bluuebunny/crossref_metadata_2025 huggingface dataset:
An Innovative Coded Language for Transferring Data via a Haptic Thermal Interface
Authors: Shani Yosef Y. , Lineykin Simon
Published: February 2025

The objective of this research was to develop a coded language, similarly to Morse or Braille, via a haptic thermal interface. The method is based on the human thermal sense to receive and decode the messages, and is to be used as an alternative or complementary channel for various scenarios in which conventional channels are not applicable or not sufficient (e.g., communication with the handicapped or in noisy/silent environments). For the method to be effective, it must include a large variety of short recognizable cues. Hence, we designed twenty-two temporally short (<3 s) cues, each composed of a sequence of thermal pulses, meaning a combination of warm and/or cool pulses with several levels of intensity. The thermal cues were generated using specially designed equipment in a laboratory environment and displayed in random order to eleven independent participants. The participants identified all 22 cues with 95% accuracy, and 16 of them with 98.3% accuracy. These results reflect extraordinary reliability, indicating that this method can be used to create an effective innovative capability. It has many potential implications and is applicable immediately in the development of a new communication capability, either as a single-modality thermal interface, or combined with tactile sensing to form a full haptic multisensory interface. This report presents the testing and evaluating process of the proposed set of thermal cues and lays out directions for possible implementation and further investigations.
The New Occurrence of Antiphospholipid Syndrome in Severe COVID-19 Cases with Pneumonia and Vascular Thrombosis Could Explain the Post-COVID Syndrome
Authors: Zlatković-Švenda Mirjana , Rašić Melanija , Ovuka Milica , Pavlov-Dolijanović Slavica , Atanasković Popović Marija , Ogrič Manca , Žigon Polona , Sodin-Šemrl Snežna , Zdravković Marija , Radunović Goran
Published: February 2025

Introduction: The classification of antiphospholipid syndrome (APS) comprises clinical criteria (vascular thrombosis or obstetric complications throughout life) and laboratory criteria (antiphospholipid antibodies (aPLs) positivity, confirmed at least twice at 12-week interval). Methods: In 100 patients admitted to the hospital with COVID-19 pneumonia, thrombosis and pregnancy complications were recorded during the hospital stay and in personal medical history. They were tested for nine types of aPLs at four time points (admission, deterioration, discharge, and 3-month follow-up): anticardiolipin (aCL), anti-β2-glycoproteinI (anti-β2GPI), and antiphosphatidylserine/prothrombin (aPS/PT) isotypes IgM/IgG/IgA. Results: During hospitalization, aPLs were detected at least once in 51% of patients. All 7% of deceased patients tested negative for aPLs upon admission, and only one patient became aCL IgG positive as his condition worsened. In 83.3% of patients, intrahospital thrombosis was not related to aPLs. One patient with pulmonary artery and cerebral artery thrombosis was given an APS diagnosis (triple aPLs positivity on admission, double on follow-up). Personal anamnesis (PA) for thromboembolism was verified in 10 patients, all of whom tested negative for aPLs at admission; however, transition to aPLs positivity at discharge (as the disease subsided) was seen in 60% of patients: three of six with arterial thrombosis (at follow-up, two did not appear, and one was negativized) and three of four with deep vein thrombosis (one was confirmed at follow-up and diagnosed with APS, one was negativized, and one did not appear). At admission, the majority of the aPLs were of the aCL IgG class (58.8%). Unexpectedly, as the COVID-19 disease decreased, anti-β2GPI IgG antibodies (linked with thromboses) became newly positive at discharge (14.9%), as confirmed at follow-up (20.8%). Conclusion: The incidence of APS in our cohort was 2.0%, whereas in the general population, it ranges from 0.001% to 0.002%. The incidence might have increased even more if the four aPLs-positive patients with intrahospital thrombosis/history of thrombosis had attended follow-up. Recommendation: All patients with severe COVID-19 or post-COVID syndrome should be evaluated for current/previous thrombosis and tested for aPLs at least twice: at admission to the hospital and at discharge, then retested 3 months later in positive cases in order to be given the appropriate therapy.
Perspectives, Challenges, and Advances in Therapeutic Strategies for Gynecological Malignant Tumors
Authors: Farolfi Alberto , Montanari Daniela , Casadei Chiara , Musolino Antonino
Published: February 2025

For years, treatment options for advanced gynecological malignancies have been limited, with the combination of carboplatin and paclitaxel being the preferred first-line therapeutic approach, regardless of disease type [...]
Prognostic Value of Pretreatment 18F-FDG-PET/CT Metabolic Parameters in Advanced High-Grade Serous Ovarian Cancer
Authors: Travaglio Morales Daniela , Coronado Poggio Mónica , Huerga Cabrerizo Carlos , Losantos García Itsaso , Escabias del Pozo Cristina , Lancha Hernández Carmen , Rodado Marina Sonia , Domínguez Gadea Luis
Published: February 2025

