Search Results (59)

With the accelerated transition of the global energy structure towards decarbonization, the share of PV power generation in the power system continues to rise. IEA predicts PV will account for 80% of new global renewable installations during 2025–2030. However, latent faults emerging from the long-term operation of photovoltaic (PV) power plants significantly compromise their operational efficiency. The existing EL detection methods in PV plants face challenges including grain boundary interference, probe band artifacts, non-uniform luminescence, and complex backgrounds, which elevate the risk of missing small defects. In this paper, we propose a high-precision defect detection method based on BiFDRep-YOLOv8n for small target defects in photovoltaic (PV) power plants, aiming to improve the detection accuracy and real-time performance and to provide an efficient solution for the intelligent detection of PV power plants. Firstly, the visual transformer RepViT is constructed as the backbone network, based on the dual-path mechanism of Token Mixer and Channel Mixer, to achieve local feature extraction and global information modeling, and combined with the structural reparameterization technique, to enhance the sensitivity of detecting small defects. Secondly, for the multi-scale characteristics of defects, the neck network is optimized by introducing a bidirectional weighted feature pyramid network (BiFPN), which adopts an adaptive weight allocation strategy to enhance feature fusion and improve the characterization of defects at different scales. Finally, the detection head part uses DyHead-DCNv3, which combines the triple attention mechanism of scale, space, and task awareness, and introduces deformable convolution (DCNv3) to improve the modeling capability and detection accuracy of irregular defects. Full article

Background/Objectives: The bidirectional relationship between diabetes mellitus (DM) and periodontal disease (PD) has garnered increasing attention due to shared inflammatory mechanisms and mutual disease exacerbation. In Romania, despite a high prevalence of diabetes and PD, integration of oral health into diabetes care remains limited. This study aimed to investigate the association between glycemic control, salivary inflammatory biomarkers (IL-1β, IL-6, MMP-8), and periodontal status in diabetic patients. Additionally, it evaluated patients’ awareness of oral health risks and their communication with healthcare providers regarding periodontal care. Methods: A cross-sectional, observational study was conducted between May and December 2024, involving 79 adult patients with confirmed type 1 or type 2 DM. Periodontal examinations assessed probing pocket depth (PPD), clinical attachment level (CAL), plaque index (PI), and bleeding on probing (BOP). Salivary samples were collected to quantify IL-1β, IL-6, and MMP-8. Participants also completed a structured questionnaire on oral symptoms, hygiene practices, and awareness of the diabetes–periodontitis link. Correlation and t-test analyses were used to explore associations between clinical, biochemical, and self-reported variables. Results: Most participants had advanced periodontitis (65.8% Stage IV; 72.2% Grade C). IL-1β and IL-6 were positively correlated (r = 0.34, p < 0.01), while MMP-8 correlated with PI (r = 0.28) and BOP (r = 0.26). Inflammatory markers showed weak correlation with HbA1c. Notably, patients with higher oral health knowledge reported worse clinical indices, suggesting increased symptom awareness rather than preventive effectiveness. Conclusions: This study reinforces the inflammatory link between DM and PD and highlights the need for integrated care models. Periodontal screening and education should be embedded within diabetes management, particularly in high-risk populations. Full article

Background/Objectives: Diabetes mellitus and periodontitis share a significant, bidirectional relationship. Diabetes raises the risk of periodontitis and influences its severity, impacting tissue repair and bone metabolism. Conversely, periodontal inflammation can disrupt glycemic control, further complicating this interlinked relationship. This systematic review aimed to evaluate the efficacy of antimicrobial photodynamic therapy (aPDT) as an adjunct to subgingival instrumentation (SI) in the treatment of periodontal pockets with a probing pocket depth (PPD) ≥ 5 mm in individuals with type 2 diabetes mellitus (DM2) and periodontitis. Methods: Using the PICOS framework, this review addressed the following question: “How does aPDT as an adjunct to SI compare to SI alone in treating periodontal pockets with PPD ≥ 5 mm in individuals with DM2 and periodontitis?” Databases searched included PubMed, Scopus, and Web of Science up to December 2024. Randomized clinical trials evaluating periodontal status and HbA1c levels in patients with DM2 undergoing periodontal therapy and experiencing SI were included. Patients who received adjunctive aPDT were compared to a control group that received SI alone. A meta-analysis was conducted illustrating treatment effects across groups. Results: After screening 117 studies based on titles and abstracts, three and four studies met the eligibility criteria for quantitative and qualitative analyses, respectively. The principal periodontal parameters assessed included PPD, clinical attachment level (CAL), plaque index (PI), and bleeding on probing (BOP). Forest plots for PD, BOP, PI, and CAL at baseline, three months, and six months revealed no statistically significant differences between the SI+aPDT group and the SI-only group. Glycated hemoglobin across treatment groups was not different. Conclusions: The combination of aPDT with SI provides limited clinical benefits in treating periodontal pockets with a PPD ≥ 5 mm in diabetic patients with periodontitis. Full article

