bluuebunny/crossref_metadata_2025 huggingface dataset:
The Safe Values of Quantitative Perfusion Parameters of ICG Angiography Based on Tissue Oxygenation of Hyperspectral Imaging for Laparoscopic Colorectal Surgery: A Prospective Observational Study
Authors: Son Gyung , Nazir Armaan , Yun Mi , Lee In , Im Sun , Kwak Jae , Park Sang-Ho , Baek Kwang-Ryul , Gockel Ines
Published: July 2023

Background: Safe values for quantitative perfusion parameters of indocyanine green (ICG) angiography have not been fully defined, and interpretation remains at the surgeon’s discretion. This prospective observational study aimed to establish the safe values for the quantitative perfusion parameters by comparing tissue oxygenation levels from HSI images in laparoscopic colorectal surgery. Methods: ICG angiography was performed using a laparoscopic near-infrared (NIR) camera system with ICG diluted in 10 mL of distilled water. For quantitative perfusion parameters, the changes in fluorescence intensity with perfusion times were analyzed to plot a time–fluorescence intensity graph. To assess real-time tissue oxygen saturation (StO2) in the colon, the TIVITA® Tissue System was utilized for hyperspectral imaging (HSI) acquisition. The StO2 levels were compared with the quantitative perfusion parameters derived from ICG angiography at corresponding points to define the safe range of ICG parameters reflecting good tissue oxygenation. Results: In the regression analysis, T1/2MAX, TMAX, slope, and NIR perfusion index were correlated with tissue oxygen saturation. Using this regression model, the cutoff values of quantitative perfusion parameters were calculated as T1/2MAX ≤ 10 s, TMAX ≤ 30 s, slope ≥ 5, and NIR perfusion index ≥50, which best reflected colon StO2 higher than 60%. Diagnostic values were analyzed to predict colon StO2 of 60% or more, and the ICG perfusion parameters T1/2MAX, TMAX, and perfusion TR showed high sensitivity values of 97% or more, indicating their ability to correctly identify cases with acceptable StO2. Conclusion: The safe values for quantitative perfusion parameters derived from ICG angiography were T1/2MAX ≤ 10 s and TMAX ≤ 30 s, which were associated with colon tissue oxygenation levels higher than 60% in the laparoscopic colorectal surgery.
What Nutraceuticals Can Do for Duchenne Muscular Dystrophy: Lessons Learned from Amino Acid Supplementation in Mouse Models
Authors: De Paepe Boel
Published: July 2023

Duchenne muscular dystrophy (DMD), the severest form of muscular dystrophy, is characterized by progressive muscle weakness with fatal outcomes most often before the fourth decade of life. Despite the recent addition of molecular treatments, DMD remains a disease without a cure, and the need persists for the development of supportive therapies aiming to help improve patients’ quality of life. This review focuses on the therapeutical potential of amino acid and derivative supplements, summarizing results obtained in preclinical studies in murine disease models. Several promising compounds have emerged, with L-arginine, N-acetylcysteine, and taurine featuring among the most intensively investigated. Their beneficial effects include reduced inflammatory, oxidative, fibrotic, and necrotic damage to skeletal muscle tissues. Improvement of muscle strength and endurance have been reported; however, mild side effects have also surfaced. More explorative, placebo-controlled and long-term clinical trials would need to be conducted in order to identify amino acid formulae that are safe and of true benefit to DMD patients.
Understanding the Impact of COVID-19 on Angioplasty Service and Outcome of Patients Treated for Chronic Limb-Threatening Ischaemia: A Single-Centre Retrospective Cohort Study
Authors: Rodway Alexander D. , Harris Jenny , Hanna Lydia , Allan Charlotte , Casal Felipe Pazos , Giltinan Ciara , Dehghan-Nayeri Ali , Santos Andre , Whyte Martin B. , Ntagiantas Nikolaos , Walton Ivan , Brown Richard , Skene Simon S. , Pankhania Ajay , Field Benjamin C. T. , Maytham Gary D. , Heiss Christian
Published: July 2023

We evaluated the impact of COVID-19 restriction on the angioplasty service and outcome of chronic limb-threatening ischaemia (CLTI) patients undergoing lower-limb angioplasty in a UK secondary care setting. Consecutive patients were analysed retrospectively. Pre-COVID-19 (08/2018–02/2020), 106 CLTI patients (91% Fontaine 4; 60% diabetes mellitus) and during COVID-19 (03/2020–07/2021) 94 patients were treated (86% Fontaine 4; 66% diabetes mellitus). While the average monthly number of patients treated did not change, the proportion of day cases significantly increased (53% to 80%), and hospitalised patients decreased. Patients treated in ≤14/5 days after referral significantly increased to 64/63%. Kaplan–Meier survival analysis (30-day/1-year) showed that neither wound healing nor mortality were significantly changed during COVID-19. In day cases, 1-year but not 30-day major amputations significantly increased, and clinically driven target-lesion revascularisation decreased during COVID-19. One-year mortality was significantly worse in hospitalised compared to day cases (14% vs. 43%) at similar wound healing rates (83% vs. 84%). The most frequent known cause of death was infectious disease (64%), while cardiovascular (21%) was less frequent. Despite COVID-19 restrictions, a safe and effective angioplasty service was maintained while shortening waiting times. Very high mortality rates in hospitalised patients may indicate that CLTI patients need to be referred and treated more aggressively earlier.
How Many Alzheimer–Perusini’s Atypical Forms Do We Still Have to Discover?
Authors: Donato Luigi , Mordà Domenico , Scimone Concetta , Alibrandi Simona , D’Angelo Rosalia , Sidoti Antonina
Published: July 2023

