With more than 200 species of native Rubus, China is considered a center of diversity for this genus. Due to a paucity of molecular markers, the phylogenetic relationships for this genus are poorly understood. In this study, we sequenced and assembled the plastomes of 22 out of 204 Chinese Rubus species (including varieties) from three of the eight sections reported in China, i.e., the sections Chamaebatus, Idaeobatus, and Malachobatus. Plastomes were annotated and comparatively analyzed with the inclusion of two published plastomes. The plastomes of all 24 Rubus species were composed of a large single-copy region (LSC), a small single-copy region (SSC), and a pair of inverted repeat regions (IRs), and ranged in length from 155,464 to 156,506 bp. We identified 112 unique genes, including 79 protein-coding genes, 29 transfer RNAs, and four ribosomal RNAs. With highly consistent gene order, these Rubus plastomes showed strong collinearity, and no significant changes in IR boundaries were noted. Nine divergent hotspots were identified based on nucleotide polymorphism analysis: trnH-psbA, trnK-rps16, rps16-trnQ-psbK, petN-psbM, trnT-trnL, petA-psbJ, rpl16 intron, ndhF-trnL, and ycf1. Based on whole plastome sequences, we obtained a clearer phylogenetic understanding of these Rubus species. All sampled Rubus species formed a monophyletic group; however, sections Idaeobatus and Malachobatus were polyphyletic. These data and analyses demonstrate the phylogenetic utility of plastomes for systematic research within Rubus. Full article

Non-exhaust road transport emissions in cities contribute to poor air quality and have an impact on human health. This paper presents a new study of particles emitted by tyre wear in real driving conditions and gives their emission factors. The most frequently emitted particles were collected in urban, suburban and road areas. They were identified and analysed physically and chemically. Their level of toxicity is well known. An overall analysis of the measured pollutants was carried out to assess their emission factors in real driving situations. The highest emitting pollutants, considered separately, were found to have high emission factors. The values obtained exceed the Euro standard for vehicles but are below those of vehicles not equipped with particle filters. Significant test analysis confirmed that the inertia of chemical pollutants is homogeneous. Emission factors have also been provided for PM₁₀ and PM_2.5. These results should contribute to the emergence of future regulations of non-exhaust emissions and should help to analyse the exposure-impact relationship for particles from tyre wear. Full article

Neurodegenerative diseases are progressive disorders that affect the central nervous system (CNS) and represent the major cause of premature death in the elderly. One of the possible determinants of neurodegeneration is the change in mitochondrial function and content. Altered levels of mitochondrial DNA copy number (mtDNA-CN) in biological fluids have been reported during both the early stages and progression of the diseases. In patients affected by neurodegenerative diseases, changes in mtDNA-CN levels appear to correlate with mitochondrial dysfunction, cognitive decline, disease progression, and ultimately therapeutic interventions. In this review, we report the main results published up to April 2024, regarding the evaluation of mtDNA-CN levels in blood samples from patients affected by Alzheimer’s (AD), Parkinson’s (PD), and Huntington’s diseases (HD), amyotrophic lateral sclerosis (ALS), and multiple sclerosis (MS). The aim is to show a probable link between mtDNA-CN changes and neurodegenerative disorders. Understanding the causes underlying this association could provide useful information on the molecular mechanisms involved in neurodegeneration and offer the development of new diagnostic approaches and therapeutic interventions. Full article

The successful detection of key components within satellites is a crucial prerequisite for executing on-orbit capture missions. Due to the inherent data-driven functionality, deep learning-based component detection algorithms rely heavily on the scale and quality of the dataset for their accuracy and robustness. Nevertheless, existing satellite image datasets exhibit several deficiencies, such as the lack of satellite motion states, extreme illuminations, or occlusion of critical components, which severely hinder the performance of detection algorithms. In this work, we bridge the gap via the release of a novel dataset tailored for the detection of key components of satellites. Unlike the conventional datasets composed of synthetic images, the proposed Typical Components of Satellites (TYCOS) dataset comprises authentic photos captured in a simulated space environment. It encompasses three types of satellite, three types of key components, three types of illumination, and three types of motion state. Meanwhile, scenarios with occlusion in front of the satellite are also taken into consideration. On the basis of TYCOS, several state-of-the-art detection methods are employed in rigorous experiments followed by a comprehensive analysis, which further enhances the development of space scene perception and satellite safety. Full article

