Major Trends Research Articles

Targeting high-potential mineral prospects in the Ezzhiliga region, Moroccan central massif, using spectral data from the ASTER sensor

This research paper introduces a comprehensive methodology for assessing hydrothermal alteration zones and structural complexity in the Ezzhiliga region, situated in the Hercynian Central Massif of Morocco. The approach utilizes ASTER imagery as the primary data source. The main objectives were to identify and analyze these geological features and then create a potential map for mineral exploration by integrating fuzzy logic and fractal concentration area analysis. Band ratios (RBD) and principal component analysis (PCA) were employed to detect and map argillic, phyllic, propylitic, and iron oxide alteration zones. Additionally, structural lineaments were extracted from the PC1 imagery to understand the structural pattern of the survey area. The incorporation of hydrothermal alteration zones and structural lineaments was achieved through the application of a fuzzy logic model, resulting in the generation of a mineral favorability map. The fuzzy logic model was customized to combine hydrothermal alteration and lineaments density maps, effectively eliminating false spectral anomalies induced by various interference factors. This map was then analyzed using the fractal concentration-area (C-A) model, which separated the anomaly from the geological background and generated a final mineral potential map. Analysis of fractal concentration-area was employed to define thresholds with greater precision, enhancing the reliability of mineral prospectivity assessments. Furthermore, laboratory analyses were performed to verify the outcomes of the mineral potential map. The obtained results revealed a significant affinity with the field data and indicated that the highly prospective zones are perfectly limited in spatial extent and generally associated with the contact of the Zaër granitic pluton with the metamorphic host rock, except for the anomaly identified to the southeast of the study area, along a major NE-SW trending fault.

A Review on Soft Exoskeletons for Hand Rehabilitation

Background: How to enhance the quality of life for the elderly has emerged as a key issue in many nations due to the ageing population. Stroke is the most prevalent disease among the elderly; specifically, the hand dysfunction caused by stroke is also a powerful obstacle to the daily life of the elderly. Soft Exoskeletons for Hand Rehabilitation (SEHRs) have become a major trend for the future due to the increasing demand for hand rehabilitation. Objective: To provide a reference for readers in this field by introducing the most recent research developments in the field of SEHR, including their classification and properties. Methods: By reviewing different types of hand rehabilitation exoskeleton research papers and patents, the advantages and disadvantages, differences, and applications of various SEHRs were summarized. Results: According to the driving mode and realizing the function of SEHRs, the structure characteristics of SEHRs are analyzed and compared. The key problems and future development trends of SEHRs were expounded. Conclusion: According to the driving method, the research shows that SEHRs can be divided into Air-Driven Soft Exoskeletons for Hand Rehabilitation (ADSEHRs), Motor-Driven Soft Exoskeletons for Hand Rehabilitation (MDSEHRs), and Hybrid-Driven Soft Exoskeletons for Hand Rehabilitation (HDSEHRs). Future research is required to further optimize the flexibility and adaptability of soft exoskeletons, improve their accuracy and sensitivity, and enhance human-machine interaction with the human hand.

Dynamic Change and Attribution Regarding Fractional Vegetation Coverage in Mengdong River Basin

The situation of rocky desertification in the southwestern part of China is very serious and has been included as one of three major ecological problems. In this study, using Landsat images as the data sources, we estimated the fractional vegetation coverage (FVC) in the Mengdong River Basin in the Hunan Province over the past 40 years, analyzed its spatio-temporal variation characteristics, and explored the driving mechanism (climate and anthropogenic) using the Mann–Kendall, Hurst index, and partial correlation methods. Specifically, the impact of ecological engineering on the recovery of vegetation cover in rocky desertification areas was analyzed and discussed in this study. The results demonstrate the following: (1) The changes in FVC in the study area before and after the rocky desertification management ecological project differed significantly, with a very small change in the rate of change in the mean value of FVC between 1987 and 1999 (<0.1%), while the FVC had a significant linear growth trend between 2000 and 2022 (>0.9%). (2) The Hurst index of FVC ranged from −0.233 to 2.476, with an average value of 0.864. The area with an H value greater than 0.75 accounted for 80.12%, indicating that the future trend in the vast majority of regions will develop in accordance with the current change trend. (3) The average partial correlation coefficients between FVC and precipitation and between FVC and temperature were −0.02 and 0.27, respectively, showing that FVC is more sensitive to temperature than precipitation. The combination of climate change and human activities is the main cause of FVC change. The contributions of climate change (precipitation and temperature) and human activities to FVC variation are about 30% and 70%, respectively. Ecological restoration projects have a significant positive effect on the recovery of vegetation in rocky desertification areas. The results of this study are intended to provide a scientific basis for analyzing the characteristics of vegetation restoration in existing rocky desertification areas and ecological management in future rocky desertification areas.

