bluuebunny/crossref_metadata_2025 huggingface dataset:
Cerebrovascular dysregulation and postoperative cognitive alterations after carotid endarterectomy
Authors: Sándor Ágnes Dóra , Czinege Zsófia , Szabó András , Losoncz Eszter , Tóth Krisztina , Mihály Zsuzsanna , Sótonyi Péter , Merkely Béla , Székely Andrea
Published: June 2024

There are controversial data about the effect of carotid endarterectomy regarding postoperative cognitive function. Our aim was to analyze the effect of cerebral tissue saturation monitored by near-infrared spectroscopy (NIRS) on cognitive function. Perioperative data of 103 asymptomatic patients undergoing elective carotid surgery under general anesthesia were analyzed. Preoperatively and 3 months after the operation, MMSE (Mini Mental State Examination) and MoCA (Montreal Cognitive Assessment) tests were conducted. For cerebral monitoring, NIRS was used, and the lowest rSO2 value and the degree of desaturation were calculated. Cognitive changes were defined as one standard deviation change from the preoperative test scores, defined as postoperative neurocognitive decline (PNCD) and cognitive improvement (POCI). PNCD was found in 37 patients (35.92%), and POCI was found in 18 patients (17.47%). Female gender, patients with diabetes, and the degree of desaturation were independently associated with PNCD. The degree of desaturation during the cross-clamp period negatively correlated with the change in the MoCA scores (R =  − 0.707, p = 0.001). The 15.5% desaturation ratio had 86.5% sensitivity and 78.8% specificity for discrimination. For POCI, a desaturation of less than 12.65% had 72.2% sensitivity and 67.1% specificity. POCI was associated with lower preoperative MOCA scores and a lower degree of desaturation. We found a significant relation between the change of postoperative cognitive function proven by the MoCA test and cerebral tissue saturation during the clamping period in patients undergoing carotid endarterectomy.
Minocycline Abrogates Individual Differences in Nerve Injury-Evoked Affective Disturbances in Male Rats and Prevents Associated Supraspinal Neuroinflammation
Authors: O’Brien Jayden A. , Austin Paul J.
Published: June 2024

Chronic neuropathic pain precipitates a complex range of affective and behavioural disturbances that differ markedly between individuals. While the reasons for differences in pain-related disability are not well understood, supraspinal neuroimmune interactions are implicated. Minocycline has antidepressant effects in humans and attenuates affective disturbances in rodent models of pain, and acts by reducing neuroinflammation in both the spinal cord and brain. Previous studies, however, tend not to investigate how minocycline modulates individual affective responses to nerve injury, or rely on non-naturalistic behavioural paradigms that fail to capture the complexity of rodent behaviour. We investigated the development and resolution of pain-related affective disturbances in nerve-injured male rats by measuring multiple spontaneous ethological endpoints on a longitudinal naturalistic foraging paradigm, and the effect of chronic oral minocycline administration on these changes. Disrupted foraging behaviours appeared in 22% of nerve-injured rats – termed ‘affected’ rats – and were present at day 14 but partially resolved by day 21 post-injury. Minocycline completely prevented the emergence of an affected subgroup while only partly attenuating mechanical allodynia, dissociating the relationship between pain and affect. This was associated with a lasting downregulation of ΔFosB expression in ventral hippocampal neurons at day 21 post-injury. Markers of microglia-mediated neuroinflammation were not present by day 21, however proinflammatory microglial polarisation was apparent in the medial prefrontal cortex of affected rats and not in CCI minocycline rats. Individual differences in affective disturbances following nerve injury are therefore temporally related to altered microglial morphology and hippocampal neuronal activation, and are abrogated by minocycline.

Graphical Abstract
Trajectories of Satisfaction with Life Following a Collective, Critical Life Event and Their Relationship with Sociodemographic Factors and Internal Migration: The Example of the German Reunification 1989/90
Authors: Hahm Stefanie , Altweck Laura , Schmidt Silke , Ulke Christine , Fleischer Toni , McLaren Thomas , Speerforck Sven , Schomerus Georg , Beutel Manfred E. , Brähler Elmar , Muehlan Holger
Published: June 2024

There are considerable interindividual differences in adjustment processes in satisfaction with life (SWL) following critical life events. We focused on a collective life event, the German reunification in 1989/90, which prompted fundamental changes in the political, social, and economic conditions to investigate the heterogeneity of short- and long-term trajectories of SWL and their association with sociodemographic factors and internal migration. Using data (short-term: 1990–1994, long-term: 1990–2019) from the German Socioeconomic Panel (N = 5548), we applied growth mixture modelling with categorical time for short-term and continuous (quadratic) time for long-term trajectories. Multinomial logistic regression was used to examine associations of the trajectories with internal migration (West German (reference)/East German non-migrants, East-West/West-East migrants), baseline characteristics (sex, age, education, marital status, employment status, household income) and changes (becoming not employed, becoming divorced/separated, change in household income). The best models indicated four classes both long- and short-term, with the majority showing high stable SWL (86.7% (short-term) vs. 62.3% (long-term)); other classes were ‘improvement’ (2.5%, vs. 16.4%), ‘decline-improvement’ (5.2% vs. 9.4%), and ‘decline’ (5.6% vs. 11.9%). For short-term trajectories, East German non-migrants and East-West migrants were more likely to show unstable trajectories. Long-term, both East German non-migrants and East-West migrants had higher odds of increasing SWL, whereas West-East migrants had higher chances for decline-improvement. Differential associations with baseline sociodemographic characteristics and changes thereof were found. The study highlights distinct SWL trajectories following the collective event of German reunification. These trajectories vary based on short- versus long-term perspectives, sociodemographic background, and internal migration patterns.
GPU-based key-frame selection of pulmonary ultrasound images to detect COVID-19
Authors: Torti Emanuele , Gazzoni Marco , Marenzi Elisa , Leporati Francesco
Published: June 2024