Considering current global climate change, drought stress is regarded as a major problem negatively impacting the growth of soybeans, particularly at the critical stages R3 (early pod) and R5 (seed development). Microbial inoculation is regarded as an ecologically friendly and low-cost-effective strategy for helping soybean plants withstand drought stress. The present study aimed to isolate newly drought-tolerant bacteria from native soil and evaluated their potential for producing growth-promoting substances as well as understanding how these isolated bacteria along with arbuscular mycorrhizal fungi (AMF) could mitigate drought stress in soybean plants at critical growth stages in a field experiment. In this study, 30 Bradyrhizobium isolates and 30 rhizobacterial isolates were isolated from the soybean nodules and rhizosphere, respectively. Polyethylene glycol (PEG) 6000 was used for evaluating their tolerance to drought, and then the production of growth promotion substances was evaluated under both without/with PEG. The most effective isolates (DTB4 and DTR30) were identified genetically using 16S rRNA gene. A field experiment was conducted to study the impact of inoculation with DTB4 and DTR30 along with AMF (Glomus clarum, Funneliformis mosseae, and Gigaspora margarita) on the growth and yield of drought-stressed soybeans. Our results showed that the bioinoculant applications improved the growth traits (shoot length, root length, leaf area, and dry weight), chlorophyll content, nutrient content (N, P, and K), nodulation, and yield components (pods number, seeds weight, and grain yield) of soybean plants under drought stress (p ≤ 0.05). Moreover, proline contents were decreased due to the bioinoculant applications under drought when compared to uninoculated treatments. As well as the count of bacteria, mycorrhizal colonization indices, and the activity of soil enzymes (dehydrogenase and phosphatase) were enhanced in the soybean rhizosphere under drought stress. This study’s findings imply that using a mixture of bioinoculants may help soybean plants withstand drought stress, particularly during critical growth stages, and that soybean growth, productivity, and soil microbial activity were improved under drought stress. Full article

Water intrusion into a building envelope describes the unwanted movement of water or vapor into a building, where it causes damage. Various factors dictate water intrusion category determination and classification. These factors include, but are not limited to, the type and degree of water intrusion, the source and route of the contamination, and exposure time, as well as geographical environmental conditions. This comprehensive research paper looked at the literature and the science to explore the bases for indoor environmental professional (IEP) classification and category determination, but also the science behind the effects of water intrusion on building materials (BM). The efficacy of building materials once degradation has occurred and any accelerating effects impacting the efficiency of building materials and their loss of integrity were closely examined in terms of material microstructural and compositional changes. The damaging effects of moisture and heat on building materials are called hygrothermal damage, which compromises the properties and use of materials. Both aspects of building integrity, i.e., water intrusion and structural deterioration, should be of concern when mitigating and remediating the intrusion of moisture. Previous research on the clarification of water categories for water intrusions is lacking. Past approaches to water classification have lacked universal scientific clarity and understanding. In addition to a need to understand the effects that water category might have on building materials and their corresponding degree of degradation, more science and reviews are needed. The need for proper class and category determination for the remediation of water intrusion within buildings is the first step toward achieving correct mitigation to ensure human health and safety. The possible adverse health effects of water intrusion need focus and cohesion for the determination of categories. We know that the final determination of water categories differs according to the degree of contamination over time and the degree of a given class of water intrusion; however, what role do the route and initial water contamination play in the determination of the category? The following paper aims to provide not only a review of the science but also an elaboration of the category determination process and the degradation effects on building materials which should be considered, as well as possible avenues of scientific research. Full article

Carbon dots (CDs) have emerged as significant fluorescent nanomaterials due to their bright, stable fluorescence, good biocompatibility, facile synthesis, etc. They are widely used in various scientific and practical applications, particularly in combination with mesoporous, florescent, or magnetic nanomaterials to enhance their properties. Recent research has focused on employing CDs and their composites in drug analysis, drug loading, biological imaging, disease diagnosis, and temperature sensing, with a growing interest in their biological and medical applications. In this study, we synthesized blue-fluorescent S, N-co-doped CDs (cys-CDs) using hydrothermal synthesis with L-cysteine and sodium citrate. These resulting cys-CD particles were approximately 3.8 nm in size and exhibited stable fluorescence with a quantum yield of 0.66. By leveraging the fluorescence quenching of the cys-CDs, we developed a rapid and sensitive method for baicalein detection, achieving high sensitivity in the low micromolar range with a detection limit for baicalein of 33 nM. Our investigation revealed that the fluorescence-quenching mechanism involved static quenching and inner-filter effect components. Overall, cys-CDs proved to be effective for accurate quantitative baicalein detection in real-world samples. Full article