Aim: To assess the prognostic value of pretreatment 18F-FDG-PET/CT quantitative metabolic parameters in patients with advanced high-grade serous ovarian cancer (HGSOC). Methods: A review of 47 patients diagnosed with advanced HGSOC between 2012 and 2020 in our center was performed, evaluating pretreatment 18F-FDG-PET/CT metabolic parameters: maximum standardized uptake value (SUVmax), total lesion glycolysis (TLG) and metabolic tumoral volume (MTV). Two experienced nuclear medicine physicians evaluated the images, thereby obtaining quantitative parameters semiautomatically classifying the volume of interest (VOI) as the target (t): VOI with the highest SUVmax normalized by lean body mass (SUVmax(lbm)), non target (nt) and total (sum of target and non-target VOIs). The disease-free survival (DFS) and overall survival (OS) were calculated. Optimal cutoff values with ROC curves/median values were used. The Correlation between metabolic parameters and DFS/OS was determined using univariate and survival-curves analysis. Results: The median DFS was 18 months (2.5–55) and the OS 33.6 months (2.5–92). The MTVtotal, MTV(t), TLGtotal and TLG(t) were significantly associated with DFS (p = 0.005, 0.01, 0.04 and 0.04, respectively). The patients with MTVtotal > 427.8 cm3 and MTVtarget > 434 cm3 had shorter DFS than the patients with lower values (18.8 versus 31 months and 15.6 versus 30, p = 0.02 and 0.01, respectively). The patients with higher TLGtotal and TLG(t) values tended to have worse DFS (p = 0.26 and 0.31, respectively). In a multivariate analysis, the MTVtotal was statistically significantly associated with DFS (p = 0.003). No correlation was found with OS. Conclusions: Pretreatment MTVtotal and MTV(t) appear to be predictive of relapse in patients with advanced HGSOC.
Therapy Combining Sorafenib and Natural Killer Cells for Hepatocellular Carcinoma: Insights from Magnetic Resonance Imaging and Histological Analyses
Authors: Zhang Zigeng , Yu Guangbo , Eresen Aydin , Hou Qiaoming , Webster Sha , Amirrad Farideh , Nauli Surya , Zhang Zhuoli
Published: February 2025

Background/Objectives: Hepatocellular carcinoma (HCC) remains a significant global health issue due to its high mortality rate and resistance to standard treatments. Sorafenib, the first-line systemic therapy for unresectable HCC, shows limited effectiveness due to resistance and severe side effects. Recent studies suggest that combining sorafenib with immunotherapy, particularly natural killer (NK) cells, may improve treatment outcomes. Methods: This study examined the effectiveness of sorafenib combined with NK cells pretreated with interleukin-12 (IL-12) and interleukin-18 (IL-18) in a rat HCC model. Tumor progression and treatment outcomes were assessed using MRI and histological analysis. Results: The results show that combination therapy significantly reduced tumor growth, increased tumor cell density, and inhibited angiogenesis and fibrosis in the tumor microenvironment. The sorafenib- and IL-12/IL-18-pretreated NK cell combination enhanced tumor inhibition by overcoming drug resistance and modulating the immune response. Conclusions: This study suggests that this combination therapy could be a promising strategy for treating HCC, offering both direct antitumor effects and modification of the tumor microenvironment for better clinical outcomes.
Non-Melanoma Skin Cancer: Assessing the Systemic Burden of the Disease
Authors: Karampinis Emmanouil , Koumaki Dimitra , Sgouros Dimitrios , Nechalioti Paraskevi-Maria , Toli Olga , Pappa Georgia , Papadakis Marios , Georgopoulou Konstantina-Eirini , Schulze-Roussaki Angeliki-Victoria , Kouretas Demetrios
Published: February 2025

The emergence of systemic therapies and photoprotection against non-melanoma skin cancer (NMSC) raises questions on the broader systematic impact of the disease. Personalized medicine involves a holistic patient approach, through which the evaluation of systemic biomarkers can reveal the interconnected aspects of patient health and tailored therapies. Cumulative UV exposure disrupts redox equilibrium and triggers inflammation and cutaneous immunosuppression, processes that contribute independently or via their interplay to cutaneous carcinogenesis. This systemic impact can be further reinforced by biomolecules derived from the NMSC microenvironment, fueling a continuous cycle of oxidative stress and inflammation in the organism. Regarding investigation of the systemic burden of NMSC, we conducted a narrative review focusing on parameters related to redox status, inflammation, and immune suppression observed in the blood components (serum, plasma, and erythrocytes) of NMSC patients. Our findings revealed an association of NMSC patients with perturbations of redox homeostasis, as evidenced by the decreased antioxidant activity, lower levels of non-enzymatic antioxidants, and increased byproducts of lipid, protein, and DNA oxidative damage. Additionally, NMSC patients presented augmented levels of pro-inflammatory interleukins, reduced anti-tumor biomolecule levels, and enhanced immune response markers, as well as elevated vitamin D levels. These systemic changes may lead to the association of NMSC with a higher risk of secondary malignancies in other organs. Overall, the findings of the present study suggest that NMSC affects systemic health beyond the skin, underscoring the need for a comprehensive and individualized approach to the management and monitoring of the patient.
Recent Anti-KRASG12D Therapies: A “Possible Impossibility” for Pancreatic Ductal Adenocarcinoma
Authors: Sobhani Navid , Pittacolo Matteo , D’Angelo Alberto , Marchegiani Giovanni
Published: February 2025