Author Gender Identification (AGI) is an extensively studied subject owing to its significance in several domains, such as security and marketing. Recognizing an author’s gender may assist marketers in segmenting consumers more effectively and crafting tailored content that aligns with a gender’s preferences. Also, in cybersecurity, identifying an author’s gender might aid in detecting phishing attempts where hackers could imitate individuals of a specific gender. Although studies in Arabic have mostly concentrated on written dialects, such as tweets, there is a paucity of studies addressing Modern Standard Arabic (MSA) in journalistic genres. To address the AGI issue, this work combines the beneficial properties of natural language processing with cutting-edge deep learning methods. Firstly, we propose a large 8k MSA article dataset composed of various columns sourced from news platforms, labeled with each author’s gender. Moreover, we extract and analyze textual features that may be beneficial in identifying gender-related cues through their writings, focusing on semantics and syntax linguistics. Furthermore, we probe several innovative deep learning models, namely, Convolutional Neural Networks (CNNs), LSTM, Bidirectional LSTM (BiLSTM), and Bidirectional Encoder Representations from Transformers (BERT). Beyond that, a novel enhanced BERT model is proposed by incorporating gender-specific textual features. Through various experiments, the results underscore the potential of both BERT and the textual features, resulting in a 91% accuracy for the enhanced BERT model and a range of accuracy from 80% to 90% accuracy for deep learning models. We also employ these features for AGI in informal, dialectal text, with the enhanced BERT model reaching 68.7% accuracy. This demonstrates that these gender-specific textual features are conducive to AGI across MSA and dialectal texts. Full article

We report on two mechanisms of angularly selective enhanced screening in the solid vortex phase of extremely layered superconductors with tilted columnar defects (CDs). We study Bi₂Sr₂CaCu₂O_8+δ samples with different densities of CD tilted 45° from the c-axis, and conduct local ac Hall magnetometry measurements, probing the sustainable current of the vortex system. We reveal two types of maxima in sustainable current for particular directions, detected as dips in the magnetic transmittivity of the vortex system. First, for a smaller number of vortices than of defects, an enhancement of screening is detected at an angular location ${\Theta }_{\mathrm{dip}}^1$∼45° for H applied close to the direction of CD. For a larger number of vortices than of CD, ${\Theta }_{\mathrm{dip}}^1$ decreases towards the $ab$-plane direction upon warming. Second, a pair of additional dips in transmittivity are detected at angles ${\Theta }_{dip}^2$ closer to, and quite symmetric with, the $ab$-plane. These two types of angularly selective enhanced screening reveal the effective pinning by tilted CD even for the composite vortex lattices nucleated in tilted fields in Bi₂Sr₂CaCu₂O_8+δ. Full article

Background: Periodontitis is a chronic infectious–inflammatory pathology, with a high prevalence, which destroys the dental support and, if left untreated, leads to tooth loss. It is associated with other pathologies, particularly diabetes mellitus. Objectives: Our objective was to conduct a review of systematic reviews with meta-analyses to determine the evidence for periodontal treatment on periodontitis and diabetes. Second, we assessed the risk of bias and methodological quality using the AMSTAR-2 and ROBIS tools. Methods: We performed bibliographic searches in PubMed/Medline, Embase, Cochrane Central, Dentistry & Oral Sciences Source databases and in the Web of Science (WOS) scientific information service to identify systematic reviews with meta-analyses from the last five years. Results: Eighteen studies that met the inclusion criteria and evaluated 16,247 subjects were included. The most studied parameters were probing pocket depth, clinical attachment level, bleeding on probing and the glycated hemoglobin. Most of the included meta-analyses evaluated adult patients with periodontitis and type 2 diabetes mellitus (T2DM). Most of the meta-analyses considered and assessed by AMSTAR-2 showed significant methodological errors. The risk of bias was the domain with the worst assessment with the ROBIS tool. Conclusions: Despite the weaknesses of the included meta-analyses in terms of methodological quality and the risk of bias, periodontal treatment and DM treatment appear to contribute to improved clinical outcomes in a bidirectional manner between periodontitis and DM. Full article