Effective management of EEG artifacts is pivotal for accurate neurological diagnostics, particularly in detecting early stages of Alzheimer’s disease. This review delves into the cutting-edge domain of fuzzy logic techniques, emphasizing intuitionistic fuzzy systems, which offer refined handling of uncertainties inherent in EEG data. These methods not only enhance artifact identification and removal but also integrate seamlessly with other AI technologies to push the boundaries of EEG analysis. By exploring a range of approaches from standard protocols to advanced machine learning models, this paper provides a comprehensive overview of current strategies and emerging technologies in EEG artifact management. Notably, the fusion of fuzzy logic with neural network models illustrates significant advancements in distinguishing between genuine neurological activity and noise. This synthesis of technologies not only improves diagnostic accuracy but also enriches the toolset available to researchers and clinicians alike, facilitating earlier and more precise identification of neurodegenerative diseases. The review ultimately underscores the transformative potential of integrating diverse computational techniques, setting a new standard in EEG analysis and paving the way for future innovations in medical diagnostics. Full article

This study aimed to explore the impact of the first two waves of the COVID-19 pandemic on the mental and physical states of sports students from Romania and also to compare the differences according to gender and the type of sport. Initially, in order to collect demographic data and health reports, a cross-sectional survey was developed to evaluate the emotional needs of sports students during the pandemic. After the second wave, the coping strategies used by the participants to fight negative emotions were assessed using the CERQ questionnaire. The results indicate that depression symptoms are the most reported psychological issues among the participants and that there are differences according to gender concerning the cognitive schemas they use in order to reduce the symptoms. Also, it was found that there are differences, corresponding to the type of sport, in choosing adaptive coping mechanisms. Ultimately, it was confirmed that higher levels of hopelessness among sports students are associated with increased vulnerability to substance use, with the correlation between those two indicators being strong. Delving deeper into this relationship can help identify critical points for intervention to prevent substance abuse. At the same time, the dichotomic analysis of the results found as moderators—the gender and the type of sport in decreasing the severity of depression could be an important aspect of the next counseling interventions. Full article

Baccatin III is a crucial precursor in the biosynthesis pathway of paclitaxel. Its main sources are extraction from Taxus or chemical synthesis using 10-deacetylbaccatin III (10-DAB) as substrate. However, these preparation approaches exhibit serious limitations, including the low content of baccatin III in Taxus and the complicated steps of chemical synthesis. Heterologous expression of 10-deacetylbaccatin III-10-O-acetyltransferase (TcDBAT) in microbial strains for biotransformation of 10-DAB is a promising alternative strategy for baccatin III production. Here, the promotion effects of glycerol supply and slightly acidic conditions with a low-temperature on the catalysis of recombinant TcDBAT strain were clarified using 10-DAB as substrate. Taxus needles is renewable and the content of 10-DAB is relatively high, it can be used as an effective source of the catalytic substrate 10-DAB. Baccatin III was synthesized by integrating the extraction of 10-DAB from renewable Taxus needles and in situ whole-cell catalysis in this study. 40 g/L needles were converted into 20.66 mg/L baccatin III by optimizing and establishing a whole-cell catalytic bioprocess. The method used in this study can shorten the production process of Taxus extraction for baccatin III synthesis and provide a reliable strategy for the efficient production of baccatin III by recombinant strains and the improvement of resource utilization rate of Taxus needles. Full article