Half a Century of Research on Posttraumatic Stress Disorder: A Scientometric Analysis.

We conducted a scientometric analysis to outline clinical research on posttraumatic stress disorder (PTSD). Our primary objective was to perform a broad-ranging scientometric analysis to evaluate key themes and trends over the past decades. Our secondary objective was to measure research network performance. We conducted a systematic search in the Web of Science Core Collection up to 15 August 2022 for publications on PTSD. We identified 42,170 publications published between 1945 and 2022. We used CiteSpace to retrieve the co-cited reference network (1978-2022) that presented significant modularity and mean silhouette scores, indicating highly credible clusters (Q = 0.915, S = 0.795). Four major trends of research were identified: 'war veterans and refugees', 'treatment of PTSD/neuroimaging', 'evidence syntheses', and 'somatic symptoms of PTSD'. The largest cluster of research concerned evidence synthesis for genetic predisposition and environmental exposures leading to PTSD occurrence. Research on war-related trauma has shifted from battlefield-related in-person exposure trauma to drone operator trauma and is being out published by civilian-related trauma research, such as the 'COVID-19' pandemic impact, 'postpartum', and 'grief disorder'. The focus on the most recent trends in the research revealed a burst in the 'treatment of PTSD' with the development of Mhealth, virtual reality, and psychedelic drugs. The collaboration networks reveal a central place for the USA research network, and although relatively isolated, a recent surge of publications from China was found. Compared to other psychiatric disorders, we found a lack of high-quality randomized controlled trials for pharmacological and nonpharmacological treatments. These results can inform funding agencies and future research.

Enhanced heat flow assessment in Gulf of Hammamet and Pelagian Sea: Temperature corrections and conductivity adjustments

This study proposes new corrections of formation temperatures combined to correction of formation conductivities to reconstruct the heat flow map of the Gulf of Hammamet-Pelagian Sea, Eastern Tunisia. For that, a new linear Cross-Plot temperature correction approach, based on Bottom Hole Temperatures (BHT) and Drill Stem Temperatures (DST) of 63 drilled boreholes, was applied. In addition, and as temperature is transmitted from the substratum to the top of a stratigraphic column owing to the thermal conductivity, the latter was investigated according to a high appraisal of ±5 m and taking into account porosity variation with depth. The produced corrected thermal conductivity and geothermal gradient allowed to calculate the corrected heat flow in the Gulf of Hammamet – Pelagian Sea. Results show that the corrected geothermal gradient varies between 23 °C/Km and 58 °C/Km with a regional mean of about 39 °C/Km. The corrected heat flow rises from 49.5 to 119 mW/m2 with a regional mean of about 68 mW/m2. Variation of heat flow is dependent of the geodynamic evolution of the area where high heat flows follow folding structures and relatively low heat flows follow major trending faults. The major variations are E-W, N-S and NW-SE in direction following the major structural trends.

Effect of fermentation containers on the taste characteristics and microbiota succession of soy sauce

Modernization of the traditional fermentation industry has been a major trend recently, such as the upgrading of fermentation containers. This study investigated the taste differences and their material basis of soy sauce fermented in tank and pond (SSFT and SSFP), and further explore the key influencing factors of taste. The intensities of umami, kokumi and sour taste in SSFT were weaker than SSFP, which were associated with 9 basic taste-active compounds, including acetic acid, lactic acid, propanedioic acid, citric acid, glutamic acid, alanine, tyrosine, d-galactose and erythritol. Moreover, 270 peptides and amino acid derivatives were potential compounds for taste difference, of which 78 % were more abundant in SSFP. Five bacterial genera (Kocuria, Tetragenococcus, Pediococcus, Staphylococcus, Weissella) and 4 fungal genera (Wickerhamiella, Millerozyma, Candida, Zygosaccharomyces) may be the functional core microbe for flavor differences in SSFT and SSFP. This study will provide theoretical value for quality improvement in the modern large-scale production of soy sauce.