In the last decades, technological advances have led to a considerable increase in computing power constraints to simulate complex phenomena in various application fields, among which are climate, physics, genomics and medical diagnosis. Often, accurate results in real time, or quasi real time, are needed, especially if related to a process requiring rapid interventions. To deal with such demands, more sophisticated approaches have been designed, including GPUs, multicore processors and hardware accelerators. Supercomputers manage high amounts of data at a very high speed; however, despite their considerable performance, their limitations are due to maintenance costs, rapid obsolescence and notable energy consumption. New processing architectures and GPUs in the medical field can provide diagnostic and therapeutic support whenever the patient is subject to risk. In this context, image processing as an aid to diagnosis, in particular pulmonary ultrasound to detect COVID-19, represents a promising diagnostic tool with the ability to discriminate between different degrees of disease. This technique has several advantages, such as no radiation exposure, low costs, the availability of follow-up tests and the ease of use even with limited resources. This work aims to identify the best approach to optimize and parallelize the selection of the most significant frames of a video which is given as the input to the classification network that will differentiate between healthy and COVID patients. Three approaches have been evaluated: histogram, entropy and ResNet-50, followed by a K-means clustering. Results highlight the third approach as the most accurate, simultaneously showing GPUs significantly lowering all processing times.
A systematic review of peer-reviewed gender literature in sustainability science
Authors: Frank Elisabeth , Mühlhaus Rike , Mustelin Katinka Malena , Trilken Esther Lara , Kreuz Noemi Katalin , Bowes Linda Catharine , Backer Lina Marie , von Wehrden Henrik
Published: June 2024

We conducted a systematic review of the available peer-reviewed literature that specifically focuses on the combination of sustainability and gender. We analyzed the existing peer-reviewed research regarding the extent to which gender plays a role in the empirical literature, how this is methodologically collected and what understanding of gender is applied in those articles. Our aim is to provide an overview of the current most common fields of research and thus show in which areas gender is already being included in the sustainability sciences and to what extent and in which areas this inclusion has not yet taken place or has only taken place to a limited extent. We identified 1054 papers that matched our criteria and conducted research on at least one sustainable development goal and gender research. Within these papers (i), the overall number of countries where lead authors were located was very high (91 countries). While the majority of lead authors were located in the Global North, less than a third of the articles were led by authors located in the Global South. Furthermore, gender is often just used as a category of empirical analysis rather than a research focus. We were able to identify (ii) a lack in coherent framing of relevant terms. Often no definition of sustainability was given, and only the sustainability goals (SDGs or MDGs) were used as a framework to refer to sustainability. Both gender and sustainability were often used as key words without being specifically addressed. Concerning the knowledge types of sustainability, our expectation that system knowledge dominates the literature was confirmed. While a problem orientation dominates much of the discourse, only a few papers focus on normative or transformative knowledge. (iii) Furthermore, the investigated literature was mainly contributing to few SDGs, with SDG 5 ‘Gender Equality’ accounting for 83% of all contributions, followed by SDG 8 ‘Decent Work and Economic Growth’ (21%), SDG 3 ‘Good Health and Well-being’ (15%) and SDG 4 ‘Quality Education’ (12%). We were additionally able to identify seven research clusters in the landscape of gender in sustainability science. (iv) A broad range of diverse methods was utilized that allow us to approximate different forms of knowledge. Yet within different research clusters, the spectrum of methodologies is rather homogeneous. (v) Overall, in most papers gender is conceptualized in binary terms. In most cases, the research is explicitly about women, running the risk that gender research in sustainability sciences grows into a synonym for women's studies.
Topographic and climatic effects on Pinus halepensis s.l. growth at its drought tolerance margins under climatic change
Authors: Sarris Dimitrios , Christodoulakis Dimitrios
Published: June 2024