Transitional streets serve as intermediary spaces between the Central Business Districts (CBDs) and surrounding residential areas, offering diverse functions and activities within urban interiors. However, a practical methodology for accurately classifying these streets has been lacking, due primarily to transitional areas’ spatial constraints and functional complexities. This study leverages Point of Interest (PoI) data from 2023 to develop an innovative methodological framework that addresses these challenges. This framework analyses transitional streets’ functional distribution and typology, employing PoI frequency density and functional type ratios to identify and classify functional zones. It generally delineates eight main types of transitional streets in the CBD of Chongqing, a prototypical hillside city. Utilising advanced data technology from internet maps, this research pioneers new approaches for identifying and analysing the functionality of transitional streets. The findings underscore the effectiveness of PoI data in precisely recognising the functional types of transitional streets, thereby providing a robust theoretical and practical foundation for the in-depth study of transitional streets. Moreover, the results enhance urban spatial planning in hillside cities of China, effectively demonstrating the advantages of PoI data in defining street typology compared to traditional methods. This approach provides a more detailed understanding of urban functional dynamics by allowing for a more nuanced data analysis of street functions. Full article

Coral islands and reefs are formed by the cementation of the remains of shallow water reef-building coral polyps and other reef dwelling organisms in tropical oceans. They can be divided into coral islands, coral sandbanks, coral reefs, and coral shoals, of which, Coral shoals are located below the depth datum and are not exposed even at low tide, and sometimes are distributed at water depths exceeding 30 m. Satellite images with wide spatial–temporal coverage have played a crucial role in coral island and reef monitoring, and remote sensing data with multiple platforms, sensors, and spatial and spectral resolutions are employed. However, the accurate detection of coral shoals remains challenging mainly due to the depth effect, that is, coral shoals, especially deeper ones, have very similar spectral characteristics to the sea in optical images. Here, an optical remote sensing detection method is proposed to rapidly and accurately detect the coral shoals using a deep belief network (DBN) from optical satellite imagery. The median filter is used to filter the DBN classification results, and the appropriate filtering window is selected according to the spatial resolution of the optical images. The proposed method demonstrated outstanding performance by validating and comparing the detection results of the Yinli Shoal. Moreover, the expected results are obtained by applying this method to other coral shoals in the Xisha Islands, including the Binmei Shoal, Beibianlang, Zhanhan Shoal, Shanhudong Shoal, and Yongnan Shoal. This detection method is expected to provide the coral shoals’ information rapidly once optical satellite images are available and cloud cover and tropical cyclones are satisfactory. The further integration of the detection results of coral shoals with water depth and other information can effectively ensure the safe navigation of ships. Full article

The Tibetan plateau, with complex and diverse ecosystems, is an important ecological security barrier to China. However, climate change and the spread of invasive plant species have imperiled the once pristine and diverse ecosystem of the region. To prevent the further spread and control of invasive plants, it is important to delineate the potential distribution patterns of alien invasive plants at the regional scale across Tibet and understand their responses to climate change. Galinsoga parviflora Cav., a member of the family Asteraceae, is an annual herbaceous plant distributed globally as an invasive weed and possesses characteristics that make it highly invasive, such as a strong ability to proliferate and disperse. The species is also known to have an allelopathic effect. There has been no report on the spatial distribution of G. parviflora in Tibet. Using field survey data, we investigated the risk of G. parviflora invasion and its impacts on the ecological safety of Tibet. We employed the MaxEnt model using the R language and SPSS software to optimize and select model parameters and data. We acquired various environmental variables along with current and future climate change scenarios (two carbon emission scenarios, SSP126 and SSP585, for the years 2050 and 2090) to predict the geographic distribution and potential risk areas in Tibet that G. parviflora can invade. The MaxEnt model accurately predicted the distribution of G. parviflora in Tibet with an average AUC of 0.985. The most suitable environmental conditions in which G. parviflora performed the best in Tibet included a mean annual temperature of 6.2–10.0 °C and an elevation range of 2672–3744 m above sea level. Our results indicate that low precipitation during the coldest quarter of the year (mean temperature −2–3 °C) was the most important variable predicting G. parviflora distribution. The results also showed that the species was hardly found when precipitation in the coldest quarter exceeded 155 mm. The current potential invasion risk areas for G. parviflora included the river valleys of central, southeastern, and eastern Tibet. With future climate change scenarios (i.e., SSP126, SSP585), the suitable habitats for G. parviflora distribution will likely shift to northwest regions from the southeast. Particularly under the highest carbon emission scenario (i.e., SSP585), the potential risk area expands more rapidly, and the center of distribution shifts to northwest regions. These findings provide useful information about the current and future changes in G. parviflora distribution in Tibet, which is crucial for the comprehensive and proactive management and control of G. parviflora under future climate change. Full article

