processed our data by removing and solving the issues identified. During data preprocessing, we analyze that we have multi-class data; therefore, we first rank features and select multiple feature sets using the info gain algorithm to get maximum variation in features for multi-class dataset. To remove noise, we use ANN-filter and get significant results more than 40% to 60% compared to NN filter with base paper (all, ckloc, IG). Then we applied search-based optimizer i.e., random forest ensemble (RFE) to get the best features set for a software prediction model and we get 30% to 50% significant results compared with genetic instance selection (GIS). Then we used a classifier to predict defects for CPDP. We compare the results of the classifier with base paper classifier using F1-measure and we get almost 35% more than base paper. We validate the experiment using Wilcoxon and Cohen’s d test.
Random Routing Algorithm for Enhancing the Cybersecurity of LEO Satellite Networks
Authors: Fratty Ruben , Saar Yuval , Kumar Rajnish , Arnon Shlomi
Published: January 2023

The recent expansion of networks of low-earth orbit (LEO) satellites such as Starlink, OneWeb, and Telesat and the evolution of communication systems toward B5G and 6G with densely interconnected devices could generate opportunities for various cyber attacks. As the satellite network offers many crucial services to the public and governmental organizations, cyberattacks pose severe risks to the communication infrastructure. In this study, we propose a random routing algorithm to prevent distributed denial-of-service (DDoS) attacks on an LEO satellite constellation network. The routing algorithm utilizes the classical algorithms, i.e., k-DG, k-DS, k-SP, and k-LO, by introducing randomness and selecting one with weighted probability distribution to increase the uncertainty in the algorithm. The study shows that the proposed random routing algorithm improves the average and median cost of the attacker against DDoS attacks while maintaining the functionality of the network. The algorithm is optimized by formulating a Bayesian optimization problem. In addition to providing an additional level of uncertainty in the routing, there is an improvement of 1.71% in the average cost and 2.05% in the median cost in a typical scenario. The algorithm causes the network to be robust to cyber attacks against LEO Satellite Networks (LSNs), however, similar to any other defensive measures, it reduces the network’s goodput.
Conversion Electrode and Drive Capacitance for Connecting Microfluidic Devices and Triboelectric Nanogenerator
Authors: Zhu Zhiyuan , Zeng Fan , Pu Zhihua , Fan Jiyu
Published: January 2023

Microfluidics is a technique that uses channels of tiny sizes to process small amounts of fluid, which can be used in biochemical detection, information technology, and other fields. In the process of microfluidic development, there are many problems that need to be solved urgently. Many microfluidic systems require the support of external devices, which increases the construction cost, and the electronic interface technology is not mature. A triboelectric nanogenerator (TENG) can harvest mechanical energy and turn it into electrical energy. It has been greatly developed now and is widely used in various fields. Nowadays, many studies are committed to the study of TENGs and microfluidic systems. The microfluidics device can be combined with a TENG to convert fluid mechanical signals into electrical signals for transmission. Meanwhile, TENGs can also act as a high-voltage source to drive microfluidic motion. In this paper, we reviewed the development of microfluidics and related technologies of microfluidic systems in conjunction with TENGs and discussed the form of electronic interface between microfluidic systems and TENG devices.
DC-AC Converter with Dynamic Voltage Restoring Ability Based on Self-Regulated Phase Estimator-DQ Algorithm: Practical Modeling and Performance Evaluation
Authors: Hasan Kamrul , Othman Muhammad Murtadha , Meraj Sheikh Tanzim , Rahman Md. Siddikur , Lipu Molla Shahadat Hossain , Kotsampopoulos Panos
Published: January 2023