Alzheimer–Perusini’s (AD) disease represents the most spread dementia around the world and constitutes a serious problem for public health. It was first described by the two physicians from whom it took its name. Nowadays, we have extensively expanded our knowledge about this disease. Starting from a merely clinical and histopathologic description, we have now reached better molecular comprehension. For instance, we passed from an old conceptualization of the disease based on plaques and tangles to a more modern vision of mixed proteinopathy in a one-to-one relationship with an alteration of specific glial and neuronal phenotypes. However, no disease-modifying therapies are yet available. It is likely that the only way to find a few “magic bullets” is to deepen this aspect more and more until we are able to draw up specific molecular profiles for single AD cases. This review reports the most recent classifications of AD atypical variants in order to summarize all the clinical evidence using several discrimina (for example, post mortem neurofibrillary tangle density, cerebral atrophy, or FDG-PET studies). The better defined four atypical forms are posterior cortical atrophy (PCA), logopenic variant of primary progressive aphasia (LvPPA), behavioral/dysexecutive variant and AD with corticobasal degeneration (CBS). Moreover, we discuss the usefulness of such classifications before outlining the molecular–genetic aspects focusing on microglial activity or, more generally, immune system control of neuroinflammation and neurodegeneration.
A Miniaturized System for Rapid, Isothermal Detection of SARS-CoV-2 in Human and Environmental Samples
Authors: Staples Jake , Dourou Athanasia-Maria , Liampa Irene , Sjaarda Calvin , Moslinger Emily , Wong Henry , Sheth Prameet M. , Arhondakis Stilianos , Prakash Ravi
Published: July 2023

We report a small-footprint cost-effective isothermal rapid DNA amplification system, with integrated microfluidics for automated sample analysis and detection of SARS-CoV-2 in human and environmental samples. Our system measures low-level fluorescent signals in real-time during amplification, while maintaining the desired assay temperature on a low power, portable system footprint. A unique soft microfluidic chip design was implemented to mitigate thermocapillary effects and facilitate optical alignment for automated image capture and signal analysis. The system-on-board prototype, coupled with the LAMP primers designed by BioCoS, was sensitive enough to detect large variations in viral loads of SARS-CoV-2 corresponding to a threshold cycle range of 16 to 39. Furthermore, tested samples consisted of a broad range of viral strains and lineages identified in Canada during 2021–2022. Clinical specimens were collected and tested at the Kingston Health Science Centre using a clinically validated PCR assay, and variants were determined using whole genome sequencing.
Low Doses of β-Caryophyllene Reduced Clinical and Paraclinical Parameters of an Autoimmune Animal Model of Multiple Sclerosis: Investigating the Role of CB2 Receptors in Inflammation by Lymphocytes and Microglial
Authors: Askari Vahid Reza , Baradaran Rahimi Vafa , Shafiee-Nick Reza
Published: July 2023

Multiple Sclerosis (MS) is a prevalent inflammatory disease in which the immune system plays an essential role in the damage, inflammation, and demyelination of central nervous system neurons (CNS). The cannabinoid receptor type 2 (CB2) agonists possess anti-inflammatory effects against noxious stimuli and elevate the neuronal survival rate. We attempted to analyze the protective impact of low doses of β-Caryophyllene (BCP) in experimental autoimmune encephalomyelitis (EAE) mice as a chronic MS model. Immunization of female C57BL/6 mice was achieved through two subcutaneous injections into different areas of the hind flank with an emulsion that consisted of myelin Myelin oligodendrocyte glycoprotein (MOG)35–55 (150 µg) and complete Freund’s adjuvant (CFA) (400 µg) with an equal volume. Two intraperitoneal (i.p.) injections of pertussis toxin (300 ng) were performed on the animals on day zero (immunizations day) and 48 h (2nd day) after injection of MOG + CFA. The defensive effect of low doses of BCP (2.5 and 5 mg/kg/d) was investigated in the presence and absence of a CB2 receptor antagonist (1 mg/kg, AM630) in the EAE model. We also examined the pro/anti-inflammatory cytokine levels and the polarization of brain microglia and spleen lymphocytes in EAE animals. According to our findings, low doses of BCP offered protective impacts in the EAE mice treatment in a CB2 receptor-dependent way. In addition, according to results, BCP decreased the pathological and clinical defects in EAE mice via modulating adaptive (lymphocytes) and innate (microglia) immune systems from inflammatory phenotypes (M1/Th1/Th17) to anti-inflammatory (M2/Th2/Treg) phenotypes. Additionally, BCP elevated the anti-inflammatory cytokine IL-10 and reduced blood inflammatory cytokines. BCP almost targeted the systemic immune system more than the CNS immune system. Thus, a low dose of BCP can be suggested as a therapeutic effect on MS treatment with potent anti-inflammatory effects and possibly lower toxicity.
Effectiveness of Opioid Switching in Advanced Cancer Pain: A Prospective Observational Cohort Study
Authors: Wong Aaron K. , Somogyi Andrew A. , Rubio Justin , Pham Tien Dung , Le Brian , Klepstad Pal , Philip Jennifer
Published: July 2023