The increasing concentration of CO₂ in the atmosphere is a major factor contributing to climate change. CO₂ storage in coal goaf is a convenient, effective, and economical solution. Methods to quickly and effectively evaluate geological conditions are urgently required. The main influencing factors are geological safety, storage potential, economics, and environmental protection; these include 4 aspects, 38 indexes, and 4 index levels that can be quantified using classification levels. We established a geological evaluation model, using analytic hierarchy process (AHP) and weighted interval methods. AHP was used to determine its elements, indicators, and inter-layer relationships, as well as to clarify its structural relationships. The weight interval method is used to evaluate unstable elements, reducing their difficulty, and constant values are used to assign weights of stable elements to increase accuracy. This model was applied to assess the suitability of the goaf in Yaojie mine for geological CO₂ storage. The results revealed that this goaf is an above average CO₂ storage space, which was consistent with previous research. This geological CO₂ storage evaluation model may also be used to assess the CO₂ storage suitability of other coal goafs. Full article

Mesenchymal stromal cell (MSC)-based advanced therapy medicinal products (ATMPs) are being tried in a vast range of clinical applications. These cells can be isolated from different donor tissues by using several methods, or they can even be derived from induced pluripotent stem cells or embryonic stem cells. However, ATMP heterogeneity may impact product identity and potency, and, consequently, clinical trial outcomes. In this review, we discuss these topics and the need to establish minimal criteria regarding the manufacturing of MSCs so that these innovative therapeutics may be better positioned to contribute to the advancement of regenerative medicine. Full article

The increasing availability of SAR images and processing results over wide areas determines the need for systematic procedures to extract the information from this dataset and exploit the enhanced quality of the displacement time series. The aim of the study is to propose a new pre-operational workflow of an A-DInSAR-based land subsidence monitoring and interpretation service. The workflow is tested in Turano Lodigiano (Lombardy region, Italy) using COSMO-SkyMed data, processed using the SqueeSAR™ algorithm, and covering the time span from 2016 to 2019. The test site is a representative peri-urban area of the Po plain susceptible to land subsidence. The results give insight about new value-added products and enable non-expert users to exploit the potential of the interferometric results. Full article

Nanomaterials (NMs) are in high demand for a wide range of practical applications; however, comprehensively understanding the toxicity of these materials is a complex challenge, due to the limited availability of epidemiological evidence on the human health effects arising from workplace exposures. The aim of this work is to assess whether and how urinary metal concentrations could be reliable and useful in NM biomonitoring. In the framework of “NanoExplore Project” [EU LIFE17 Grant ENV/GR/000285], 43 not-exposed subjects and 40 exposed workers were recruited to measure exposure to NMs (PCN and LDSA) in the proximity of the workstations and biological biomarkers (urinary metal concentrations—Aluminum (Al), Silica (Si), Titanium (Ti), and Chromium (Cr); urinary OS biomarkers—TAP, Isop, and MDA). The results showed that Si and Ti were directly associated with NM exposure (both PCN and LDSA), as well as with OS biomarkers, especially in exposed workers. Moreover, the mediation analyses showed that Si could account for about 2.8% in the relationship between LDSA and OS biomarkers, possibly by decreasing OS antioxidant defenses in exposed people. In conclusion, our study provides evidence that occupational exposure to mixtures containing NMs can represent an underestimated hazard for exposed people, increasing the body burden and the oxidative balance. Full article

Arsenic contamination poses a significant public health risk worldwide, with chronic exposure leading to various health issues. Detecting and monitoring arsenic exposure accurately remains challenging, necessitating the development of sensitive detection methods. In this study, we introduce a novel approach using fast-scan cyclic voltammetry (FSCV) coupled with carbon-fiber microelectrodes (CFMs) for the electrochemical detection of As³⁺. Through an in-depth pH study using tris buffer, we optimized the electrochemical parameters for both acidic and basic media. Our sensor demonstrated high selectivity, distinguishing the As³⁺ signal from those of As⁵⁺ and other potential interferents under ambient conditions. We achieved a limit of detection (LOD) of 0.5 μM (37.46 ppb) and a sensitivity of 2.292 nA/μM for bare CFMs. Microscopic data confirmed the sensor’s stability at lower, physiologically relevant concentrations. Additionally, using our previously reported double-bore CFMs, we simultaneously detected As³⁺-Cu²⁺ and As³⁺-Cd²⁺ in tris buffer, enhancing the LOD of As³⁺ to 0.2 μM (14.98 ppb). To our knowledge, this is the first study to use CFMs for the rapid and selective detection of As³⁺ via FSCV. Our sensor’s ability to distinguish As³⁺ from As⁵⁺ in a physiologically relevant pH environment showcases its potential for future in vivo studies. Full article