A self-regulated phase estimator (SRPE)-based DQ algorithm for a DC-AC converter with dynamic voltage restoring (DVR) ability is presented in this paper. When compared to the conventional phase-locked loop (PLL), the provided controller can significantly reduce phase distortions and low-order harmonics from the load voltage while attaining quicker dynamic response. Furthermore, the fundamental attribute of the load voltage allows the integrated DC-AC converter to operate at a consistent frequency eliminating frequency oscillations. The SRPE is utilized primarily in the DQ control theory as the reference voltage generator which can compensate for the grid voltage. SRPE has good band-pass filtering properties and a mathematically simple structure that can thoroughly attenuate voltage imbalance and has quick dynamic response. The SRPE has been made to be frequency-adaptive using a damping factor and robust grid frequency estimation. The SRPE can maintain the fundamental frequency at 50 Hz and keep the total harmonic distortions (THD) within the 5% limit even during grid disruptions. The DC-AC converter and SRPE-DQ’s stability are thoroughly examined. The experiment is carried out to show the efficacy of the suggested complete control system. There are also comparative simulation studies to show the benefits of the suggested technique. The results reveal that the suggested approach can immediately identify and correct for any grid voltage imbalance while also assisting in maintaining the constant voltage at the load side despite voltage sag/swell and distortions.
A Method for Reducing the Instability of Negawatts Considering Changes in the Behavior of Consumers
Authors: Takai Koichi , Tamura Yuto , Shinomiya Norihiko
Published: January 2023

Negawatt trading is expected to improve energy efficiency via the prediction of peak demands and power-saving requests. However, the amount of power saved by consumers is not stable. The accurate prediction of demands and making appropriate requests with respect to power saving are difficult obstacles that need to be overcome in order to attain useful negawatt trading processes. To increase the accuracy of predictions and requests, earlier research suggests some methods or linear problems. On the other hand, the investigation of factors that affect consumption is important for correcting the current instability. In this research study, weather changes including temperature, time passing, and the consciousness of consumers are considered as important factors against electricity demands. In this paper, we propose a behavioral model of consumers using weather data. By using this behavioral model, the effectiveness of the suggested methods in earlier research for improving negawatt trading and the uncertainty of negawatts caused by weather changes is investigated.
Mozambique: Country Profile
Authors: Cambaza Edgar
Published: January 2023

Mozambique is a Southern African tropical country; it forms a 4330 km coastline on the Indian Ocean side. It is one of the continent’s five former Portuguese colonies, with the economy relying mainly on agriculture and mining.
Obesity Is Associated with Increased F2-Isoprostanes and IL-6 in Black Women
Authors: Saleem Mohammad , Kastner Paul , Mehr Pouya , Milne Ginger , Ishimwe Jeanne , Park Jennifer , Shibao Cyndya , Kirabo Annet
Published: January 2023

Obesity affects over 40% of the adult population and is a major risk factor for morbidity and mortality due to cardiovascular disease. Black women have one of the highest prevalences of obesity, insulin resistance, hypertension, and cardiovascular events in the US. We previously found that free radical-mediated lipid peroxidation contributes to IL-6 production in dendritic cells leading to inflammation and hypertension. Thus, we hypothesized that F2-isoprostanes (F2-IsoPs), products and biomarkers of endogenous lipid peroxidation, contribute to increased inflammation and IL-6 production among obese Black women. We studied a total of 88 obese Black women of age 42.0 ± 9.8 years, weight 102 ± 16 kg, and body mass index (BMI) 37.68 ± 5.08. Systolic and diastolic blood pressure were 124 ± 14/76.2 ± 9.9 mmHg, heart rate was 68.31 ± 10.26 beats/min, and fasting insulin was 15.0 ± 8.7 uU/mL. Plasma F2-IsoPs were measured using gas chromatography/negative ion chemical ionization mass spectrometry (GC/NICI-MS). Plasma cytokines, including IL-6, IL-8, IL-10, IL-1β, TNF-a, and C-reactive proteins were measured using multiplex Luminex technology. Anthropometric measurements were performed using dual-energy X-ray absorptiometry. Using Pearson’s correlation analysis, we found that BMI was positively correlated with plasma F2-IsoPs, while inversely correlated with insulin sensitivity in obese Black women. Further, F2-IsoPs were positively correlated with inflammatory marker IL-6 levels while negatively correlated with anti-inflammatory marker IL-10. In addition, we found that plasma F2-IsoPs levels were significantly associated with reduced insulin sensitivity. These results suggest that F2-IsoPs may be associated with obesity-induced cardiovascular risk in Black women by increasing the production of inflammatory cytokine IL-6 and decreasing the production of anti-inflammatory IL-10.
Exploring Neogene Marine Diatomites in Western Crete: A New Source-Rock Candidate with Hydrocarbon Generation Potential?
Authors: Telemenis Dimosthenis , Makri Vagia-Ioanna , Manoutsoglou Emmanouil , Bellas Spyridon
Published: January 2023