Background: Periodontitis and diabetes mellitus (DM) exhibit a bidirectional relationship and are globally significant systemic chronic conditions. The utilization of antibiotics alongside non-surgical periodontal treatment (NSPT) has been a subject of investigation in numerous clinical studies involving human subjects. Thus, the objective of this systematic review is to address the following question: “What is the efficacy of scaling and root planing (SRP) associated with antimicrobials in patients with type 2 DM and periodontitis?”. Methods: A systematic review of the literature was conducted encompassing databases such as MEDLINE/PubMed, Scopus, and Web of Science up to July 2024. Additionally, alerts were configured to capture studies published from the initial search until manuscript submission. Randomized clinical trials assessing clinical periodontal parameters in DM patients undergoing SRP and receiving either topical or systemic antibiotics were compared against a control group (SRP only). Two investigators independently screened articles, extracted data, and evaluated their quality. The selection process, study characteristics, risk of bias, impact of antibiotics on clinical parameters, and certainty of evidence were elucidated in both textual and tabular formats. Meta-analysis was performed separately with forest plots generated for treatment modalities, period of evaluation, and type of antibiotics used. Results: Following the analysis of abstracts and full articles, a total of 30 randomized clinical trials were incorporated into this review, comprising 9 studies on the association of topical antibiotics and 21 studies on systemic antibiotic administration. The principal periodontal parameters assessed included probing pocket depth (PPD), clinical attachment level (CAL), plaque index (PI), and bleeding on probing (BoP). Conclusions: Analysis of the results led to the conclusion that adjunctive periodontal treatment with either topical or systemic antibiotics confers subtle clinical benefits. Nevertheless, owing to the heightened emergence of resistant bacteria and potential side effects, the use of antibiotic therapy in periodontal treatment should be judiciously administered. Full article

A single nucleotide variant in mitochondrial DNA (mtDNA) 1555A>G is associated with drug-induced hearing loss. For the 1555A>G mutation site, 1555A wild-type and 1555G mutant-type plasmids were constructed, respectively. In this study, a PCR method based on the TaqMan amplification refractory mutation system was proposed to detect mtDNA 1555A>G. A common upstream primer, a common TaqMan probe, and two downstream allele-specific primers with mismatched bases were designed. One-step amplification and detection of the wild-type and mutant type at the 1555 site were realized for the deafness-related gene through two reactions. Based on this detection method, the minimum detection limit of the wild-type and mutant type detection systems for plasmids was 50 copies/μL. The minimum sensitivity for the detection of nucleic acids in real dried blood spot (DBS) samples was 0.1 ng/μL. In the normal DBS DNA sample, the detection limit of the mutation abundance reached 0.78%. The specificity of the detection method was 100%, and the coefficient of variation was less than 3.36%. This approach was validated using clinical DNA extracted from 113 DBS samples of newborns. Additionally, it showed 100% agreement with bi-directional Sanger sequencing. It can be used as an optional method for the clinical detection of deafness-related genes. Full article

Recent advancements in neural probe technology have become pivotal in both neuroscience research and the clinical management of neurological disorders. State-of-the-art developments have led to the advent of multichannel, high-density bidirectional neural interfaces that are adept at both recording and modulating neuronal activity within the central nervous system. Despite this progress, extant bidirectional probes designed for simultaneous recording and stimulation are beset with limitations, including elicitation of inflammatory responses and insufficient charge injection capacity. In this paper, we delineate the design and application of an innovative ultraflexible bidirectional neural probe engineered from polyimide. This probe is distinguished by its ability to facilitate high-resolution recordings and precise stimulation control in deep brain regions. Electrodes enhanced with a PEDOT:PSS/IrO_x composite exhibit a substantial increase in charge storage capacity, escalating from 0.14 ± 0.01 mC/cm² to an impressive 24.75 ± 0.18 mC/cm². This augmentation significantly bolsters the electrodes’ charge transfer efficacy. In tandem, we observed a notable reduction in electrode impedance, from 3.47 ± 1.77 MΩ to a mere 41.88 ± 4.04 kΩ, while the phase angle exhibited a positive shift from −72.61 ± 1.84° to −34.17 ± 0.42°. To substantiate the electrodes’ functional prowess, we conducted in vivo experiments, where the probes were surgically implanted into the bilateral motor cortex of mice. These experiments involved the synchronous recording and meticulous analysis of neural signal fluctuations during stimulation and an assessment of the probes’ proficiency in modulating directional turning behaviors in the subjects. The empirical evidence corroborates that targeted stimulation within the bilateral motor cortex of mice can modulate the intensity of neural signals in the stimulated locale, enabling the directional control of the mice’s turning behavior to the contralateral side of the stimulation site. Full article