Opioid switching is a common practice of substituting one opioid for another to improve analgesia or adverse effects; however, it has limited evidence. This study aimed to examine the effectiveness of opioid switching in advanced cancer. This multi-center prospective cohort study recruited patients assessed to switch opioids (opioid switch group) or to continue ongoing opioid treatment (control group). Clinical data (demographics, opioids) and validated instruments (pain and adverse effects) were collected over two timepoints seven days apart. Descriptive analyses were utilized. Non-parametric tests were used to determine differences. Fifty-four participants were recruited (23 control group, 31 switch group). At the follow-up, opioid switching reduced pain (worst, average, and now) (p < 0.05), uncontrolled breakthrough pain (3-fold reduction, p = 0.008), and psychological distress (48% to 16%, p < 0.005). The switch group had a ≥25% reduction in the reported frequency of seven moderate-to-severe adverse effects (score ≥ 4), compared to a reduction in only one adverse effect in the control group. The control group experienced no significant pain differences at the follow-up. Opioid switching is effective at reducing pain, adverse effects, and psychological distress in a population with advanced cancer pain, to levels of satisfactory symptom control in most patients within 1 week.
Validation of a Novel EUS-FNB-Derived Organoid Co-Culture System for Drug Screening in Patients with Pancreatic Cancer
Authors: Grützmeier Simon Ezban , Kovacevic Bojan , Vilmann Peter , Rift Charlotte Vestrup , Melchior Linea Cecilie , Holmström Morten Orebo , Brink Lene , Hassan Hazem , Karstensen John Gásdal , Grossjohann Hanne , Chiranth Deepthi , Toxværd Anders , Hansen Carsten Palnæs , Høgdall Estrid , Hasselby Jane Preuss , Klausen Pia
Published: July 2023

Cancer-associated fibroblasts (CAFs) have been shown to impact the chemosensitivity of patient-derived tumor organoids (PDTOs). However, the published literature comparing PDTO response to clinical outcome does not include CAFs in the models. Here, a co-culture model was created using PDTOs and CAFs derived from endoscopic ultrasound-guided fine-needle biopsies (EUS-FNBs) for potential use in drug screening applications. Co-cultures were established, and growth was compared to monocultures using image metrics and a commercially available assay. We were able to establish and expand validated malignant PDTOs from 19.2% of adenocarcinomas from EUS-FNBs. CAFs could be established from 25% of the samples. The viability of PDTOs in the mixed cell co-culture could be isolated using image metrics. The addition of CAFs promoted PDTO growth in half of the established co-cultures. These results show that co-cultures can be established from tiny amounts of tissue provided by EUS-FNB. An increased growth of PDTOs was shown in co-cultures, suggesting that the present setup successfully models CAF–PDTO interaction. Furthermore, we demonstrated that standard validation techniques may be insufficient to detect contamination with normal cells in PDTO cultures established from primary tumor core biopsies.
Bi2WO6@g-C3N4 Heterostructure for Cathodic Photoelectrochemical Dopamine Sensor
Authors: Wu Zhifang , Su Ying , Han Fangjie , Liang Zhishan , Han Dongxue , Qin Dongdong , Niu Li
Published: July 2023

A simple and low-cost cathodic photoelectrochemical (PEC) sensor based on Bi2WO6@g-C3N4 was designed for dopamine (DA) detection. The Bi2WO6 nanoflower was first prepared using a simple hydrothermal method followed by the combination with g-C3N4 nanosheet to form the Bi2WO6@g-C3N4 heterostructure. The heterostructure can extend the absorbance to the visible region and accelerate the transfer of charge carriers. Furthermore, DA easily coordinates with exposed Bi3+ on the Bi2WO6 surface and forms the charge-transfer complex to further enhance the cathodic photocurrent. Under optimal conditions, there are two linear relationships between the concentration of DA and photocurrent intensity. The linear ranges are 0.1–10 µM and 10–250 µM, with a sensitive detection limit (LOD) of 28 nM. Notably, the real sample of human blood serum analysis further revealed the accuracy and feasibility of the Bi2WO6@g-C3N4-based PEC platform. Convincingly, the heterostructure of Bi2WO6 and g-C3N4 opened up a new avenue for the construction of DA analysis.
Effects of Physical Activity and Nutrition Education on the Gut Microbiota in Overweight and Obese Children
Authors: Morgado Micaela C. , Sousa Mónica , Marques Cláudia , Coelho André B. , Costa Júlio A. , Seabra André
Published: July 2023