Diatomites are sedimentary rocks rich in siliceous algae, mainly diatoms, and are evident in Greece mainly in Neogene successions. Despite their significance and worldwide potential as source rocks for hydrocarbons, little is known about them in the wider area of Greece, limited in their biostratigraphic characteristics and industrial use. This study assesses for the first time the Neogene diatomites in Western Crete and focuses on their source rock quality and hydrocarbon generation potential on top of their stratigraphic characteristics. The studied synthetic outcrop is of the Miocene age and is located in the Apokoronas sedimentary basin, in the Chania province. It is subdivided into four subsections reaching heights of 13 m. It has a total documented, visible extend of 90–100 m and presents adequate thickness in relation to other reported diatomitic occurrences in Crete. A SEM study and bulk sampling of 28 samples has been carried out on this outcrop and geochemical analysis has been conducted by means of a Rock-Eval 6 pyrolysis to facilitate the understanding of hydrocarbon potential. Stratigraphic analysis supports the establishment of system tracts (ST), with transgressive ones (TST) illustrated by fining-upward sequences including highstands (HST). At the top, a final coarsening-upwards sequence suggests a regressive sequence (RST) most probably related to the Messinian Salinity Crisis (MSC) event. Total organic carbon (TOC, %wt.) values are found to reach 3.4% in the diatomites, while siltstone/mudstone interlayers encounter lower TOC (%wt.), yet with exceptions reaching TOC levels as high as the diatomaceous facies. Overall, Rock-Eval pyrolysis shows that organic matter from the studied cross sections is immature with the hydrocarbon generation potential ranging from poor to excellent. The kerogen type is proved to be type III with poor to almost good quality. This suggests the presence of a prolific diatomaceous source rock in Western Crete demonstrating a high significance for the offshore hydrocarbon exploration in the Eastern Mediterranean that could potentially be related to the offshore Western and Southern Crete E&P-awarded blocks.
Electrochemical Advanced Oxidation Processes Using Diamond Technology: A Critical Review
Authors: Brosler Priscilla , Girão Ana V. , Silva Rui F. , Tedim João , Oliveira Filipe J.
Published: January 2023

Re-evaluation of conventional wastewater treatment processes is of paramount importance to improve the overall quality of our aquatic environment. Electrochemical Advanced Oxidation Processes (EAOPs) are the most promising alternative methods with application in wastewater treatment facilities since in situ electrogenerated oxidant agents degrade and mineralize a wide range of water pollutants. Boron-doped diamond (BDD) technology has proven its excellency in the anodic oxidation (AO) of different pollutants. In this work, we describe the use of a systematic literature review (SLR) methodology and a bibliometric analysis tool for the assessment of a representative sample of work (hundreds of publications) concerning the synergism between AO using BDD technology and other oxidation methods. One section of the discussion relates to different techniques used to enhance the AO performance of BDD technology, namely persulfate radicals or ozone and photoelectrocatalysis, whereas the second one considers Fenton-based reactions. A standard synergism effect occurs between AO using BDD technology and the add-ons or the Fenton-based methods, resulting in the enhancement of the degradation and mineralization efficiencies. The future of EAOPs using BDD technology must include renewable energy sources to self-sustain the overall process, and further research on the subject is mandatory to enable the effective acceptance and application of such processes in wastewater remediation facilities.
Changes in Phyllosphere Microbial Communities of Pinus tabuliformis after Infestation by Bursaphelenchus xylophilus
Authors: Jiang Yong , Liu Jiaying , Liang Shichu , Zhu Wenxu , Li Hui
Published: January 2023