Transformativism and Expressivity in Hegel’s Philosophy of Mind

Abstract According to a major trend in Hegel scholarship, Hegel advocates a McDowell-style transformativist conception of the human mind. Central to this conception is a methodological dualism, according to which phenomena belonging to the rational mind, in contrast to those belonging to non-rational nature, must be accounted for from within the ‘space of reasons.’ In this paper I argue, by contrast, that Hegel rejects methodological dualism. For Hegel, a constitutive aspect of the rational mind is the activity of expression. I show how Hegel’s philosophy of mind adequately accounts for low-level forms of expressivity without appealing to capacities connected to conceptual thought and judgment, and that he does so by drawing on methods similar to those employed within the empirical sciences of his time. Thus, for Hegel, the sphere of the rational mind is broader than the McDowellian space of reasons.

Newspaper Headlines and Intimate Partner Femicide in Portugal

The media’s representation of intimate partner femicides has been contributing to addressing gender-based violence as a structural phenomenon. Aiming to understand which crime elements are valued and how they might contribute to victim blaming, the present study explores the portrayal of intimate partner femicides in Portugal through the analysis of newspaper headlines. The core of the analysis comprises 853 newspaper headlines published between 2000 and 2017, which were subjected to a categorical content analysis. The results suggest two major trends that are aligned with the scope of the two newspapers analyzed. While some headlines offer informative perspectives on crime and its characteristics, the majority tend to sensationalize the narratives, potentially legitimizing violence against women. The results of this study enrich the social and academic debate on the media’s potential influence in preventing and combating gender-based violence. Moreover, by shedding light on the media’s representation of intimate partner femicides, the study reinforces the importance of a broader discussion on the role of journalism in fostering social change.

2022~2023 러시아 영화 주요 경향 연구

This article is an attempt to examine Russian cinema as a whole in 2022-2023. Among the main trends in Russian cinema over the past two years, the first thing to be noted is its relationship to contemporary Russian society and history. Many of the Russian films that received high praise at home and abroad, were selected for prestigious international film festivals, including Cannes and Rotterdam, and were presented at major Russian film festivals or won prizes. In this article, we will focus on Kirill Serebrennikov's The Wife of Chaikovsky, which was selected in competition at the Cannes Film Festival in 2022, The Bullfinch(2023), directed by Boris Hlebnikov, one of the most important auteurs of contemporary Russian cinema, which was the opening film of the 2023 Moscow International Film Festival, Fairy Tail(2022), which had its world premiere at the Rotterdam International Film Festival, by Alexander Sokurov, who is considered a master not only of contemporary Russian cinema but also of world cinema, and finally, The Camel's Wayh, by Vitaly Suslin, who is one of the most Russian filmmakers of his generation and has built a unique body of work based on a very Russian setting. The second major trend in contemporary Russian cinema that I will discuss is the emergence of Russian regional cinema. I will analyze the film Pardon(2023), directed by Ainur Askarov from Bashkortostan, Plague(2023), directed by Yakutian director Dmitry Davydov, one of the most highly regarded films by international critics, and Aita (2023), directed by Yakutian director Stepan Burnashev. Contemporary Russian cinema is characterized by diversity, locality, and the presence of female directors. In other words, after the collapse of the Soviet Union, Russian cinema has achieved unprecedented diversity, and not only central filmmakers centered in Moscow and Petersburg, but also local filmmakers including Yakutia are actively producing works.