Under global warming, drought will reduce productivity of Pinus halepensis s.l. (subspecies halepensis and brutia) and cause a retreat from its rear edge distribution (latitudinal/elevational) in the Mediterranean. To test whether topography can influence this scenario, we studied for approximately 40 years the growth of six natural pine stands in water-limited habitats on the islands of Zakinthos and Samos (eastern Mediterranean Greece), and determined the critical moisture sources that drove pine growth. Dominant pines were selected with no permanent water sources under contrasting moisture conditions created by topography (“wet”-gulley/valley vs. “dry”-upslope habitats). The responses of P. halepensis s.l. to drought under a moderate and a worst case scenario were tested, projected under global warming (approx. − 25% and 40% in annual precipitation compared to 1961–1990 average). Our results show that “wet” habitat pines had higher productivity under normal to wet climate. However, the more precipitation declined, “wet” habitat tree growth was reduced at a significantly faster rate, but also showed a faster recovery, once rainfall returned. Thus, Pinus halepensis s.l. populations in gullies/valleys, may be more drought resilient and less likely to retreat towards higher elevation/latitudes under global warming, compared to pines on dry upslope sites. Under moderate drought, both ecosystems relied on deeper moisture pools supplied by rainfall of the previous 3–6 years (including the year of growth). However, valley/gully habitat pines on significantly deeper soils (and probably on deeper heavily weathered bedrock), appeared to utilize surface moisture from winter/spring rainfall more efficiently for survival and recovery. Thus, deep soils may provide the key “buffer” for pine survival in such ecosystems that could act as potential refugia for P. halepensis s.l. under climate change.
The emerging role of robotics in plastic and reconstructive surgery: a systematic review and meta-analysis
Authors: Awad Laura , Reed Benedict , Bollen Edward , Langridge Benjamin J. , Jasionowska Sara , Butler Peter E. M. , Ponniah Allan
Published: June 2024

The role of robotics has grown exponentially. There is an active interest amongst practitioners in the transferability of the potential benefits into plastic and reconstructive surgery; however, many plastic surgeons report lack of widespread implementation, training, or clinical exposure. We report the current evidence base, and surgical opportunities, alongside key barriers, and limitations to overcome, to develop the use of robotics within the field. This systematic review of PubMed, Medline, and Embase has been conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PROSPERO (ID: CRD42024524237). Preclinical, educational, and clinical articles were included, within the scope of plastic and reconstructive surgery. 2, 181, articles were screened; 176 articles met the inclusion criteria across lymph node dissection, flap and microsurgery, vaginoplasty, craniofacial reconstruction, abdominal wall reconstruction and transoral robotic surgery (TOR). A number of benefits have been reported including technical advantages such as better visualisation, improved precision and accuracy, and tremor reduction. Patient benefits include lower rate of complications and quicker recovery; however, there is a longer operative duration in some categories. Cost presents a significant barrier to implementation. Robotic surgery presents an exciting opportunity to improve patient outcomes and surgical ease of use, with feasibility for many subspecialities demonstrated in this review. However, further higher quality comparative research with careful case selection, which is adequately powered, as well as the inclusion of cost-analysis, is necessary to fully understand the true benefit for patient care, and justification for resource utilisation.
Regulating the sharing economy: The effects of day caps on short- and long-term rental markets and stakeholder outcomes
Authors: Gauß Patrick , Gensler Sonja , Kortenhaus Michael , Riedel Nadine , Schneider Andrea
Published: June 2024

Home sharing platforms have experienced a rapid growth over the last decade. Following negative publicity, many cities have started regulating the short-term rental market. Regulations often involve a cap on the number of days a property can be rented out on a short-term basis. We draw on rich data for short-term rentals on Airbnb and for the long-term rental market to examine the impact of short-term rental regulations with a day cap on various stakeholders: hosts, guests, the platform provider, and residents. Based on a difference-in-differences design, we document a sizable drop in Airbnb activity. Interestingly, not only targeted hosts (i.e., hosts with reservation days larger than the day cap), but also non-targeted hosts reduce their Airbnb activity. The reservation days of non-targeted hosts decrease between 26.27% and 51.89% depending on the treatment. Targeted hosts experience a similar decline. There is, nevertheless, significant non-compliance: more than one third of hosts do not comply with enacted short-term rental regulations. Additional analyses show that few properties are redirected from short-term rental to long-term rental use and that there is no significant drop in long-term rents. Drawing on a theoretical model, we tie the estimated effects to changes in stakeholders’ welfare: Regulations significantly reduce the welfare of hosts, and the loss ranges between 46.30% and 9.02%. The welfare loss of the platform provider is proportional to the loss of the hosts. Welfare of guests decreases moderately ranging between 4.5% to 4.1%. The welfare of residents increases minimal. These results question the effectiveness and desirability of the studied short-term rental regulations.
Weighted Breaths: Exploring Biologic and Non-Biologic Therapies for Co-Existing Asthma and Obesity
Authors: Pilkington Albert W. , Buragamadagu Bhanusowmya , Johnston Richard A.
Published: June 2024

Purpose of Review

To discuss the effectiveness of biologics, some of which comprise the newest class of asthma controller medications, and non-biologics in the treatment of asthma co-existing with obesity.