Phyllosphere microbial communities have an important role in plant growth and resistance to pathogen infection and are partially influenced by leaf characteristics. Pinewood nematode, Bursaphelenchus xylophilus, is one of the greatest threats to pine trees and is spreading all over the world. However, studies on the resistance of plant–microbe interactions to pathogens during the nematode’s pathogenesis and the relationships of leaf chemical characteristics caused by pinewood nematode and phyllosphere microbial communities are limited. In this study, different stages of Pinus tabuliformis that were healthy or infected with B. xylophilus-associated leaf characteristics and phyllosphere bacterial and fungal communities were compared. These results demonstrated that soluble sugar and starch contents decreased based on the extent of infection. Phyllosphere microbial community changes potentially caused by B. xylophilus infection of P. tabuliformis and the fungal community compositions of healthy P. tabuliformis trees (Ya) were clearly different from diseased P. tabuliformis trees at an early stage of B. xylophilus infection (Yb) and P. tabuliformis trees in the last stage of B. xylophilus infection (Yc), particularly along the first coordinate axis. According to a linear discriminant effect size (LEfSe) analysis, the biomarker species in the phyllosphere of Yb were Acidobacteria, Deinococcus-Thermus, and Patescibacteria, while those in the phyllosphere of Ya were Proteobacteria, Aureobasidium, Dictyosporium, Alternariaster, Knufia, Microstroma, and Naganishia. Particularly at the end of PWD (pine wilt disease) infection, the majority of microbial taxa tended to co-exclude rather than co-occur with PWD infection. The result of a canonical correlation analysis (CCA) showed that the chemical properties of leaves, such as carbon and nitrogen, have significant impacts on phyllosphere microbial communities. These results expanded the possible connections between the phyllosphere communities and plant health.
Nutritional Assessment and Comparison of the Composition of Oil Extracted from Argan Nuts Collected from a Plantation and Two Natural Forest Stands of ARGAN Trees
Authors: Sabiri Chaimaa , Tazi Bouchra , Maata Nadia , Rahim Souad , Taki Hassan , Bennamara Ahmed , Saad Lhoussaine , Derouiche Abdelfettah
Published: January 2023

Argan oil (AO), extracted from the argan tree’s fruits, is principally composed of mono-unsaturated fatty acids, polyphenols, tocopherols, and sterols. This unique chemical composition is likely to be responsible for its beneficial effects. The argan tree (Argania spinosa) grows endemically in the southwest of Morocco. This study aimed to evaluate the chemical composition of three types of argan oil from three geographical locations: argan oil extracted from argan nuts collected from a plantation (Casablanca, AOC) and two forest stands of argan trees growing naturally in their native environment of the south-west of Morocco ((regions of Essaouira (AOE) and Taroudant (AOT)). The composition of the three oils corresponds to the known composition of argan oil in terms of fatty acids and unsaponifiable fraction. The chemical analyses revealed that the argan oil extracted from the plantations (AOC) is significantly richer in linoleic acid, linolenic acid, and tocopherols compared to the oil from the two natural stands (AOE and AOT) of argan trees. These results suggest that it is possible to facilitate an assisted migration of the argan tree outside its natural area into sites exposed to sea spray without affecting the quality of its argan oil.
Impact of Former Peat Extraction Field Afforestation on Soil Greenhouse Gas Emissions in Hemiboreal Region
Authors: Samariks Valters , Lazdiņš Andis , Bārdule Arta , Kalēja Santa , Butlers Aldis , Spalva Gints , Jansons Āris
Published: January 2023

The reduction of greenhouse gas (GHG) emissions and climate change mitigation are global issues. Peatlands in Europe are widely distributed in the Nordic–Baltic region, and Baltic countries are some of the largest peat suppliers for horticulture in Europe. However, there is no sustainable substitute for peat in the horticulture industry. Therefore, it is necessary to identify suitable re-cultivation types for former peat extraction fields, because knowledge about the effect of re-cultivation on annual carbon and GHG budgets is limited. Ecosystem GHG (CO2, CH4, N2O) exchange measurements, environmental parameter assessment and sampling in the study were conducted in a hemiboreal vegetation zone for 24 consecutive months in former peat extraction fields with different re-cultivation management strategies (land use types). The aim of the study was to assess the influence of diverse re-cultivation management strategies on the GHG emissions of former peat extraction fields. The most suitable re-cultivation management is afforestation with Scots pine (Pinus sylvestris) in order to obtain the lowest annual CO2eq values and ensure additional carbon sequestration in living tree biomass. The developed linear mixed-effect models showed a good model fit (R2CO2 = 0.80, R2CH4 = 0.74) for the analyzed land use types, and thus can be used for CO2 and CH4 emissions estimation.
Comparison of the Biomass and Dendrometric Parameters of Norway Spruce with Its Different Representations in Young Stands at Lower Altitudes in the Czech Republic
Authors: Novosadová Kateřina , Kadlec Jiří , Kománek Martin , Pokorný Radek
Published: January 2023