Background: Pancreatic ductal adenocarcinoma (PDAC) is an aggressive cancer, able to thrive in a challenging tumor microenvironment. Current standard therapies, including surgery, radiation, chemotherapy, and chemoradiation, have shown a dismal survival prognosis, resulting in less than a year of life in the metastatic setting. Methods: The pressing need to find better therapeutic methods brought about the discovery of new targeted therapies against the infamous KRAS mutations, the major oncological drivers of PDAC. Results: The most common KRAS mutation is KRASG12D, which causes a conformational change in the protein that constitutively activates downstream signaling pathways driving cancer hallmarks. Novel anti-KRASG12D therapies have been developed for solid-organ tumors, including small compounds, pan-RAS inhibitors, protease inhibitors, chimeric T cell receptors, and therapeutic vaccines. Conclusions: This comprehensive review summarizes current knowledge on the biology of KRAS-driven PDAC, the latest therapeutic options that have been experimentally validated, and developments in ongoing clinical trials.
Correlation of GNAS Mutational Status with Oncologic Outcomes in Patients with Resected Intraductal Papillary Mucinous Neoplasms
Authors: Evans Julia , Shivok Kylee , Chen Hui Hsuan , Gorgov Eliyahu , Bowne Wilbur B. , Jain Aditi , Lavu Harish , Yeo Charles J. , Nevler Avinoam
Published: February 2025

Background: Intraductal papillary mucinous neoplasms (IPMNs) are pre-malignant pancreatic lesions that may progress to invasive pancreatic ductal adenocarcinoma (PDAC). IPMN-associated invasive carcinoma (iIPMN) has been associated with more favorable survival outcomes compared to non-iIPMN-derived PDAC. Here, we aim to investigate the genetic landscape of IPMNs to assess their relevance to oncologic outcomes. Methods: This retrospective study used a large single-institution prospectively maintained database. Patients who underwent curative-intent pancreatic resection between 2016 and 2022 with histologically confirmed diagnosis of IPMN were included. Demographic, pathologic, molecular, and oncologic outcome data were recorded. Kaplan–Meier survival analyses were performed. PDAC data from public genetic databases were used for mutational correlation analysis. p-value ≤ 0.05 was considered as significant. Results: A total of thirty-nine patients with resected IPMN with complete clinical and sequencing data were identified and included in the final cohort. The male-to-female distribution was 21:18, and the mean age was 70.1 ± 9.1 years. GNAS mutations occurred in 23.1% of patients, and 89.7% of patients had iIPMN. In iIPMN patients, GNAS mutation was strongly associated with improved disease-free survival: all GNAS-mutant patients survived to follow-up with significantly fewer recurrences than in GNAS wild-type (WT) patients (p = 0.013). Mutated GNAS closely co-occurred with wild-type KRAS (p < 0.001), and further analysis of large genomic PDAC datasets validated this finding (OR 3.47, p < 0.0001). Conclusions: Our study suggests prognostic value of mutational status in malignant resected IPMNs. WT GNAS, mutant P53, and mutant KRAS each correlate with recurrence and decreased survival. Further studies are required to validate these preliminary observations.
Clinical Approaches for the Management of Skin Cancer: A Review of Current Progress in Diagnosis, Treatment, and Prognosis for Patients with Melanoma
Authors: Connor Colton , Carr Quinton L. , Sweazy Alisa , McMasters Kelly , Hao Hongying
Published: February 2025

Melanoma represents a significant public health challenge due to its increasing incidence and potential for metastasis. This review will explore the current clinical approaches to the management of melanoma, focusing on advancements in diagnosis, treatment, and prognosis. Methods for early detection and accurate staging have been enhanced by new diagnostic strategies. Treatment modalities have expanded beyond traditional surgical excision to include targeted therapy and immunotherapy. Prognostic assessment has benefited from the development of novel biomarkers and genetic profiling. This review will highlight the progress made in the multidisciplinary management of melanoma, underscoring the importance of continuous research to improve patient outcomes.
Rotavirus Spreads in a Spatially Controlled Manner
Authors: Passarelli Gianna V. , Doldan Patricio , Metz-Zumaran Camila , Keser Yagmur , Boulant Steeve , Stanifer Megan L.
Published: February 2025

Rotavirus is an enteric virus that leads to 200,000 deaths worldwide every year. The live-cell imaging evaluating rotavirus infection of MA104 cells revealed that rotavirus replication and spread occurs in a spatially controlled manner. Specifically, following initial rotavirus infection, the infected cells die, and the second round of infection occurs in the restricted area surrounding the initially infected cell. Interestingly, we found that the time required to establish the secondary infection is shorter compared to the time required for the initial infection. To determine if this increase in the kinetic of secondary infection was due to the early release of viruses or priming of the cells that are infected during the secondary infection, we used a combination of live-cell microscopy, trypsin neutralization assays, and the pharmacological inhibition of calcium signaling. Together, our results show that the second round of infection required rotavirus to be released and accessible to extracellular proteases. In addition, we found that the calcium wave induced upon rotavirus infection was critical for initial infection but did not play a role in the establishment of a secondary infection. Finally, we uncovered that high viral titers released from the initial infection were sufficient to accelerate the rate of the secondary infection.
Elucidation of Factors Affecting Anterior Occlusion in Primary Dentition Based on the Japan Environment and Children’s Study
Authors: Ishiko Risa , Sena Kotaro , Koseki Ichie , Sasai Masumi , Ota Chiharu , Koseki Takeyoshi
Published: February 2025