Empirical assessment of ChatGPT’s answering capabilities in natural science and engineering

ChatGPT is a powerful language model from OpenAI that is arguably able to comprehend and generate text. ChatGPT is expected to greatly impact society, research, and education. An essential step to understand ChatGPT’s expected impact is to study its domain-specific answering capabilities. Here, we perform a systematic empirical assessment of its abilities to answer questions across the natural science and engineering domains. We collected 594 questions on natural science and engineering topics from 198 faculty members across five faculties at Delft University of Technology. After collecting the answers from ChatGPT, the participants assessed the quality of the answers using a systematic scheme. Our results show that the answers from ChatGPT are, on average, perceived as “mostly correct”. Two major trends are that the rating of the ChatGPT answers significantly decreases (i) as the educational level of the question increases and (ii) as we evaluate skills beyond scientific knowledge, e.g., critical attitude.

The pristine precursor of Andean-type magmatism preserved in magma mingling zones

Intermediate magma compositions have been postulated to be parental to Andean-type magmatism in the recent years. Geochemical and experimental methods have allowed the modelling of a hypothetical parental composition that accounts for the major element trends displayed by Andean-type batholiths. However, natural plutonic examples matching the modelled composition remain lacking, likely due to the predominance of fractionated liquids and cumulates in the batholiths after protracted and large-scale differentiation. Contrary to this, magma mingling zones, a common feature in Andean-type batholiths, are characterised by quenching phenomena, minimising differentiation. In this paper, we present data from intermediate magmatism in the world-class Gerena magma mingling zone in the Seville Sierra Norte batholith (southern Iberia), compositionally equivalent to Andean-type magmatic series. Geochemical data from quenched dark globules of variable scale and the corresponding host granodiorites are contrasted with the bimodal trends displayed by the host batholith. Results suggest that the smaller-scale dark globules have not undergone any significant fractionation. Furthermore, after conducting geochemical modelling we conclude the dark globules represent a composition that could be parental to Andean-type magmas. We propose that magma mingling zones are an optimal place to probe for parental magmas of Andean-type magmatism, particularly those represented in pristine melanocratic, intermediate globules.

Experimental Study on Preparation and Characteristics of Concrete Modified by Construction Waste

With the advancement of urbanization construction, the proportion of construction waste to the total urban waste continues to increase, especially waste concrete. The treatment and reuse of waste concrete is a major trend that poses enormous pressure on environmental protection. This article focuses on the problems in the preparation of recycled aggregates from waste concrete, which has important practical value. This article presents a new type of recycled concrete prepared through surface modification of recycled coarse aggregate and design experiments to change the replacement rate of coarse aggregate. The physical properties of recycled coarse aggregate, workability of fresh concrete, and mechanical properties of recycled concrete are analyzed. The research results indicate the following: (1) Through surface modification, recycled concrete can improve the workability of fresh concrete at a fixed water cement ratio, which can meet the requirements of mixing, transportation, and pouring of fresh concrete. (2) By modifying the surface of recycled aggregates, the strong water absorption performance of recycled aggregates caused by old mortar and surface defects has been reduced. And the modification effect of recycled aggregate improves the hydration process of recycled concrete, making the surface structure dense and further enhancing the strength of recycled concrete. (3) The compressive strength of recycled concrete specifications from construction waste shows a decreasing trend with the increase in coat aggregate replacement rate. The final ratio is as follows: modular dose of 12%, modification time of 90 min, and 20% recycled aggregate content.

COVID-19 disruptions and education in South Africa: Two years of evidence

ABSTRACT This paper provides an overview of learning losses and altered schooling patterns in South Africa during the COVID-19 pandemic (2020–2021). Five major trends emerge from a review of the evidence. These include significant learning losses (38–118% of a year of learning), widened learning inequality, lowered grade repetition rates, increased secondary school enrolments and an unprecedented rise in candidates writing and passing the National Senior Certificate (NSC) examination. School completion significantly increased in 2021 and 2022, spurred by COVID-19 adjusted assessment and promotion practices in Grades 10 and 11. Larger numbers of youth also achieved a NSC pass or Bachelor's pass enabling access to university. With twin pandemic shocks of learning losses and secondary school enrolment increases, remediating losses and realigning progression rules to effective assessment practices should be prioritised.