In forestry, it is still common to plant the seedlings of and cultivate Norway spruce (Picea abies L. Karst) at lower altitudes; however, the climatic change that has been occurring increases evaporative demands in these areas. As a result, the spruce evidently suffers from drought, withers and loses its power to grow, thus, influencing stem thickness and tree-height growth, as well as biomass production. Therefore, the growth and biomass production of young (5-, 15- and 25-year-old) Norway spruce stands at these altitudes (i.e., from 200 to 500 m a.s.l.) was surveyed, as a case study, across the Training Forest Enterprise “Masaryk Forest” Křtiny. There, 48 stands with a varied representation of spruce (i.e., up to 30%, 31%–60%, 61%–90% and over 91%) were analyzed. In each stand, 12 trees were sampled across all social status classes (i.e., sub-dominant, co-dominant and dominant) in detail. Basic dendrometric parameters (such as the total tree height, height of the crown base and stem diameter at breast height) and the amount of the above-ground tree organ biomass (i.e., stem, branches and needles) were investigated. Based on the trends found in the biomass production here and climate change predictions, we recommend that Norway spruce be cultivated only in zones from an altitude of ca 400 m a.s.l., with an annual precipitation of 700 mm and an average annual temperature of 7 °C, and its percentage representation in the stand be no more than 30%.
Heating Rate during Thermal Modification in Steam Atmosphere: Influence on the Properties of Maple and Ash Wood
Authors: Milić Goran , Todorović Nebojša , Veizović Marko , Popadić Ranko
Published: January 2023

This study aimed to compare two thermal modification (TM) schedules—with short and long heating phases—and their influence on the properties of maple (Acer pseudoplatanus L.) and ash (Fraxinus excelsior L.) wood. Two TM runs were conducted in industrial conditions (open system, steam atmosphere; substantially longer method compared to the processes usually described in the literature), with the same peak phase (200 °C, 3 h), but with different heating rates—slow (1.1 °C/h) and fast (2.5 °C/h). The results revealed that both TMs significantly reduced hygroscopicity and swelling of wood, but the influence of slow heating rate—through prolonged exposure of wood to relatively high temperatures—on dimensional stability was more pronounced. The modulus of elasticity, compressive strength and Brinell hardness remained mostly unchanged after TM (except for fast-modified maple), while the modulus of rupture was strongly reduced by TM in both species. It is assumed—at least in the case of maple wood—that a combination of initial moisture content above 8% and fast heating rate during TM can cause more intensive degradation of wood polymers. Relatively small differences in colour between slow- and fast-modified wood were found. The results confirmed the hypothesis that the heating phase is an important part of the TM schedule, and it can directly affect (together with peak temperature and time) certain wood properties.
Operational Analysis of Grapple Yarding in New Zealand: A Case Study of Three Mechanized Harvesting Operations
Authors: Visser Rien , Harrill Hunter , Obi Okey Francis , Holmes Luke
Published: January 2023

The New Zealand forest industry has increased its use of swing yarders when harvesting on steep slopes. Swing yarders can more readily operate with grapple carriages, both mechanical and motorized, in comparison to tower yarders. Especially when coupled with mechanized felling, grapple yarding has led to improved productivity and safety. The effective use of grapple yarding is dependent on the level of knowledge of the working capability of the machines. This productivity study analyzed the operational capability of grapple yarding at three different harvest sites in North Island, New Zealand. The swing yarders were the T-Mar 650, T-Mar 550, and Madill 124 models. Parameters including average piece size, extraction distance, turn volume and the number of pieces were recorded for each cycle, as well as the level of bunching, with a minimum of 125 cycles, were measured at each site. The average delay-free cycle time for the three sites ranged between 2.8 and 3.7 min, which is very fast compared to yarder operations using chokers. Productivity ranged from 50 to 55 tons per productive machine hour. Extraction distance, piece size and stem presentations significantly influenced productivity. Stem presentation, especially bunching, across the cutover influenced the mean payload per yarding cycle resulting in higher productivity. In addition to providing productivity capability information at three case study sites, the analyses linked stand and terrain parameters such as tree size and extraction distance with production variability. Managing variability is critical to achieving consistently higher rates of production efficiency.
Development of Measuring Device for Diameter at Breast Height of Trees
Authors: Li Shangyang , Fang Luming , Sun Yuanjing , Xia Lei , Lou Xiongwei
Published: January 2023