Childhood obesity continues to represent a growing challenge, and it has been associated with gut microbiota dysbiosis. This study examines the gut microbiota composition in overweight and obese school children and assesses whether a 12-week multidisciplinary intervention can induce changes in the gut microbiota. The intervention, which combined recreational football and nutritional education, was implemented among 15 school children, aged 7–10 years, with a Body Mass Index ≥ 85th percentile. The children were assigned into two groups: Football Group (n = 9) and Nutrition and Football Group (n = 6). Faecal samples were collected at the beginning and end of the program and analysed by sequencing the 16S rRNA gene. Over the intervention, a significant decrease was found collectively for Bifidobacterium genera (p = 0.011) and for Roseburia genera in the Football Group (p = 0.021). The relative abundance of Roseburia (p = 0.002) and Roseburia faecis (p = 0.009) was negatively correlated with moderate to vigorous physical activity (MVPA), while Prevotella copri was positively correlated with MVPA (p = 0.010) and with the daily intake of protein (p = 0.008). Our findings suggest that a multidisciplinary intervention was capable of inducing limited but significant positive changes in the gut microbiota composition in overweight and obese school children.
Native Carnivore Diversity and Relative Abundance in Landscapes of the Coast Range in Central Chile: Insights for Conservation Decision-Making
Authors: Ramírez-Álvarez Diego , Napolitano Constanza , Arriagada Gabriel , Salgado Iván , Cox Simón , Céspedes-Parada Belén
Published: July 2023

Natural habitats in South America have been intensively used and modified, including their conversion to exotic tree plantations, impacting the terrestrial fauna communities. Carnivores play an important role in the functioning of ecosystems as apex predators. Landscape characteristics and resource availability determine the composition and abundance of co-occurring carnivores. We hypothesized that the diversity and relative abundance of native carnivores varied in relation to the different vegetation macrohabitats. We predicted that native forests support a higher diversity and abundance of native carnivores compared to exotic plantations. Between 1 March 2021 and 31 March 2022, we estimated the species’ richness, composition, and relative abundance of terrestrial native carnivores in three different landscapes of the Coast Range in central Chile: (a) monoculture plantation of the exotic Pinus radiata (MP); (b) Mediterranean coastal thorn forest (TF); and (c) Mediterranean coastal sclerophyllous forest (SF). We monitored an area of 1000 ha in each landscape, installing 10 camera traps (total of 30 camera traps). We used a monitoring transect with unbaited camera traps separated by 1 km, with a total photo-trapping effort of 10,046 camera days. The classification, organization, and analysis of camera trap data were conducted using CameraSweet software. The total number of independent native carnivore species events (photos separated > 60 min) recorded in each landscape were 1564 in SF, 1412 in TF, and 775 in MP. Carnivore richness and composition were not significantly different in all three landscapes. We detected five native carnivore species. Relative abundance by species was significantly higher in SF compared to MP for Leopardus guigna, Conepatus chinga, and Galictis cuja and also significantly higher in TF compared to MP for L. guigna. Our results suggest that the native vegetation cover must be preserved to maintain viable and abundant native carnivore populations, crucially relevant in the highly impacted and human-dominated global biodiversity hotspot of Central Chile. This study contributes to informing evidence-based decision-making and conservation strategies at the landscape level to mitigate biodiversity loss.
A Self-Powered VDJT AC–DC Conversion Circuit for Piezoelectric Energy Harvesting Systems
Authors: Kamran Muhammad , Edla Mahesh , Thabet Ahmed , Mikio Deguchi , Bui Vinh
Published: July 2023

A comprehensive model for micro-powered piezoelectric generator (PG), analysis of operation, and control of voltage doubler joule thief (VDJT) circuit to find the piezoelectric devices (PD’s) optimum functioning points are discussed in the present article. The proposed model demonstrates the power dependence of the PG on mechanical excitation, frequency, and acceleration, as well as outlines the load behaviour for optimal operation. The proposed VDJT circuit integrates the combination of voltage doubler (VD) and joule thief circuit, whereas the VD circuit works in Stage 1 for AC (alternating current)–DC (direct current) conversion, while a joule thief circuit works in Stage 2 for DC–DC conversion. The proposed circuit functions as an efficient power converter, which converts power from AC–DC and boosts the voltage from low to high without employing any additional electronic components and generating duty cycles. The electrical nature of the input (i.e., PD) of a VDJT circuit is in perfect arrangement with the investigated optimisation needs when using the proposed control circuit. The effectiveness of the proposed VDJT circuit is examined in terms of both simulation and experiment, and the results are presented. The proposed circuit’s performance was validated with available results of power electronics interfaces in the literature. The proposed circuit’s flexibility and controllability can be used for various applications, including mobile battery charging and power harvesting.
Thermodynamic Entropy as a Noether Invariant from Contact Geometry
Authors: Bravetti Alessandro , García-Ariza Miguel Ángel , Tapias Diego
Published: July 2023

We use a formulation of Noether’s theorem for contact Hamiltonian systems to derive a relation between the thermodynamic entropy and the Noether invariant associated with time-translational symmetry. In the particular case of thermostatted systems at equilibrium, we show that the total entropy of the system plus the reservoir are conserved as a consequence thereof. Our results contribute to understanding thermodynamic entropy from a geometric point of view.
Unstable Points, Ergodicity and Born’s Rule in 2d Bohmian Systems
Authors: Tzemos Athanasios C. , Contopoulos George
Published: July 2023

We study the role of unstable points in the Bohmian flow of a 2d system composed of two non-interacting harmonic oscillators. In particular, we study the unstable points in the inertial frame of reference as well as in the frame of reference of the moving nodal points, in cases with 1, 2 and multiple nodal points. Then, we find the contributions of the ordered and chaotic trajectories in the Born distribution, and when the latter is accessible by an initial particle distribution which does not satisfy Born’s rule.
Teaching Is Messy: Using Lesson Study to Reimagine Student-Centered Clinical Experiences
Authors: Falbe Kristina N. , Seglem Robyn
Published: July 2023