Trends, Problems, and Solutions from Point Cloud via Non-Uniform Rational Basis Spline to Building Information Modelling: Bibliometric and Systematic Study

Building Information Modelling (BIM) has found applications not only in the planning and designing of new buildings but also in project monitoring, record-keeping, and analyses of existing structures. In addition to its primary application, information modelling spreads to other areas, developing solutions for their specific uses. This study engaged a mixed-method literature review according to the extent of the pool of knowledge for two research steps between three concepts—from point cloud to NURBS and then from NURBS to BIM. In the first step, the keywords point cloud and NURBS were analysed using scientometric methods. In the second step, a systematic analysis of the content of works obtained with the keywords NURBS and BIM is presented, extracting problems and proposed solutions for information transfer technology. The results of a quantitative analysis identified major trends, (1) research is distributed in interdisciplinary and multidisciplinary areas and historical (heritage) modelling is the highlighted one, (2) development of technologies for object surveying, and (3) the application of data in different engineering fields, while a qualitative analysis points at problems in (1) model building, (2) interoperability, and (3) automatization. Solutions such as mixed models, multi-layered models, a mix of formats, or bridging elements (semantics, proto-model) are proposed.

Ensemble methods and semi-supervised learning for information fusion: A review and future research directions

Advances over the past decade at the intersection of information fusion methods and Semi-Supervised Learning (SSL) are investigated in this paper that grapple with challenges related to limited labelled data. To do so, a bibliographic review of papers published since 2013 is presented, in which ensemble methods are combined with new machine learning algorithms. A total of 128 new proposals using SSL algorithms for ensemble construction are identified and classified. All the methods are categorised by approach, ensemble type, and base classifier. Experimental protocols, pre-processing, dataset usage, unlabelled ratios, and statistical tests are also assessed, underlining the major trends, and some shortcomings of particular studies. It is evident from this literature review that foundational algorithms such as self-training and co-training are influencing current developments, and that innovative ensemble techniques are continuing to emerge. Additionally, valuable guidelines are identified in the review for improving research into intrinsically semi-supervised and unsupervised pre-processing methods, especially for regression tasks.

Preliminary Survey on Ethnomedicinal Value of Spontaneous Urban Plants

One of the major global trends of the twenty-first century that has a big impact on our lives is urbanization. By 2050, two-thirds of the world's population, who currently make up half of the population are expected to reside in urban regions. The demands of urban environments can lead to greater poverty and environmental degradation such as poor air and water quality, shortages in water supply, waste-disposal issues, and excessive energy consumption will become worse. Additionally, urbanization encourages the invasion of non-native species by reducing the diversity of plant species, making it difficult to plant growth. Some species, however, exhibit signs of resilience to these challenges and are adaptable to the urban environment. Spontaneous Urban Plants (SUP), also known as "weeds" are frequently found in abandoned urban landscapes. They are neglected as unwelcome, unwieldy, and unkempt, but they thrive in environments where most plants cannot grow. They can grow out of cracks in the sidewalks, in the wall of a garbage ditches, or even in a tiny space inside the walls of houses. This research aims to identify the SUP species with ethnomedicinal values in urban environment. This roadside surveys were conducted to identify SUP species with ethnomedicinal values in 10 urban areas in the Galle district between January and July 2020. Open-ended and semi-structured questionnaire was used to interview a total of 37 people including Ayurveda and traditional medical practitioners, community elders and people experts in plants. The acquired data were verified using the Ayurveda authentic books and reputed journals. A total of 50 plant species of 27 families were identified as SUP. Asteraceae and Amaranthaceae and Fabaceae were reported as the most represented families. The most plant species are used to treat gastrointestinal disorders, followed by respiratory disorders and dermatological conditions. However, ethnomedicinal values of these SUP are yet to be revealed. 
 Keywords: Ethnomedicinal, Spontaneous urban plants, Urbanization, Weed

A novel high energy density single-phase linear piezoelectric motor: design and experiment