Diameter at breast height (DBH) is the main metric for standing tree growth measurements. Developing fast and efficient measurement devices for measuring DBH is of great values in forest resource surveys. In this paper, we propose a new tree diameter measurement instrument developed using self-reset displacement sensor, which is equipped with a Personal Computer (PC) terminal to enable the measurement, transmission, storage, and analysis of tree diameters in one. The measurements showed an overall bias of 1.44% and an accuracy of 97.35% compared to the caliper, a conventional diameter measuring instrument. The overall bias was −0.52% compared to the diameter tape, and the measurement accuracy was 98.43%. Compared to the conventional devices, the proposed device is small and easy to carry, the measurement efficiency is significantly improved, and the measurement data can be directly derived for analysis. Compared with related electronic measuring instruments, this proposed device has the advantages of small volume, easy operation, large measurement range, and wider applicability.
Modeling Productivity and Estimating Costs of Processor Tower Yarder in Shelterwood Cutting of Pine Stand
Authors: Papandrea Salvatore F. , Stoilov Stanimir , Angelov Georgi , Panicharova Tanya , Mederski Piotr S. , Proto Andrea R.
Published: January 2023

Cable-based yarding technology has had a long tradition on steep slopes in Europe, and the new implementation of yarding functions in recent decades favored operational efficiency and lower extraction costs. The main goal of this study was to evaluate the performance of the Syncrofalke 3t truck-mounted Processor Tower Yarder (PTY) on steep terrain, in coniferous forests managed with the shelterwood system. In particular, the aim was to determine PTY productivity and costs, with attention to parameters that could increase PTY effectiveness. The study was carried out in the Sredna Gora Mountains, Central Bulgaria, in pure Scots pine stand, with trees of average DBH = 34 cm and height = 22 m. The study was carried out in six corridors with 120 work cycles of tree extraction up the hill, 28° (53%). The mean productivity of PTY was 15.20 m3 per productive machine hour (PMH) and 12.29 m3 per scheduled machine hour (SMH) and was mainly influenced by the productivity of the yarder unit. Under the given conditions, the performance of PTY significantly increased if more than one tree (at least two trees) were attached and extracted per yarder cycle, since the productivity of the processor was approximately twice that of the yarder. The gross costs of the studied PTY were calculated at 297.48 EUR PMH−1 and 16.17 EUR m−3. The variable costs (75%) predominate in the net costs distribution, followed by the fixed costs (15%) and the labor costs (10%). The time, productivity and cost results obtained showed the high efficiency and level of integration of PTY operations in order to achieve economic efficiency of logging in montane pine forest managed in a shelterwood system.
Polyphenol-Rich Extract of Fermented Chili Pepper Alleviates Insulin Resistance in HepG2 Cells via Regulating INSR, PTP1B, PPAR-γ, and AMPK Pathways
Authors: Wang Tao , Li Meiqi , Cai Shengbao , Zhou Linyan , Hu Xiaosong , Yi Junjie
Published: January 2023

Fermented Capsicum frutescens L. is a well-known traditional food ingredient in China with a variety of potential nutritional functions due to the increased content of polyphenolic compounds during the fermentation process. This study aimed to investigate the ameliorative effect of fermented chili peppers (FCP) on insulin resistance and the potential mechanism of action. HepG2 cells were treated with 5 × 10−6 mol/L insulin for 12 h to establish the insulin resistance model. The results showed that the ethanol extract of FCP (1 mg/mL), rather than non-FCP extract, significantly increased glucose consumption in insulin-resistant HepG2 cells, which was at least partly attributed to an increase in polyphenolic compounds after fermentation, including kaempferol-3-O-rutinoside, caffeic acid, kaempferol-3-O-glucoside, luteolin, and apigenin. Molecular docking analysis suggested that these five significantly increased polyphenolic compounds in FCP could partially and effectively interact with the key amino acid residues of four key insulin resistance-related receptors (INSR, PTP1B, PPAR-γ, and AMPK). In conclusion, the fermentation process enhanced or even conferred a pronounced anti-insulin resistance effect on chili peppers, and the increased polyphenolic compounds in chili pepper had synergistic effects in modulating the INSR, PTP1B, PPAR-γ, and AMPK pathways to regulate the destruction of glucose consumption.