Background/Objectives: Malocclusion in primary dentition affects permanent dentition. However, the factors contributing to malocclusion in the oral cavities of children have not been fully elucidated. We hypothesized that environmental factors affect malocclusion in the primary dentition of the Japanese population and aimed to identify factors associated with anterior occlusion in primary dentition. Methods: The study involved 3793 parent–child pairs from the Miyagi Regional Centre as part of a supplementary survey to the Japan Environment and Children’s Study, a cohort study. A questionnaire assessing oral development and environmental factors was administered to parent-child pairs who consented to participate. Parents assessed anterior occlusion when their children were 3.5 years old. Results: The maxillary primary central incisors tended to erupt earlier in the open bite group. Significantly more children in this group were breastfed until 1 year and drank ionic beverages at 1.5 years. In addition, thumb sucking or pacifier use was significantly common at 2 years of age. A correlation was observed between the mother’s body mass index (BMI) before and after pregnancy and anterior occlusion. Conclusions: In the open bite group, the occlusion status of the anterior teeth at 3.5 years of age showed distinctive results influenced by the eruption period of the primary anterior teeth, oral habits, intake of sweetened beverages, and maternal BMI. These findings suggest that parental observation could be useful for screening children for malocclusion until the eruption of permanent dentition.
Reduced-Order Models and Conditional Expectation: Analysing Parametric Low-Order Approximations
Authors: Matthies Hermann G.
Published: February 2025

Systems may depend on parameters that can be controlled, serve to optimise the system, are imposed externally, or are uncertain. This last case is taken as the “Leitmotiv” for the following discussion.A reduced-order model is produced from the full-order model through some kind of projection onto a relatively low-dimensional manifold or subspace. The parameter-dependent reduction process produces a function mapping the parameters to the manifold.One now wants to examine the relation between the full and the reduced state for all possible parameter values of interest. Similarly, in the field of machine learning, a function mapping the parameter set to the image space of the machine learning model is learned from a training set of samples, typically minimising the mean square error. This set may be seen as a sample from some probability distribution, and thus the training is an approximate computation of the expectation, giving an approximation of the conditional expectation—a special case of Bayesian updating, where the Bayesian loss function is the mean square error. This offers the possibility of having a combined view of these methods and also of introducing more general loss functions.
Reporting Wandering Dogs to Protect Kiwi and Dogs: New Zealanders’ Involvement, Attitudes, and Beliefs
Authors: Macaskill Anne C. , Kaine Geoff , Aley Joanne P.
Published: February 2025

Wandering dogs are a threat to Aotearoa New Zealand’s endemic kiwi bird species because kiwi have not evolved defenses against mammalian predators. New Zealanders can protect kiwi by reporting wandering dogs, and this also protects the dogs themselves. This study explored New Zealanders’ reporting intentions and behavior, as well as attitudes and beliefs about wandering dogs, harm to kiwi, and dog welfare. Guided by the I3 framework, we also assessed respondents’ involvement with the intervention of reporting, and involvement with both dog welfare and kiwi welfare. A sample of 250 New Zealanders completed the questionnaire online. Attitudes and behavior were consistent with involvement, and patterns for involvement with kiwi welfare and involvement with dog welfare were similar. The results indicated that almost all respondents fell into one of two quadrants based on involvement—both quadrants were highly involved with dog and kiwi welfare but varied on involvement with reporting. This pattern suggests that promotion campaigns are likely to be an effective intervention to increase the reporting of wandering dogs. Promotional campaigns might focus on dog welfare or kiwi welfare, and should highlight the link between reporting, dogs, and harm to kiwi.
Preparation of Titanium Oxycarbide from Ilmenite (FeTiO3) Concentrate Through Thermal Reduction and Magnetic Separation Processes
Authors: Zhu Fuxing , Deng Bin , Huang Zhipeng , Yang Song , Li Kaihua , Mu Tianzhu , Lv Xueming
Published: February 2025