Teacher preparation is dependent on a clinical model of instruction where students apprentice with licensed teachers to gain experience in a classroom. It is not always easy to create these opportunities in schools that are local to the university, especially with a large middle-level program. This qualitative study examines how using lesson study in an early clinical experience can create high-quality experiences and develop innovative thinking around lesson design. This research answers the following questions: (1) What events do the preservice teachers identify as memorable in their interactions with students, peers, and teachers during a clinical experience that uses the lesson study model? (2) How does the lesson study model influence preservice teachers’ thinking about teaching? The results from the study suggest that a lesson study model is a viable option for middle-level teacher preparation programs. While it solves some practical issues, such as a lack of quality clinical experiences, it also creates an experience where students feel supported, scaffolded, and engaged.
The Inequities Embedded in Measures of Engagement in Science Education for African American Learners from a Culturally Relevant Science Pedagogy Lens
Authors: Nkrumah Tara
Published: July 2023

Although African American educators strive to ameliorate racist and/or sexist barriers to learners’ science engagement in U.S. education, examples of applications of culturally relevant science instruments to measure African American learners’ engagement in science are hard to find in the literature. Inaccurate perceptions about student engagement in science education continue to exist, including assumptions about the prevalence and effects of low socioeconomic status, limited content knowledge, and a lack of interest or motivation of African American learners compared to white learners. Most exemplars of student engagement in science focus on the cognitive, behavioral, and social mores of white, male, cisgender, middle-class learners and their reactions to teacher pedagogy. This article reports on a qualitative study of three African American female and male secondary science educators’ narratives of “engagement” in science amongst systemic inequities in the northeastern and southeastern U.S. regions. To better understand African American learners’ science engagement, I combined socially transformative science curriculum approaches for African American students using five types of mastery with the concepts of culturally relevant science pedagogy as the facilitator of racial equity. A critical-arts-based research methodology was used to craft participants’ autobiographical data and drawings into a literary métissage of the participants’ experiences, memories, and culturally relevant pedagogical strategies. Themes included: (1) teachers’ recognition that their interest and positionality impacted their engagement in science; (2) their understanding of how identifying as scientists informed their career choices and modes of participation; and (3) their observations about how mentoring and vision influenced students’ attitudes about engaging in science. The major finding was that critical incidents that teachers experienced when they were students in K-20 schools influenced how they became engaged in science and constructed their culturally relevant practices as science educators. The implications of this finding for pre-service and teacher leadership development for equitable teaching and learning will be discussed, and recommendations for using culturally relevant science practices and navigating power dynamics will be provided.
Survey of Personalized Learning Software Systems: A Taxonomy of Environments, Learning Content, and User Models
Authors: Ismail Heba , Hussein Nada , Harous Saad , Khalil Ashraf
Published: July 2023

This paper presents a comprehensive systematic review of personalized learning software systems. All the systems under review are designed to aid educational stakeholders by personalizing one or more facets of the learning process. This is achieved by exploring and analyzing the common architectural attributes among personalized learning software systems. A literature-driven taxonomy is recognized and built to categorize and analyze the reviewed literature. Relevant papers are filtered to produce a final set of full systems to be reviewed and analyzed. In this meta-review, a set of 72 selected personalized learning software systems have been reviewed and categorized based on the proposed personalized learning taxonomy. The proposed taxonomy outlines the three main architectural components of any personalized learning software system: learning environment, learner model, and content. It further defines the different realizations and attributions of each component. Surveyed systems have been analyzed under the proposed taxonomy according to their architectural components, usage, strengths, and weaknesses. Then, the role of these systems in the development of the field of personalized learning systems is discussed. This review sheds light on the field’s current challenges that need to be resolved in the upcoming years.
Classification of Barriers to Digital Transformation in Higher Education Institutions: Systematic Literature Review
Authors: Gkrimpizi Thomais , Peristeras Vassilios , Magnisalis Ioannis
Published: July 2023

Digital transformation of higher education institutions (HEIs) is of paramount importance in today’s technology-driven world. However, there are numerous barriers that hinder the successful implementation of digital transformation initiatives in HEIs. In this article, we identify and classify these barriers based on a systematic literature review. The findings reveal twenty distinct barriers that inhibit digital transformation in higher education. These were then organised into six broad categories, namely environmental, strategic, organisational, technological, people-related and cultural. The study provides a comprehensive understanding of the barriers faced, facilitating the development of effective strategies and interventions. Our analysis provides valuable information for higher education institutions, policy makers and stakeholders involved in digital transformation initiatives.
Review of Battery Storage and Power Electronic Systems in Flexible A-R-OPF Frameworks
Authors: Gabash Aouss
Published: July 2023