Recent Findings

Our review of recent preliminary and published data from clinical trials revealed that obese asthmatics respond favorably to dupilumab, mepolizumab, omalizumab, and tezepelumab, which are biologics currently indicated as add-on maintenance therapy for severe asthma. Furthermore, clinical trials are ongoing to assess the efficacy of non-biologics in the treatment of obese asthma, including a glucagon-like peptide-1 receptor agonist, a Janus kinase inhibitor, and probiotics.

Although many biologics presently indicated as add-on maintenance therapy for severe asthma exhibit efficacy in obese asthmatics, other phenotypes of asthma co-existing with obesity may be refractory to these medications. Thus, to improve quality of life and asthma control, it is imperative to identify therapeutic options for all existing phenotypes of obese asthma.
Bioaerosol Exposures and Respiratory Diseases in Cannabis Workers
Authors: Eidem Tess , Nordgren Tara , Hernandez Mark
Published: June 2024

Purpose of Review

This review investigates occupational inhalation hazards associated with biologically derived airborne particles (bioaerosols) generated in indoor cannabis cultivation and manufacturing facilities.

Recent Findings

Indoor cannabis production is growing across the US as are recent reports of respiratory diseases among cannabis workers, including occupational asthma morbidity and mortality. More information is needed to understand how bioaerosol exposure in cannabis facilities impacts worker health and occupational disease risk.

Preliminary studies demonstrate a significant fraction of airborne particles in cannabis facilities are comprised of fungal spores, bacteria, and plant material, which may also contain hazardous microbial metabolites and allergens. These bioaerosols may pose pathogenic, allergenic, toxigenic, and pro-inflammatory risks to workers. The absence of multi-level, holistic bioaerosol research in cannabis work environments necessitates further characterization of the potential respiratory hazards and effective risk prevention methods to safeguard occupational health as the cannabis industry continues to expand across the US and beyond.
Lipoprotein (a)-Related Inflammatory Imbalance: A Novel Horizon for the Development of Atherosclerosis
Authors: Qin Ting , Ma Tian-Yi , Huang Kang , Lu Shi-Juan , Zhong Jiang-Hua , Li Jian-Jun
Published: June 2024

Purpose of Review

The primary objective of this review is to explore the pathophysiological roles and clinical implications of lipoprotein(a) [Lp(a)] in the context of atherosclerotic cardiovascular disease (ASCVD). We seek to understand how Lp(a) contributes to inflammation and arteriosclerosis, aiming to provide new insights into the mechanisms of ASCVD progression.

Recent Findings

Recent research highlights Lp(a) as an independent risk factor for ASCVD. Studies show that Lp(a) not only promotes the inflammatory processes but also interacts with various cellular components, leading to endothelial dysfunction and smooth muscle cell proliferation. The dual role of Lp(a) in both instigating and, under certain conditions, mitigating inflammation is particularly noteworthy.

This review finds that Lp(a) plays a complex role in the development of ASCVD through its involvement in inflammatory pathways. The interplay between Lp(a) levels and inflammatory responses highlights its potential as a target for therapeutic intervention. These insights could pave the way for novel approaches in managing and preventing ASCVD, urging further investigation into Lp(a) as a therapeutic target.
Effect of hot water maceration, rehydration, and soft tissue presence on 3D geometry of bone
Authors: Bittner-Frank Martin , Strassl Andreas , Unger Ewald , Hirtler Lena , Kainberger Franz , Windhager Reinhard , Moscato Francesco , Benca Emir
Published: June 2024

Purpose

In forensic medicine, maceration is often essential for examining bone surfaces, serving purposes such as identifying cut marks, making geometric measurements, and determining the victim’s age. While hot water maceration removes soft tissue effectively, it is known to cause bone surface shrinkage. This raises the question of whether this effect is permanent or if it can be partially reversed through rehydration, considering the presence of soft tissue.

Methods

Computed tomography (CT) scans were conducted on the radii of 20 paired human anatomic forearm specimens. Subsequently, the radii were extracted, macerated in 60 °C water, CT-scanned in an air environment, rehydrated, re-implanted into the forearms, and CT-scanned again.

Results

Maceration resulted in a mean shrinkage of 0.12 mm on the outer bone surface. This shrinkage was nearly fully recoverable for the diaphysis after rehydration and accounting for soft tissue surrounding the bone. In contrast, the epiphysis showed permanent shrinkage, likely due to the loss of small bone fragments. Analysis of the inner bone surface indicated a smaller effect, but with significant standard deviations, especially for the epiphysis, possibly related to the less well-defined nature of the inner bone surface.