The need for organizations to increase resilience is still growing, not least because of economic crises, such as the 2007–2009 global financial crisis, the COVID-19 pandemic, and supply shortages in raw material procurement combined with rising commodity costs and energy prices. We use an attention-based view approach as a theoretical lens to investigate the shift in management’s attention due to a crisis, with a particular focus on working capital management (WCM) as a decisive finance tool. In addition, we examine how management’s attention shifts to organizational resilience (OR). We also analyze how managers’ cognitive flexibility (CF), which reflects their ability to anticipate and quickly adapt, moderates the change in attention. By surveying 307 top and middle managers in German small- and medium-sized enterprises, we measure the crisis effect on the shift in managerial attention to WCM and OR. In addition, we measure managers’ CF and examine the contribution of these individual characteristics in the context of WCM and OR. Our mediation model reveals a positive, indirect-only effect of the crisis on the shift in management attention to OR mediated by the shift in management attention to WCM. In addition, our results show that managers’ CF negatively moderates the effect between managerial focus shifts to WCM and to OR. Our study’s results deepen the understanding of the importance of managers’ CF in times of crisis and the impact of CF on sales development, suggesting that managers’ CF may influence the link between the focal characteristics of WCM and OR. Full article

This study extensively analyzed the bacterial information of biofilms and activated sludge in oxic reactors of full-scale moving bed biofilm reactor-integrated fixed-film activated sludge (MBBR-IFAS) systems. The bacterial communities of biofilms and activated sludge differed statistically (R = 0.624, p < 0.01). The denitrifying genera Ignavibacterium, Phaeodactylibacter, Terrimonas, and Arcobacter were more abundant in activated sludge (p < 0.05), while comammox Nitrospira was more abundant in biofilms (p < 0.05), with an average relative abundance of 8.13%. Nitrospira and Nitrosomonas had weak co-occurrence relationships with other genera in the MBBR-IFAS systems. Potential function analysis revealed no differences in pathways at levels 1 and 2 based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) between biofilms and activated sludge. However, in terms of pathways at level 3, biofilms had more potential in 26 pathways, including various organic biodegradation and membrane and signal transportation pathways. In comparison, activated sludge had more potential in only five pathways, including glycan biosynthesis and metabolism. With respect to nitrogen metabolism, biofilms had greater potential for nitrification (ammonia oxidation) (M00528), and complete nitrification (comammox) (M00804) concretely accounted for methane/ammonia monooxygenase (K10944, K10945, and K10946) and hydroxylamine dehydrogenase (K10535). This study provides a theoretical basis for MBBR-IFAS systems from the perspective of microorganisms. Full article

In DCE-MRI, the degree of contrast uptake in normal fibroglandular tissue, i.e., background parenchymal enhancement (BPE), is a crucial biomarker linked to breast cancer risk and treatment outcome. In accordance with the Breast Imaging Reporting & Data System (BI-RADS), it should be visually classified into four classes. The susceptibility of such an assessment to inter-reader variability highlights the urgent need for a standardized classification algorithm. In this retrospective study, the first post-contrast subtraction images for 27 healthy female subjects were included. The BPE was classified slice-wise by two expert radiologists. The extraction of radiomic features from segmented BPE was followed by dataset splitting and dimensionality reduction. The latent representations were then utilized as inputs to a deep neural network classifying BPE into BI-RADS classes. The network’s predictions were elucidated at the radiomic feature level with Shapley values. The deep neural network achieved a BPE classification accuracy of 84 ± 2% (p-value < 0.00001). Most of the misclassifications involved adjacent classes. Different radiomic features were decisive for the prediction of each BPE class underlying the complexity of the decision boundaries. A highly precise and explainable pipeline for BPE classification was achieved without user- or algorithm-dependent radiomic feature selection. Full article