This paper provides an overview of power electronics and its applications in various fields, emphasizing power conditioning and minimizing losses for high energy efficiency. It discusses the distinction between unidirectional and bidirectional converters and their applications in power systems. The significance of unidirectional and bidirectional power flow in different scenarios is explored. The importance of battery storage systems (BSSs) for grid stabilization, frequency regulation, and renewable energy integration is highlighted. The paper focuses on flexible active-reactive optimal power flow (A-R-OPF) frameworks in battery storage and power electronic systems, reviewing existing research, identifying gaps, and offering new perspectives. It addresses the challenges and potential of grid-scale energy storage for reliable and cost-effective power systems with high renewable energy penetration. The need for energy curtailment, demand response, and smart grid implementation is discussed. The paper emphasizes comprehensive coordination, new power lines, European collaboration, and smart grid implementation to meet the dynamic needs of Europe’s power grids.
A Mask-Wearing Detection Model in Complex Scenarios Based on YOLOv7-CPCSDSA
Authors: Wang Jingyang , Wang Junkai , Zhang Xiaotian , Yu Naiwen
Published: July 2023

With the rapid development of deep learning technology, many algorithms for mask-wearing detection have achieved remarkable results. However, the detection effect still needs to be improved when dealing with mask-wearing in some complex scenes where the targets are too dense or partially occluded. This paper proposes a new mask-wearing detection model: YOLOv7-CPCSDSA. Based on YOLOv7, this model replaces some convolutions of the original model, CatConv, with FasterNet’s partial convolution (PConv) to form a CatPConv (CPC) structure, which can reduce computational redundancy and memory access. In the case of an increase in the network layer, the parameters are reduced instead. The Small Detection (SD) module is added to the model, which includes structures such as upsampling, concat convolution, and MaxPooling to enhance the ability to capture small targets, thereby improving detection accuracy. In addition, the Shuffle Attention (SA) mechanism is introduced, which enables the model to adaptively focus on important local information, thereby improving the accuracy of detecting mask-wearing. This paper uses comparative and ablation experiments in the mask dataset (including many images in complex scenarios) to verify the model’s effectiveness. The results show that the mean average precision@0.5 (mAP@0.5) of YOLOv7-CPCSDSA reaches 88.4%, which is 1.9% higher than that of YOLOv7, and its frames per second (FPS) rate reaches 75.8 f/s, meeting the real-time detection requirements. Therefore, YOLOv7-CPCSDSA is suitable for detecting mask-wearing in complex scenarios.
Control and Implementation of the Parallel Enhanced Commutation Integrated Nested Multilevel Inverter Topology
Authors: Terbrack Christoph , Speer Sascha , Endisch Christian
Published: July 2023

Due to their high efficiency and advanced battery management capability, cascaded multilevel inverters are an exciting option for battery electric powertrains. A promising, new and highly efficient cascaded multilevel inverter is the Parallel Enhanced Commutation Integrated Nested Multilevel Inverter. The inverter, with four semiconductor switches per submodule, can reconfigure individual battery cells in series and parallel and generate positive and negative phase voltages in regular four-quadrant operation. Therefore, emerging degrees of freedom in battery management and inverter operation must be managed and mapped into a specific Switching State for every switch. As controlling the high number of switches is safety-relevant, this publication profoundly explains the inverter’s functionality. We introduce a Switching Function that accepts easy-to-understand functional states as input, simplifying research on higher-level control algorithms and advanced single-cell battery-management capabilities. As the Switching Function guarantees safe operation and the correct contribution of every cell to the overall functionality of the inverter, it enables researchers to confidently use and thereby accelerate research on the promising new topology. The method we describe is fast, simple, deterministic and designed to convert setpoint specifications into an executable Switching Pattern. We prove that our Switching Function is operable on an FPGA with a twenty-kilohertz setpoint update operating a 17-level inverter.
Airborne Radar STAP Method Based on Deep Unfolding and Convolutional Neural Networks
Authors: Zou Bo , Feng Weike , Zhu Hangui
Published: July 2023

The lack of independent and identically distributed (IID) training range cells is one of the key factors that limit the performance of conventional space-time adaptive processing (STAP) methods for airborne radar. Sparse recovery (SR)-based and convolutional neural network (CNN)-based STAP methods can obtain high-resolution estimations of the clutter space-time spectrum by using few IID training range cells, so as to realize the clutter suppression effectively. However, the performance of SR-STAP methods usually depends on the SR algorithms, having the problems of parameter setting difficulty, high computational complexity and low accuracy, and the CNN-STAP methods have a high requirement for the nonlinear mapping capability of CNN. To solve these problems, CNNs can be used to reduce the requirements of SR algorithms for parameter setting and iterations, increasing its accuracy, and the clutter space-time spectrum obtained by SR can be used to reduce the network scale of the CNN, resulting in the method proposed in this paper. Based on the idea of deep unfolding (DU), the SR algorithm is unfolded into a deep neural network, whose optimal parameters are obtained by training to improve its convergence performance. On this basis, the SR network and CNN are trained end-to-end to estimate the clutter space-time spectrum efficiently and accurately. The simulation and experimental results show that, compared to the SR-STAP and CNN-STAP methods, the proposed method can improve the clutter suppression performance and have a lower computational complexity.
Machine Learning Implementation in Membrane Bioreactor Systems: Progress, Challenges, and Future Perspectives: A Review
Authors: Frontistis Zacharias , Lykogiannis Grigoris , Sarmpanis Anastasios
Published: July 2023