Ilmenite concentrate has emerged as the key titanium raw material for exploitation and utilization, playing a crucial role in the preparation of metallic titanium and titanium dioxide. However, the presence of impurities such as Fe, Ca, and Mg in ilmenite concentrate severely restricts its economic utilization and environmentally friendly applications. In our previous research, a novel process was proposed to prepare TiCl4 from high-Ca- and Mg-containing ilmenite through carbothermal reduction and boiling chlorination. Nevertheless, the employment of graphite as a reducing agent and hydrochloric acid for metallic iron separation led to elevated production costs. The aim of this study was to explore an alternative and more cost-effective method. Petroleum-derived coke was used as the reducing agent to investigate the feasibility of producing titanium oxycarbide from ilmenite concentrate via carbothermal reduction and magnetic separation. The results showed that petroleum-derived coke is capable of reducing ilmenite concentrate to coral-shaped TiCxOy under high-temperature conditions. However, an approximate 100 °C increment in temperature is required to reach an equivalent reduction efficiency compared with graphite. The X-ray diffraction (XRD) analysis results of the reduced products reveal that complete reduction of ilmenite concentrate by petroleum-derived coke can only be achieved when the reduction process is conducted at 1600 °C for 3 h or at 1500 °C for 5 h. The reduced product obtained at 1600 °C, characterized by a substantial presence of dense Ti2O3, exhibits a significantly coarser particle size after 30 minutes of ball milling in contrast to the reduced product obtained at 1200 °C, which is rich in M3O5 anosovite. Magnetic separation results showed that the reduction product at 1200 °C could not have metallic iron removed by magnetic separation at 1.2 T, while the reduction product at 1600 °C could yield a non-magnetic charge rich in Ti2O3 and TiCxOy with an iron content as low as 2 ± 0.03 wt.%, which fully meets the requirements for producing TiCl4 by boiling chlorination. Overall, these research results offer a new approach for the low-cost production of TiCl4 from ilmenite concentrate with high levels of Ca and Mg impurities through boiling chlorination.
Association Between Mandibular Cortical Erosion and Bone Mineral Density Assessed by Phalangeal Ultrasound and Dual Energy X-Ray Absorptiometry in Spanish Women
Authors: Canal-Macías Maria L. , Vera-Rodríguez Vicente , Leal-Hernández Olga , Calderón-García Julián Fernando , Roncero-Martín Raúl , García-Blázquez Francisco , Rico-Martín Sergio , López-Espuela Fidel , Morán José M. , Fabregat-Fernández Juan , Lavado-García Jesús M. , Pedrera-Canal María
Published: February 2025

Background and Objectives: Analysing the characteristics of the mandibular bone through panoramic radiographs could be useful as a prescreening tool for detecting individuals with osteoporosis. The aims of this study were to evaluate the possible associations between the mandibular cortical index (MCI) and bone mineral density (BMD) in various bone regions, to investigate whether BMD better identifies moderate–severe mandibular erosion or severe mandibular erosion, and to establish BMD cut-off points to identify individuals with moderate or severe mandibular cortical erosion. Methods: This study analysed 179 Spanish Caucasian women between September 2021 and June 2024. Bone measurements, including amplitude-dependent speed of sound (Ad-SOS), the ultrasound bone profiler index (UBPI), and the bone transmission time (BTT), were obtained via dual energy X-ray absorptiometry (DXA) for the femoral neck, lumbar spine, and trochanter and quantitative bone ultrasound (QUS) for the phalanx. The MCI was calculated via the Klemetti index from panoramic radiographs. Results: According to the Klemetti index classification, lower QUS measurements in the phalanx and DXA measurements in the femoral neck, trochanter, and lumbar spine were found in women with poorer mandibular cortical bone quality. Our results revealed that, compared with moderate cortical erosion, all the BMD measures had better AUCs when identifying severe cortical erosion. Moreover, femoral neck BMD had the largest area under the curve (AUC = 0.719) for detecting severe mandibular cortical erosion, suggesting a cut-off of <0.703 gr/cm2. Finally, predictor analysis of osteoporosis revealed that moderate and severe mandibular cortical erosion, compared with an uninjured mandibular cortical area, was independently associated with a diagnosis of osteoporosis. Conclusions: In conclusion, MCI was associated with BMD measurements assessed by QUS and DXA in various bone regions. Our results suggest that the Klemetti index could be used as a predictor of osteoporosis and fracture risk.
Evaluation of the Disinfection Efficacy of Er: YAG Laser Light on Single-Species Candida Biofilms—An In Vitro Study
Authors: Dembicka-Mączka Diana , Kępa Małgorzata , Fiegler-Rudol Jakub , Grzech-Leśniak Zuzanna , Matys Jacek , Grzech-Leśniak Kinga , Wiench Rafał
Published: February 2025

Background/Objectives: Oral candidiasis is an opportunistic infection caused by Candida species. Recently, antifungal drugs have become less effective due to yeast resistance, emphasizing the need for new treatment strategies. This study aimed to assess the effect of the Er:YAG laser on the inhibition of growth and elimination of mature single-species Candida biofilms. Methods: The study utilized reference strains of C. albicans, C. glabrata, C. parapsilosis, and C. krusei organized in single-species biofilms on Sabouraud dextrose agar (SDA). First part: Candida suspensions (0.5 McFarland standard) were spread on SDA plates—two for each strain. Er:YAG laser irradiation was applied in a single pulse mode, 30 to 400 mJ, to 32 predetermined points. The growth inhibition zones (GIZs) were measured at 24–96 h of incubation. Second part: biofilms were prepared similarly and, after 96 h of incubation, exposed to Er:YAG laser irradiation at different energies (50, 100, 150, 200 mJ) for 180 s, per 1.44 cm area. Post-irradiation, impressions were taken using Rodac Agar to determine yeast counts. The count of colony-forming units (CFU) after irradiation was measured and results were analysed statistically. Results: First part: GIZ was found in all irradiated sites, with various Candida strains. The results showed a significant increase in the width of GIZ in the energy range of 30–280 mJ and a non-significant increase in the energy range of 300–400 mJ. Second part: the number of CFU remaining after the irradiation of biofilms with 150 mJ energy differed statistically significantly from other results obtained after using 50, 100, or 200 mJ energy, regardless of the Candida strain tested. Conclusions: The Er:YAG is shown to have good disinfecting properties (inhibiting biofilm growth, even at low-energy doses (50 mJ), and eliminating maturity, Candida spp. biofilms most effective on the 150 mJ energy dose).
Fault Root Cause Analysis Based on Liang–Kleeman Information Flow and Graphical Lasso
Authors: Liu Xiangdong , Liu Jie , Yang Xiaohua , Wu Zhiqiang , Wei Ying , Xu Zhuoran , Wen Juan
Published: February 2025