Conclusion

The epiphyseal surface of hot water-macerated bone will, on average, be approximately 0.15 mm deflated and cannot retain the original surface. On the other hand, the diaphyseal surface is less affected and can be nearly completely restored after rehydration and accounting for soft tissue surrounding the bone.
Top-down and bottom-up coupling effects of subsidies on recipient ecosystems
Authors: Osakpolor Stephen E. , Manfrin Alessandro , Leroux Shawn J. , Schäfer Ralf B. , McLeod Anne M.
Published: June 2024

A subsidy can directly enter a recipient ecosystem by either being consumed or being recycled to the nutrient pool with both pathways causing multiple indirect and potentially conflicting effects. Subsidy pathways are prone to anthropogenic stressors, which can impact the relative strength of the recycling and direct consumption fluxes. Current studies have mainly focused on a single coupling pathway, limiting our knowledge of subsidy effects on recipient ecosystems. We derive a series of models to predict the relative and interactive effects between consumption and recycling subsidy coupling pathways on the biomass and functions of a recipient ecosystem. We solved the models for analytical equilibria, and compared model predictions with and without each subsidy pathway. Our results show that the direct consumption and recycling coupling pathways of subsidies interact antagonistically, as the feedbacks between both pathways led to lower stocks and functions of the recipient ecosystem than a model which omits these feedbacks. These subsidy effects are consistent for each trophic level of the recipient ecosystem. Our models also predicted that consumption and recycling pathways of subsidies had differential effects on the recipient ecosystem. Recycling coupling pathway always led to equal or higher stocks and functions across recipient ecosystem trophic levels, whereas consumption couplings had alternating positive and negative effects depending on trophic level and characteristic of a trophic cascade. We suggest that future empirical and theoretical research on subsidies should consider various coupling pathways to provide a more mechanistic understanding of the effects of subsidies.
Factors associated with the adjustment of typically developing siblings from single-incidence, multiple-incidence and non-autism spectrum disorders families
Authors: Şengül Erdem Hatice , Şengül Avşar Asiye
Published: June 2024

This study investigated the broader autism phenotype (BAP) in mothers and siblings and the mothers’ stress and perceived support levels as factors affecting typically developing siblings’ adjustment by introducing the number of children with autism spectrum disorders (n-ASD) as a factor. The sample consisted of 25 families with multiple-incidence autism spectrum disorder (ASD) children (multiplex families), 38 families with single-incidence ASD children (simplex families), and 46 families with non-ASD children. The data were collected via mothers by the Autism-Spectrum Quotient, Family Support Scale, Questionnaire on Resources and Stress, Social Communication Questionnaire, and Strengths and Difficulties Questionnaire. ANOVA, Kruskal-Wallis H-test, and multiple linear regression analysis were used to analyze the data. According to the findings, siblings and mothers’ BAP, maternal stress, and perceived support levels significantly differed depending on the n-ASD, and the n-ASD was a significant predictor of both siblings’ problem behaviors and prosocial behaviors. These findings were discussed, and limitations and suggestions were included.
The role of minimal residual disease and serum free light chain ratio in the management of multiple myeloma
Authors: Zhu Long-Ying , Hu Qi-Lei , Zhang Liang , Li Zuo-Jie
Published: June 2024

Multiple myeloma (MM) denotes a cancerous growth characterized by abnormal proliferation of plasma cells. Growing evidence suggests that the complexity in addressing MM lies in the presence of minimal residual disease (MRD) within the body. MRD assessment is becoming increasingly important for risk assessment in patients with MM. Similarly, the levels of serum free protein light chain and their ratio play a crucial role in assessing the disease burden and changes in MM. In this paper, we review and explore the utilization of MRD and serum free light chain ratio in the treatment of MM, delving into their respective characteristics, advantages, disadvantages, and their interrelation.
Predicting properties of nodes via community-aware features
Authors: Kamiński Bogumił , Prałat Paweł , Théberge François , Zając Sebastian
Published: June 2024

This paper shows how information about the network’s community structure can be used to define node features with high predictive power for classification tasks. To do so, we define a family of community-aware node features and investigate their properties. Those features are designed to ensure that they can be efficiently computed even for large graphs. We show that community-aware node features contain information that cannot be completely recovered by classical node features or node embeddings (both classical and structural) and bring value in node classification tasks. This is verified for various classification tasks on synthetic and real-life networks.
Unveiling the secretome of Penicillium fuscoglaucum JAM-1 for efficient dual substrate degradation and waste valorization
Authors: Joshi Namrata , Grewal Jasneet , Stasiuk Robert , Drewniak Lukasz , Pranaw Kumar
Published: June 2024