This study offers a review of machine learning (ML) applications in membrane bioreactor (MBR) systems, an emerging technology in advanced wastewater treatment. The review focuses on implementing ML algorithms to enhance the prediction of membrane fouling, control and optimize the system, and predict faults early, thereby enabling the development of novel cleaning strategies. Key ML algorithms such as artificial neural networks (ANNs), support vector machines (SVMs), random forest, and reinforcement learning (RL) are briefly introduced, with an emphasis on their potential and limitations in advanced wastewater applications. The main challenges obstructing the implementation, namely data quality, interpretability, and transferability of ML, are identified. Finally, future research trends are proposed, including ML integration with big data, the Internet of Things (IoT), and hybrid model development. The review also underscores the need for interdisciplinary collaboration and investment in data management, along with the implementation of new policies addressing data privacy and security. By addressing these challenges, the integration of ML into MBRs has the potential to significantly enhance performance and reduce the energy footprint, providing a sustainable solution for advanced wastewater treatment.
Combining Tree-Ring Width and Density to Separate the Effects of Climate Variation and Insect Defoliation
Authors: Kunz Marcel , Esper Jan , Kuhl Eileen , Schneider Lea , Büntgen Ulf , Hartl Claudia
Published: July 2023

Though frequently used in dendroclimatology, European larch (Larix decidua Mill.) is regularly defoliated by mass outbreaks of the larch budmoth (Zeiraphera griseana Hb., LBM). The near-cyclic growth depressions are unrelated to but possibly coincide with cold summers, which challenges signal detection on interannual timescales. LBM defoliation events cause sharp maximum latewood density declines and irregular earlywood/latewood ratios in the outbreak year, followed by one or two anomalously narrow rings. Here, we present a process-based method integrating these diverse response patterns to identify and distinguish LBM-related signals from climate-induced deviations. Application to larch sites along elevational transects in the Swiss Alps reveals the algorithm to perform better than existing extreme event detection methods, though our approach enables additional differentiation between insect- and climate-induced signatures. The new process-based multi-parameter algorithm is a suitable tool to identify different causes of growth disturbances and will therefore help to improve both tree-ring-based climate and insect defoliation reconstructions.
Crinipellis deutziae, Marasmius pinicola spp. nov., and C. rhizomaticola (Agaricales, Basidiomycota) New to China from Beijing
Authors: Li Yue , He Shuang-Hui , Zhang Yi-Zhe , Liang Jia-Qi , Sheng Wen-Yue , Si Jing , Li Hai-Jiao
Published: July 2023

Specimens of Crinipellis and Marasmius (Marasmiaceae) collected from Beijing, North China, were studied by morphological and molecular methods. Phylogenetic analyses were performed separately for the two genera based on ITS sequence data. Two new species, C. deutziae and M. pinicola, were found, and C. rhizomaticola was reported from China for the first time. Crinipellis deutziae is characterized by small basidiocarps, large and variably shaped basidiospores measuring 8.8–11 × 7.5–9.5 µm, the presence of both cheilocystidia and pleurocystidia, and growing on Deutzia parviflora. Marasmius pinicola is characterized by small basidiocarps, cylindrical, reniform to phaseoliform basidiospores measuring 6–8 × 3.5–4.2 µm, often capitate cheilocystidia, and pleurocystidia, and growing on fallen leaves of Pinus tabuliformis. Descriptions and illustrations are provided for the three species. The results of this study contribute to the knowledge of the species diversity of macro-fungi in Beijing.
Early Growth Characterization and C:N:P Stoichiometry in Firmiana simplex Seedlings in Response to Shade and Soil Types
Authors: Zhi Ximin , Song Yi , Yu Deshui , Qian Wenzhang , He Min , Lin Xi , Zhang Danju , Gao Shun
Published: July 2023

Light and soil environments have extensive heterogeneity for many plants species affecting plant growth, reproduction, and distribution. However, the interaction effects of these two factors on the ecophysiological traits and adaptive strategy of plants remain largely unclear. In the present study, we set four shading levels and three soil types to investigate the effects of shade and soil type on seedlings growth, C:N:P stoichiometry responses, and nutrient use efficiency in Firmiana simplex (F. simplex). The maximum of total biomass was observed in acid purple soil under 75% shade, with a maximum difference of 3.6 times. With the increase in shading intensity, C content in the root, stem, and leaf reached maximum value under 75% shade. However, C content in the root and N content in the stem reached a maximum value of 420.6 g·kg−1 and 13.7 g·kg−1 in acid purple soil, respectively. With the increase in shading intensity, the total C and N accumulation showed a trend of progressive increase and then decrease, reaching the maximum value of 346.2 mg and 10.7 mg under 75% shade, respectively. The N:P ratios of various organ ranged from 3.1 to 11.9 in acid purple soil and red soil, indicating that the seedlings growth was restricted by nitrogen. We concluded that the interactions of shade and soil types might adjust the C:N:P stoichiometry and influence the dynamic balance between nutrients and organs in F. simplex seedlings.
Effect of Tree Size Heterogeneity on the Overall Growth Trend of Trees in Coniferous Forests of the Tibetan Plateau
Authors: Wang Yuelin , Shu Shumiao , Wang Xiaodan , Chen Wende
Published: July 2023