Root cause analysis is used to find the specific fault location and cause of a fault during system fault diagnosis. It is an important step in fault diagnosis. The root cause analysis method based on causality starts from the origin of the causal connection between transactions and infers the location and cause of the mechanism failure by analyzing the causal impact of variables between systems, which has methodological advantages. Causal analysis methods based on transfer entropy are proven to have biases in calculation results, so there is a phenomenon of calculating false causal relationships, which leads to the problem of insufficient accuracy in root cause analysis. Liang–Kleeman information flow (LKIF) is a kind of information entropy that can effectively carry out causal inference, which can avoid obtaining wrong causal relationships. We propose a root cause analysis method that combines graphical lasso and information flow. In view of the large amount of redundant information in industrial data due to the coupling effect of industrial systems, graphical lasso (Glasso) is a high-precision dimensionality reduction method suitable for large-scale and high-dimensional datasets. To ensure the timeliness of root cause analysis, graphical lasso uses dimensionality reduction of the data. Then, LKIF is used to calculate the information flow intensity of each relevant variable, infer the causal relationship between the variable pairs, and trace the root cause of the fault. On the Tennessee Eastman simulation platform, root cause analysis was performed on all faults, and two root cause analysis solutions, transfer entropy and information flow, were compared. Experimental results show that the LKIF–Glasso method can effectively detect the root cause of faults and display the propagation of faults throughout the process. It further shows that information flow has a better effect in root cause analysis than transfer entropy. And through the root cause analysis of the step failure of the stripper, the reason why information flow is superior to transfer entropy is explained in detail.
Exploring the Instructional Effectiveness of High-Growth K-2 Teacher Teams in Foundational Reading
Authors: Downs Jake , Martz Katie , Mohr Kathleen
Published: February 2025

This study examined high-performing teacher teams in Title I elementary schools that demonstrated significant student growth in foundational reading skills. Using an explanatory sequential mixed-methods design, we identified K-2-grade-level teams within a district with the highest growth on Acadience Reading. The study explored (1) student growth and proficiency outcomes in these high-growth teams and (2) how teachers described their instructional practices and outcomes. Focus group interviews were conducted, and thematic analysis revealed key factors, including collaboration, data responsiveness, professional development, and content/pedagogical knowledge. Recommendations and directions for future research are discussed.
Data-Driven Distributionally Robust Optimal Power Flow for Distribution Grids Under Wasserstein Ambiguity Sets
Authors: Liu Fangzhou , Huo Jincheng , Liu Fengfeng , Li Dongliang , Xue Dong
Published: February 2025

The increasing integration of distributed energy resources into distribution feeders introduces significant uncertainties, stemming from volatile renewable sources and other fluctuating electrical elements, which pose substantial challenges for optimal power flow (OPF) analysis. This paper introduces a data-driven distributionally robust chance-constrained (DRCC) approach to address the stochastic Alternating Current (AC) OPF problem in distribution grids, where the exact probability distributions of uncertainties are unknown. The proposed method utilizes the Wasserstein metric to construct an ambiguity set based on empirical distributions derived from historical data, eliminating the need for prior knowledge of the underlying probability distributions. Notably, the size of the Wasserstein ball within the ambiguity set is inversely related to the volume of available data, allowing for adaptive robustness. Moreover, a computationally efficient reformulation of the DRCC-OPF model is developed using the LinDistFlow AC power flow approximation. The effectiveness and precision of the developed method are validated through multiple IEEE distribution test cases, demonstrating higher reliability of the security constraints compared with other methods. As more data become available, this reliability is systematically and securely adjusted to achieve greater economic efficiency.
Transient Stability Analysis and Emergency Generator Tripping Control Based on Spatio-Temporal Graph Deep Learning
Authors: Wang Shuaibo , Zeng Jie , Zhang Jie , Liang Zhuohang , Zhu Yihua , Li Shufang
Published: February 2025