In the pursuit of cost-effective and superior enzymes crucial for the efficient hydrolysis of diverse lignocellulosic biomasses, filamentous fungi have emerged as key candidates for bioprospecting endeavors. In our exploration for potent lignocellulosic biomass degraders, we have identified a strain of Penicillium fuscoglaucum JAM-1, showcasing multipurpose hydrolase capabilities in its secretome. During fermentation, P. fuscoglaucum JAM-1 effectively utilized rapeseed cake (RSC), resulting in improved enzymatic activities, including xylanase (612 U/gds), β-glucosidase (264 U/gds), endoglucanase (102 U/gds), FPase (21.3 U/gds), and exo-polygalacturonase (49.17 U/gds), as compared to pine sawdust (PSD). Secretome profiling revealed a protein abundance totaling 435 and 120 proteins during RSC and PSD utilization, respectively. The major component of carbohydrate-active enzymes (CAZymes) consists of cellulose-degrading proteins, including endoglucanases (GH5, GH7), β-glucosidases (GH1, GH3, GH17), and cellobiohydrolases (GH6, GH7). Correspondingly, hemicellulose-degrading enzymes were present, encompassing endo-1,4-xylanase (GH10), α/β-galactosidase (GH27, GH35, GH36), α/β-mannosidases (GH38, GH2, GH47, GH5), and α-l-arabinofuranosidase (GH43, GH62, GH51, GH54) and carbohydrate-active auxiliary activities enzymes, such as AA9 (formerly known as GH61) lytic polysaccharide monooxygenase (LPMO). Upon application to fruit waste, the crude enzyme demonstrated higher saccharification potential compared to commercial cellulase (Cellic CTec2). Specifically, the crude enzyme yielded 565 mg/g of reducing sugar within 72 h, outperforming Cellic CTec2, which yielded 352 mg/g under identical conditions. A comprehensive comparative analysis of enzyme workings, activities, and secretome profiling underscores P. fuscoglaucum JAM-1 as a potent cellulase producer, showcasing its potential to boost lignocellulose biodegradation. These findings highlight the practical applications of the P. fuscoglaucum JAM-1 in various industrial processes, suggesting its role as a valuable candidate for further exploration and exploitation in biotechnological applications.

Graphical abstract
Remote sensing for assessing the impact of forest fire severity on ecological and socio-economic activities in Kozan District, Turkey
Authors: Ibrahim Sa’ad , Kose Mustafa , Adamu Bashir , Jega Idris Mohammed
Published: June 2024

Monitoring the ecological and socioeconomic impacts of wildfires using traditional approaches requires significant financial resources, time, and sampling expertise. However, not only are resources scarce, but the spatial and temporal extent of forest fires can also make it impractical to assess large areas over time. Thus, fire monitoring initiatives are often not realized. This has inevitably made the remote sensing approach an interesting option for fire protection managers and decision-makers due to its ability to measure large areas and its temporal capabilities. In this study, burn spectral indices derived from Landsat 8 (difference normalized vegetation index (dNDVI) and difference normalized burn ratio (dNBR)) were used to assess the ecological and socioeconomic impacts of forest fires based on an existing land use/land cover dataset. The relationships between estimated fire severity/area and environmental and anthropogenic factors were also evaluated. The results show that more than 700 hectares of forest and other land use categories were burned. Fires adversely affect high forests, thickets, degraded forests, and most cultivated and rural areas. The study also revealed a moderate positive relationship between burn severity and pre-fire vegetation (R2 = 0.48 and R2 = 0.49 for the dNDVI and dNBR, respectively). This result suggested that the fuel amount is the main driver of burn severity during the fire season in this particular ecosystem. Topography has been shown to affect fire behavior in the study area, where fires occur primarily at elevations averaging 400-800 meters above mean sea level. In contrast, there is a weak positive relationship between population density and burnt area. This phenomenon is commonly observed in specific regions, where the incidence of fire is directly proportional to the density of the population. However, the severity decreases when burning exceeds a threshold. This study has shown that Landsat 8 data-derived burn spectral indices (dNDVI and dNBR) have high potential for the spatial analysis of wildfires.
Period-like polynomials for L-series associated with half-integral weight cusp forms
Authors: Branch James , Diamantis Nikolaos , Raji Wissam , Rolen Larry
Published: June 2024

Given the L-series of a half-integral weight cusp form, we construct polynomials behaving similarly to the classical period polynomial of an integral weight cusp form. We also define a lift of half-integral weight cusp forms to integral weight cusp forms that are compatible with the L-series of the respective forms.
An iterative two-phase optimization method for heterogeneous multi-drone routing problem considering differentiated demands
Authors: Liu Huan , Wu Guohua , Yuan Yufei , Wang Dezhi , Zheng Long , Zhou Wei
Published: June 2024

Owing to low cost, high flexibility and delivery efficiency, effectively addressing the challenges of “last-mile” delivery. While collaborative truck-drone delivery systems have been proposed to overcome limitations such as limited battery life and payload capacity, they are not well-suited for large and heavy parcel delivery. To solve the issue, a pioneering heterogeneous multi-drone delivery system. In this system, the mother drone handles the delivery of large and heavy parcels, releasing small drones to manage the delivery of smaller and lighter parcels. To address the complexities of this multi-drone delivery system, we introduce a divide-and-conquer framework consisting of two integral phases. The first phase, the task allocation phase, generates multiple task allocation schemes, while the second phase, the single-drone route planning phase, produces high-quality routes for each individual drone. Two phases are performed in an iterative manner until the predefined stopping criteria are satisfied. In the task allocation phase, we propose a simulated annealing algorithm (SA) to facilitate task allocation among multiple drones, utilizing transfer and recombination operators to generate high-quality solutions. After obtaining the task allocation scheme, a satisfactory route of a mother drone is generated by a variable neighborhood descent algorithm (VND). A desirable route for each single small drone is produced by dynamic programming (DP).Extensive experiments are conducted, demonstrating the outstanding optimization and time efficiency of the proposed two-phase optimization method by the fact that it obtains within a 4.89% gap from the optimal solution generated by CPLEX in 15.48 s for instance up to 125 nodes.
Joint data augmentations for automated graph contrastive learning and forecasting
Authors: Liu Jiaqi , Chen Yifu , Ren Qianqian , Gao Yang
Published: June 2024