Tree growth is under the combined influence of abiotic and biotic factors. Trees with different sizes may respond differently to these factors, implying that tree size heterogeneity may also modulate the overall growth trend. To test this hypothesis, we focused on the radial growth trends of natural subalpine forests on the Tibetan Plateau. We first extended the iterative growth model (IGM) to the tree ring scale (IGMR) to test the applicability of the generalized metabolic growth theory to tree growth. As predicted by the IGMR, the radial growth of trees at the aggregate scale is constrained by a unimodal pattern. Using the IGMR, we reconstructed the historical best growth trajectory (HBGT) of trees within the same community based on the tree with the largest radius and/or longest age in the community. From the average difference between the HBGT and the current radial growth rate of trees with different sizes, we constructed an indicator that can measure the overall variation in tree radial growth. Based on this indicator, we found a negative effect of tree size heterogeneity on the overall variability of tree growth across elevations. Further analysis also revealed that the radial growth rate of trees on the Tibetan Plateau has increased significantly compared to the past, where the growing season average temperature and annual minimum temperature were negatively and positively correlated with tree growth below and above the treeline, respectively. Our study not only confirmed that the overall variability of tree growth depends on tree size heterogeneity but also proposed an indicator that reveals net changes in the tree radial growth rate relative to the past. These theoretical advances are highly beneficial for understanding changes in the extent of subalpine forests.
Detection of Forestry Pests Based on Improved YOLOv5 and Transfer Learning
Authors: Liu Dayang , Lv Feng , Guo Jingtao , Zhang Huiting , Zhu Liangkuan
Published: July 2023

Infestations or parasitism by forestry pests can lead to adverse consequences for tree growth, development, and overall tree quality, ultimately resulting in ecological degradation. The identification and localization of forestry pests are of utmost importance for effective pest control within forest ecosystems. To tackle the challenges posed by variations in pest poses and similarities between different classes, this study introduced a novel end-to-end pest detection algorithm that leverages deep convolutional neural networks (CNNs) and a transfer learning technique. The basic architecture of the method is YOLOv5s, and the C2f module is adopted to replace part of the C3 module to obtain richer gradient information. In addition, the DyHead module is applied to improve the size, task, and spatial awareness of the model. To optimize network parameters and enhance pest detection ability, the model is initially trained using an agricultural pest dataset and subsequently fine-tuned with the forestry pest dataset. A comparative analysis was performed between the proposed method and other mainstream target detection approaches, including YOLOv4-Tiny, YOLOv6, YOLOv7, YOLOv8, and Faster RCNN. The experimental results demonstrated impressive performance in detecting 31 types of forestry pests, achieving a detection precision of 98.1%, recall of 97.5%, and mAP@.5:.95 of 88.1%. Significantly, our method outperforms all the compared target detection methods, showcasing a minimum improvement of 2.1% in mAP@.5:.95. The model has shown robustness and effectiveness in accurately detecting various pests.
Enhanced CO2 Reduction by Electron Shuttle Molecules via Coupling Different Electron Transport Processes in Microbial Electrosynthesis
Authors: Zhang Jie , Liu He , Zhang Yan , Fu Bo , Zhang Chao , Cui Minhua , Wu Ping , Chen Chongjun
Published: July 2023

Electron shuttling molecules (ESMs) have been proven to accelerate the electron transfer from the electrode to the electroactive microorganism in microbial electrosynthesis (MES) for higher CO2 reduction or chemical production rate. However, the microbial electron acceptors of electroactive microorganisms and their responses to different electron shuttling molecules in MES were still unknown. In this study, three kinds of ESMs, e.g., riboflavin (B2), methyl viologen (MV) and neutral red (NR) were applied in the MES for acetate production to explore the mechanism of different ESMs on microbial interactions. The acetate concentrations were 41% and 51% higher than that of the control in B2 and NR addition. The acetogens relative abundances of control, B2, MV and NR were 0.29%, 5.68%, 22.78% and 42.89%, respectively. The microbial function profile of the microbial community on the biocathodes indicated that the performance of acetate production was more closely related to the expression of electron transport. The B2 was coupled with the NADH complex and hydrogenase, while MV and NR were coupled with the Rnf complex to support electron transfer and energy conversion via various electron transfer pathways. The study revealed that the ESMs coupled with different electron transport complexes of microorganisms to achieve electron transfer, resulting in product changes.
Autochthonous Microbes to Produce Ligurian Taggiasca Olives (Imperia, Liguria, NW Italy) in Brine
Authors: Cecchi Grazia , Di Piazza Simone , Rosa Ester , De Vecchis Furio , Silvagno Milena Sara , Rombi Junio Valerio , Tiso Micaela , Zotti Mirca
Published: July 2023

Table olives are considered high-quality food, and Italy has a wealth of varieties and typical features that are truly unique in the world (about eighty cultivars of table olives or dual-purpose olives, four of which are protected by the protected designation of origin—PDO), and it is the second largest European consumer, behind Spain. The Taggiasca olive does not have a PDO, but it is very appreciated not only in the region of production (Liguria), but also in all the Italian regions and abroad. Autochthonous microbes (bacteria, yeasts, and filamentous fungi) are essential in the fermentative processes for brine olive production. However, these microbial communities that colonised the olive drupes are affected by the environmental conditions and the fermentation treatments. Hence the importance of studying and comparing olive microbes from different farms and investigating the relationships between bacteria, yeasts, and filamentous fungi to speed up the deamarisation process. Our results showed that yeasts are dominant relative to lactobacteria in all three brines studied, and Wickerhamomyces anomalus was the most performant fungus for the oleuropein degradation. The latter represents the best candidate for the realisation of a microbial starter.