This paper addresses the challenge of achieving fast and accurate transient stability analysis and emergency control in power systems, which are crucial for reliable grid operation under disturbances. To this end, we propose a spatio-temporal graph deep learning approach leveraging Diffusion Convolutional Gated Recurrent Units (DCGRUs) for transient stability assessment and coherent generator group prediction. Unlike traditional methods, our approach explicitly represents transient responses as spatio-temporal graph data, capturing both topological and dynamic dependencies. The DCGRU model effectively extracts these features, and the predicted coherent generator groups are incorporated into the single-machine infinite-bus equivalence method to design an emergency generator tripping scheme. Simulation analysis results on both benchmark and real-world power grids validate the proposed method’s feasibility and effectiveness in enhancing transient stability analysis and emergency control.
Deep-Fuzzy Logic Control for Optimal Energy Management: A Predictive and Adaptive Framework for Grid-Connected Microgrids
Authors: Cavus Muhammed , Dissanayake Dilum , Bell Margaret
Published: February 2025

This paper introduces a novel energy management framework, Deep-Fuzzy Logic Control (Deep-FLC), which combines predictive modelling using Long Short-Term Memory (LSTM) networks with adaptive fuzzy logic to optimise energy allocation, minimise grid dependency, and preserve battery health in grid-connected microgrid (MG) systems. Integrating LSTM-based predictions provides foresight into system parameters such as state of charge, load demand, and battery health, while fuzzy logic ensures real-time adaptive control. Results demonstrate that Deep-FLC achieves a 25.7% reduction in operational costs compared to the conventional system and a 17.5% saving cost over the Fuzzy Logic Control (FLC) system. Additionally, Deep-FLC delivers the highest battery efficiency of 61% and constraints depth of discharge to below 2% per time step, resulting in a reduction of the state of health degradation to less than 0.2% over 300 h. By combining predictive analytics with adaptive control, this study addresses the limitations of standalone approaches and establishes Deep-FLC as a robust, efficient, and sustainable energy management solution. Key novel contributions include the integration of advanced prediction mechanisms with fuzzy control and its application to battery-integrated grid-connected MG systems.
High Power Density IGBT Loss Calculation Model and Analysis
Authors: Wang Feng , Song Yifan , Dou Wang , Zheng Zhaolei , Li Zhuangzhuang , Li Biao , Liu Jun
Published: February 2025

This paper presents the establishment of an accurate loss model for high-power-density IGBT modules used in electric vehicles, leveraging the thermal simulation capabilities of the power electronics simulation software PLECS 4.1. The study aims to address the significant influence of IGBT losses on the energy efficiency and reliability of electric vehicles. A simulation model was built using the SVPWM modulation strategy to drive a three-phase inverter, and the average loss method was employed to determine both conduction and switching losses. The simulation results were compared with calculations based on the datasheet, showing a deviation of less than 4%. For instance, the actual conduction loss was found to be 7.988 W, compared to the theoretical calculation of 8.16 W, with a deviation of 2.15%. Similarly, the switching loss was 22.069 W, compared to the theoretical value of 22.447 W, with a deviation of 1.71%. These results confirm that the proposed model accurately predicts losses under specified conditions. Compared with traditional methods, the model presented in this paper offers higher precision and improved simulation speed, thus proving effective for accurate loss analysis of IGBT modules and supporting further energy efficiency improvement and system optimization in electric vehicles.
Development of a Digital System for Monitoring Emergency Conditions in 20 kV Distribution Networks
Authors: Baltin Alisher , Issenov Sultanbek , Nurmaganbetova Gulim , Zhumadirova Aliya , Yussupova Assel , Potapenko Alexandra , Maussymbayeva Aliya
Published: February 2025

This article presents research on the possibilities of using information and communication technologies in monitoring systems for electrical networks with isolated neutral, aimed at improving and automating production functions in the energy sector. This aligns with the digitalization policy of Kazakhstan’s economy and is part of similar programs in the field of the electric power industry. This article explores an approach to organizing a digital monitoring system for emergency conditions, specifically single-phase ground faults in medium-voltage lines within the range of 6–35 kV, including the new voltage class of 20 kV. A version of such a system is proposed, based on a combination of a server, a wireless information network, and remote digital voltage measurement nodes. This wireless information and communication network is designed to detect the locations of single-phase ground faults (SPGF) using specialized zero-sequence voltage sensors installed at various points along the power transmission lines, along with wireless signal transmission channels to the dispatcher’s server. To ensure protection against industrial interference, based on the results of practical environment modeling, a transmission technology most resistant to external noise is selected. This article proposes the selection of equipment necessary for implementing wireless transmission technology and develops two versions of a digital voltmeter design based on low-power programmable microcontrollers. The proposed technical solutions require further experimental validation, and therefore, the authors plan to conduct additional research and practical experiments in the future.
Machine Learning Algorithms and Nondestructive Methods for Estimating Wood Density in Planted Forest Trees
Authors: Lorensani Rafael Gustavo Mansini , Gonçalves Raquel
Published: February 2025