The circuit simplification and simple structure of piezoelectric motor have become a major trend at present. Therefore, a novel, miniaturized, single-phase driven piezoelectric motor is proposed. The suggested piezoelectric motor employs a bending vibration mode of the first order, which is inspired by the motion patterns of fish tail fins. First, the motor’s operational principle and structure are explained. By analyzing the relationship between the working frequency and amplitude of the motor and the output power, the key parameters of the motor are determined, and the structure size of the motor is calculated. Next, the FEM model of the stator is utilized to conduct transient analysis in order to examine the movement path of the driving foot. Symmetrical right-diagonal or left-diagonal motions are formed by the driving foot during the first bending vibration, creating oblique elliptical movements. Finally, a prototype is made and its vibration and mechanical characteristics are tested. At a frequency of 15.6 kHz, the motor’s highest speed without any load is measured at 31.2 mm/s. Both forward and backward performance is identical. When the motor is supplied with a voltage of 140 Vpp and a preload of 2 N, it achieves a moving speed of 4.2 mm/s at 15.6 kHz, with an output thrust of around 0.9 N.

Research on coal mining intensity based on the DPSIR-SPA model.

High-intensity mining has become a major trend in future coal mining. However, it will unavoidably worsen the harm done to the natural environment of mining sites by coal mining, which is already prone to doing so. So, how may coal mining intensity (CMI) be decreased? Minimize the harm that coal mining causes to the environment and offer a theoretical basis for protecting the environment in mining sites. In order to achieve this, based on the existing literature on CMI, we first redefine the concept of CMI, analyze its influencing factors, propose an evaluation index system, and introduce the theory of set pair analysis (SPA) to build a quantitative evaluation model of CMI. We then propose an adjustment strategy for the CMI and conduct a verification analysis using the Halagou Coal Mine and Caojiatan Coal Mine as an example. The results show that the Halagou and Caojiatan Coal Mine belong to the higher-intensity mining stage. It is consistent with existing research. Moreover, the development trend of CMI in the Halagou Coal Mine is analyzed in conjunction with the set pair potential theory, and specific measures to reduce CMI are given, from the perspective of coal mining. It provides the basis for the source protection of the ecological environment in the mining area. Theoretically, this study can help both the quantitative assessment of mining intensity and the source protection of the mining ecological environment. Besides, it offers specific guidelines for building environmentally friendly mines.

Collaboration and Competition: A Social Network Analysis of Thailand’s Music Industry

This study quantitatively investigates the collaborative framework and competitive landscape of Thailand’s evolving music industry, driven by technological progress and changing consumer preferences. By examining data obtained from Thailand’s Department of Intellectual Property, specifically 138,868 songs, it explores the complex network of relationships among music creators, artists, and various rights-holders, including those associated with recording, music, melodies, and lyrics. Utilizing social network analysis, this research uncovers a power law distribution in these networks, reflecting a scale-free market configuration. This characteristic is marked by a few dominant players exercising considerable market influence, contrasted with numerous less-interconnected participants. This investigation notes regular patterns of collaboration between artists and different rights-holders. Furthermore, the network of music creators displays small-world properties, with short collaborative distances fostering efficient information exchange and creative synergy. Crucially, this study identifies key influential players instrumental in directing the industry’s major trends, highlighting their role in market concentration. These significant findings will provide critical evidence for informing future policy development aimed at improving efficiency and equity in the digital content industries.

Advancements in Agricultural Technology: A Comprehensive Review of Machine Learning and Deep Learning Approaches for Crop Management and Disease Detection

Traditional agricultural practices often lack personalized guidance for farmers, which leads to poor crop choices, wasteful fertiliser use, and inadequate disease control. As a result, sustainability and productivity decline. In order to address these issues, this review examines the developments in agricultural technology, with a focus on the fusion of deep learning and machine learning techniques. We look at techniques like ensemble modelling, which optimises crop selection and fertiliser consumption depending on soil properties, and advanced image processing methods, which use leaf images to diagnose plant diseases accurately. Our goal in conducting this study is to provide light on how agricultural technology is developing and how it affects contemporary farming methods. We emphasise the major trends, approaches, and developments in the field of agricultural technology by examining a variety of research papers covering many elements of the subject. Our thorough analysis highlights the potential of deep learning and machine learning techniques to transform agricultural disease diagnosis, fertiliser selection, and crop management. With this investigation, we hope to add to the current conversation about using technology to solve the urgent problems facing the agriculture industry and, in the process, open the door for more effective and sustainable farming methods in the future