Graph augmentation plays a crucial role in graph contrastive learning. However, existing methods primarily optimize augmentations specific to particular datasets, which limits their robustness and generalization capabilities. To overcome these limitations, many studies have explored automated graph data augmentations. However, these approaches face challenges due to weak labels and data incompleteness. To tackle these challenges, we propose an innovative framework called Joint Data Augmentations for Automated Graph Contrastive Learning (JDAGCL). The proposed model first integrates two augmenters: a feature-level augmenter and an edge-level augmenter. The two augmenters learn whether to drop an edge or node to obtain optimized graph structures and enrich the information available for modeling and forecasting task. Moreover, we introduce two stage training strategy to further process the features extracted by the encoder and enhance their effectiveness for forecasting downstream task. The experimental results demonstrate that our proposed model JDAGCL achieves state-of-the-art performance compared to the latest baseline methods, with an average improvement of 14% in forecasting accuracy across multiple benchmark datasets.
Grounding rod hanging and removing robot with hand-eye self-calibration capability in substation
Authors: Lin Yunhan , Wang Jiahui , Liu Kaibo , Min Huasong
Published: June 2024

In this paper, a robot system for hanging and removing grounding rods is designed by integrating 3D recognition technology, hand-eye self-calibration technology, and automatic operation technology. Specifically, a novel hand-eye self-calibration algorithm is proposed that only uses common objects in the actual scene, which differs from traditional robot hand-eye calibration in that it requires a dedicated calibration board to assist with offline completion. Addressing the problem that existing self-calibration methods cannot be optimized as a whole, resulting in low accuracy and instability of the solution, a multi-stage objective function optimization self-calibration algorithm is proposed. An optimization method based on the minimization of re-projection error is designed to compensate for the results, which uses an efficient Oriented fast and rotated brief (ORB) feature extraction algorithm and introduces a scoring mechanism to retain more correct matching points in the feature matching stage. Experimental verifications are conducted using both public dataset and practical robot system. In the dataset experiment, our method demonstrates superior accuracy and robustness compared to existing self-calibration methods. Furthermore, the practical robot platform experiment confirms the feasibility and efficacy of our approach across various wind speeds and lighting conditions.
Two-stage many-objective evolutionary algorithm: enhanced dominance relations and control mechanisms for separated balance
Authors: Li Wei , Niliang Qilin , Wang Lei , Jiang Qiaoyong
Published: June 2024

Although the multiobjective evolutionary algorithms (MOEAs) have been proved to bring promising prospects for solving multiobjective optimization problems (MOPs), the performance of the algorithm deteriorates sharply in high-dimensional objective space due to the weak selection pressure and the unregulated balance, which is caused by the increase of objective space dimension. Some current MOEAs with two-stage strategy (TS) strive to address above issues by dividing the evolutionary process into two independent stages, in which convergence and diversity are handled separately within successive generations of different stages. However, TS-MOEAs have some weaknesses, such as sensitivity to stage division, and incomplete separation of convergence and diversity. In this paper, TS/KW-MaOEA is proposed for solving many-objective optimization problems (MaOPs), which keeps TS as the central and equips a perfect control mechanism for separated balance. More specifically, TS/KW-MaOEA can automatically adjust the balance trend and provide appropriate selection pressure for MaOPs according to the Kondratiev wave (KW) search model and the objective space dimension. To verify the effectiveness of the proposed algorithm, a series of experiments are carried out against seven state-of-the-art many-objective optimization algorithms on 15 benchmark problems with up to 30 objectives. Experimental results indicate that the proposed algorithm is highly competitive against peer competitors.
Enhancing learning on uncertain pixels in self-distillation for object segmentation
Authors: Chen Lei , Cao Tieyong , Zheng Yunfei , Wang Yang , Zhang Bo , Yang Jibin
Published: June 2024

Self-distillation method guides the model learning via transferring knowledge of the model itself, which has shown the advantages in object segmentation. However, it has been proved that uncertain pixels with predicted probability close to 0.5 will restrict the model performance. The existing self-distillation methods cannot guide the model to enhance its learning ability for uncertain pixels, so the improvement is limited. To boost the student model’s learning ability for uncertain pixels, a novel self-distillation method is proposed. Firstly, the predicted probability in the current training sample and the ground truth label are fused to construct the teacher knowledge, as the current predicted information can express the performance of student models and represent the uncertainty of pixels more accurately. Secondly, a quadratic mapping function between the predicted probabilities of the teacher and student model is proposed. Theoretical analysis shows that the proposed method using the mapping function can guide the model to enhance the learning ability for uncertain pixels. Finally, the essential difference of utilizing the predicted probability of the student model in self-distillation is discussed in detail. Extensive experiments were conducted on models with convolutional neural networks and Transformer architectures as the backbone networks. The results on four public datasets demonstrate that the proposed method can effectively improve the student model performance.
Research on coal-rock identification method and data augmentation algorithm of comprehensive working face based on FL-Segformer
Authors: Zhang Yun , Tong Liang , Lai Xingping , Cao Shenggen , Yan Baoxu , Yang Yanbin , Liu Yongzi , He Wei
Published: June 2024