Inferring forest properties is crucial for the timber industry, enabling efficient monitoring, predictive analysis, and optimized management. Nondestructive testing (NDT) methods have proven to be valuable tools for achieving these goals. Recent advancements in data analysis, driven by machine learning (ML) algorithms, have revolutionized this field. This study analyzed 492 eucalyptus trees (Eucalyptus sp.), aged 3 to 7 years, planted in São Paulo, Brazil. Data from forest inventories were combined with results from ultrasound, drilling resistance, sclerometric impact, and penetration resistance tests. Seven machine learning algorithms were evaluated to compare their generalization capabilities with conventional statistical methods for predicting basic wood density. Among the models, extreme gradient boosting (XGBoost) achieved the highest accuracy, with a coefficient of determination (R2) of 89% and a root mean square error (RMSE) of 10.6 kg·m−3. In contrast, the conventional statistical model, using the same parameters, yielded an R2 of 33% and an RMSE of 26.4 kg·m−3. These findings highlight the superior performance of machine learning in the nondestructive inference of wood properties, paving the way for its broader application in forest management and the timber industry.
Robust Synthetic Data Generation for Sequential Financial Models Using Hybrid Variational Autoencoder–Markov Chain Monte Carlo Architectures
Authors: Bruni Prenestino Francesco , Barbierato Enrico , Gatti Alice
Published: February 2025

Generating high-quality synthetic data is essential for advancing machine learning applications in financial time series, where data scarcity and privacy concerns often pose significant challenges. This study proposes a novel hybrid architecture that combines variational autoencoders (VAEs) with Markov Chain Monte Carlo (MCMC) sampling to enhance the generation of robust synthetic sequential data. The model leverages Gated Recurrent Unit (GRU) layers for capturing long-term temporal dependencies and MCMC sampling for effective latent space exploration, ensuring high variability and accuracy. Experimental evaluations on datasets of Google, Tesla, and Nestlé stock prices demonstrate the model’s superior performance in preserving statistical and temporal patterns, as validated by quantitative metrics (discriminative and predictive scores), statistical tests (Kolmogorov–Smirnov), and t-Distributed Stochastic Neighbour Embedding (t-SNE) visualisations. The experiments reveal the model’s scalability, maintaining high fidelity even under augmented dataset sizes and missing data scenarios. These findings position the proposed framework as a computationally efficient and structurally simple alternative to Generative Adversarial Network (GAN)-based methods, suitable for real-world applications in data-driven financial modelling.
Methyltransferase HsdM Regulates the Pathogenicity of Streptococcus agalactiae to Nile Tilapia (Oreochromis niloticus)
Authors: Jiang Dongdong , Wang Bei , Ren Yan , Mo Xubing , Yu Meiling , Zhang Defeng
Published: February 2025

DNA methylation is a critical mechanism for regulating gene expression in bacteria and plays an essential role in bacterial pathogenesis. A mutant, WC1535ΔhsdM, lacking hsdM encoding a DNA methyltransferase was constructed using homologous recombination technology. The growth, hemolytic activity, and capsule formation of the mutant were analyzed. The dynamic distribution of the wild-type (WT) and mutant strains in tilapia tissues after artificial infection was determined. The adhesion, invasion, anti-phagocytic, and whole-blood survival abilities of the WT and mutant strains were analyzed. Tilapia were intraperitoneally injected with the WT or mutant strains, and the LD50 values were determined. The expression levels of the immune-related genes in tilapia were analyzed by qRT-PCR. The mutant showed faster growth during the logarithmic growth period (5–10 h) and lower hemolytic activity than the WT strain. Mutant loads in tilapia tissues were significantly lower than those of the WT strain. Mutant strain adhesion to epithelial cells was significantly reduced, it was more easily engulfed by macrophages, and it had decreased intracellular survival. The LD50 of the mutant was 2.06 times higher than that of the WT strain, indicating decreased pathogenicity. Expression levels of immune-related genes IL-1β, IL-6, IFN-γ, and TNF-α in tilapia induced by the mutant were lower than those by the WT strain. In conclusion, the WC1535ΔhsdM mutant exhibited an increased growth rate and decreased hemolytic activity, tissue colonization, and pathogenicity, indicating that HsdM could regulate S. agalactiae growth and pathogenicity. This study provides new insights into the pathogenesis of piscine S. agalactiae.
Has Finance Promoted High-Quality Development in China’s Fishery Economy?—A Perspective on Formal and Informal Finance
Authors: Ye Shengchao , Zhang Qian , Li Xiao , Yu Jianli , Wang Haohan
Published: February 2025

The high-quality development of China’s fishery economy serves as its core objective, with robust financial support playing a pivotal role. This study employs provincial panel data spanning 2005 to 2020 and utilizes the entropy method to evaluate the level of high-quality development in China’s fishery economy across three dimensions: fundamental security, sustainability, and comprehensive efficiency. From the perspectives of formal and informal finance, it compares their support effects on different aspects of high-quality development in China’s fishery economy, while also exploring the mechanisms underlying these effects by considering factors such as industrial uncertainty and economic scale. The findings indicate that, overall, the support provided by both formal and informal finance for high-quality development in the fishery economy is insufficient. Further analysis reveals a significant threshold effect of fishery economic scale, with turning points at 108.44 billion CNY and 232.98 billion CNY for formal and informal finance, respectively. For higher-level indicators, such as sustainability and comprehensive efficiency, formal and informal financial systems demonstrate complementary roles, depending on the scale of the regional fishery economy. Furthermore, industrial uncertainty serves as a significant mediating factor only for formal financial support, with the levels of sustainability and comprehensive efficiency most affected.