Coal-rock interface identification technology was pivotal in automatically adjusting the shearer’s cutting drum during coal mining. However, it also served as a technical bottleneck hindering the advancement of intelligent coal mining. This study aimed to address the poor accuracy of current coal-rock identification technology on comprehensive working faces, coupled with the limited availability of coal-rock datasets. The loss function of the SegFormer model was enhanced, the model’s hyperparameters and learning rate were adjusted, and an automatic recognition method was proposed for coal-rock interfaces based on FL-SegFormer. Additionally, an experimental platform was constructed to simulate the dusty environment during coal-rock cutting by the shearer, enabling the collection of coal-rock test image datasets. The morphology-based algorithms were employed to expand the coal-rock image datasets through image rotation, color dithering, and Gaussian noise injection so as to augment the diversity and applicability of the datasets. As a result, a coal-rock image dataset comprising 8424 samples was generated. The findings demonstrated that the FL-SegFormer model achieved a Mean Intersection over Union (MIoU) and mean pixel accuracy (MPA) of 97.72% and 98.83%, respectively. The FL-SegFormer model outperformed other models in terms of recognition accuracy, as evidenced by an MIoU exceeding 95.70% of the original image. Furthermore, the FL-SegFormer model using original coal-rock images was validated from No. 15205 working face of the Yulin test mine in northern Shaanxi. The calculated average error was only 1.77%, and the model operated at a rate of 46.96 frames per second, meeting the practical application and deployment requirements in underground settings. These results provided a theoretical foundation for achieving automatic and efficient mining with coal mining machines and the intelligent development of coal mines.
Experimental study on joint sensing and early warning method of landslide disaster based on NPR-OFST
Authors: Tao Zhigang , Feng Yuxiang , Zhang Xiaoyu , Yu Zhehan
Published: June 2024

In order to explore more effective methods of landslide disaster monitoring and controlling, NPR anchor cable and optical fiber grating strain sensor are physically combined to form a slope reinforcement-monitoring integration system, with PVC pipe an intermediary. Physical model test is carried out according to timely warning of landslide disasters of the Newtonian force monitoring system. At the same time, the optical fiber sensing technology has the condition of continuous perception of time and space. The feasibility of monitoring the whole life cycle of slope instability and positioning the potential sliding surface is discussed. Through the analysis of the test results, it is concluded that the fiber grating strain sensor can effectively monitor the deep displacement of the slope. PVC pipe and the soil have deformation coordination, which is able to effectively reinforce the slope body together with the combined anchor cable sensing device, and can continuously sense the potential sliding surface in the whole life cycle of the slope. By comparing the results of Newton force monitoring curve with the fiber grating strain monitoring, the mechanical law of “Newton force sudden drops, immediately catastrophe happens” is further verified. The feasibility of the combined sensing and early warning method of optical fiber sensing technology and Newton force monitoring is verified. This method realizes the further optimization of Newton force monitoring system.
Screw extrusion additive manufacturing of thermoplastic polyolefin elastomer
Authors: Curmi Albert , Rochman Arif , Gatt Alfred
Published: June 2024

This study determined the requisite process parameters for good-quality screw extrusion additive manufacturing (AM) of thermoplastic polyolefin (TPO) using fused granulate fabrication (FGF). TPO is a non-hygroscopic, cheaper, and less dense alternative to the well-established thermoplastic polyurethane (TPU). TPO was found to extrude correctly at 170 °C, on a glass build plate at 80 °C with Magigoo PP adhesive. A water uptake test on TPO reported a mass gain plateau of 0.25%, which is significantly lower than that of TPU, which suggests that TPO may not require drying before 3D printing. Tensile testing on FGF TPO specimens achieved similar stress at yield as well as stress and strain at break as indicated by the data sheet for the XY and YZ orientations. The Z direction is significantly weaker than the X and Y orientations, reaching only 30% of the stress at break. TPO achieved the best average stress at yield of 6.36 MPa using the 0.4 mm nozzle with XY printing orientation and stress and strain at break of 13.8 MPa and 1300% at YZ orientation and 1 mm nozzle. The setup achieved relatively high-quality prints of complex geometries, including the popular torture-test Benchy and a child-sized orthotic insole.
The shift-dimension of multipersistence modules
Authors: Chachólski Wojciech , Corbet René , Sattelberger Anna-Laura
Published: June 2024

We present the shift-dimension of multipersistence modules and investigate its algebraic properties. This gives rise to a new invariant of multigraded modules over the multivariate polynomial ring arising from the hierarchical stabilization of the zeroth total multigraded Betti number. We give a fast algorithm for the computation of the shift-dimension of interval modules in the bivariate case. We construct multipersistence contours that are parameterized by multivariate functions and hence provide a large class of feature maps for machine learning tasks.