Images captured by deep space probes exhibit large-scale variations, irregular overlap, and remarkable differences in field of view. These issues present considerable challenges for the registration of multi-view asteroid sensor images. To obtain accurate, dense, and reliable matching results of homonymous points in asteroid images, this paper proposes a new scale-invariant feature matching and displacement scalar field-guided optical-flow-tracking method. The method initially uses scale-invariant feature matching to obtain the geometric correspondence between two images. Subsequently, scalar fields of coordinate differences in the x and y directions are constructed based on this correspondence. Next, interim images are generated using the scalar field grid. Finally, optical-flow tracking is performed based on these interim images. Additionally, to ensure the reliability of the matching results, this paper introduces three methods for eliminating mismatched points: bidirectional optical-flow tracking, vector field consensus, and epipolar geometry constraints. Experimental results demonstrate that the proposed method achieves a 98% matching correctness rate and a root mean square error of 0.25 pixels. By combining the advantages of feature matching and optical-flow field methods, this approach achieves image homonymous point matching results with precision and density. The matching method exhibits robustness and strong applicability for asteroid images with cross-scale, large displacement, and large rotation angles. Full article

Metabolic syndrome is experiencing a concerning and escalating rise in prevalence today. The link between metabolic syndrome and periodontal disease is a highly relevant area of research. Some studies have suggested a bidirectional relationship between metabolic syndrome and periodontal disease, where one condition may exacerbate the other. Furthermore, the existence of periodontal disease among these individuals significantly impacts overall health management. This research focuses on the relationship between periodontal disease and metabolic syndrome, while also incorporating data on general health status and overall well-being. We aimed to develop advanced machine learning models that efficiently identify key predictors of metabolic syndrome, a significant emphasis being placed on thoroughly explaining the predictions generated by the models. We studied a group of 296 patients, hospitalized in SCJU Sibiu, aged between 45–79 years, of which 57% had metabolic syndrome. The patients underwent dental consultations and subsequently responded to a dedicated questionnaire, along with a standard EuroQol 5-Dimensions 5-Levels (EQ-5D-5L) questionnaire. The following data were recorded: DMFT (Decayed, Missing due to caries, and Filled Teeth), CPI (Community Periodontal Index), periodontal pockets depth, loss of epithelial insertion, bleeding after probing, frequency of tooth brushing, regular dental control, cardiovascular risk, carotid atherosclerosis, and EQ-5D-5L score. We used Automated Machine Learning (AutoML) frameworks to build predictive models in order to determine which of these risk factors exhibits the most robust association with metabolic syndrome. To gain confidence in the results provided by the machine learning models provided by the AutoML pipelines, we used SHapley Additive exPlanations (SHAP) values for the interpretability of these models, from a global and local perspective. The obtained results confirm that the severity of periodontal disease, high cardiovascular risk, and low EQ-5D-5L score have the greatest impact in the occurrence of metabolic syndrome. Full article

Prolonged exposure to a sensory stimulus induces perceptual adaptation aftereffects. Traditionally, aftereffects are known to change the appearance of stimulus features, like contrast, color, or shape. However, shifts in the spatial position of objects have also been observed to follow adaptation. Here, I demonstrate that visual adaptation produced by different adapter stimuli generates a bi-directional spatial repulsion. Observers had to judge the distance between a probe dot pair presented in the adapted region and compare them to a reference dot pair presented in a region not affected by adaptation. If the probe dot pair was present inside the adapted area, observers underestimated the distance. If, however, the dot pair straddled the adapted area, the distance was perceived as larger with a stronger distance expansion than compression. Bi-directional spatial repulsion was found with a similar magnitude for size and density adapters. Localization estimates with mouse pointing revealed that adaptation also affected absolute position judgments. Bi-directional spatial repulsion is most likely produced by the lines of adapter stimuli since single bars used as adapters were sufficient to induce spatial repulsion. Spatial repulsion was stronger for stimuli presented in the periphery. This finding explains why distance expansion is stronger than distance compression. Full article

Targeted sequencing has been widely utilized for genomic molecular diagnostics and the emerging DNA data storage paradigm. However, the probe sequences used to enrich regions of interest have different hybridization kinetic properties, resulting in poor sequencing uniformity and setting limitations for the large-scale application of the technology. Here, a low-complexity deep learning model is proposed for prediction of sequencing depth from probe sequences. To capture the representation of probe and target sequences, we utilized a sequence-encoding model that incorporates k-mer and word embedding techniques, providing a streamlined alternative to the intricate computations involved in biochemical feature analysis. We employed bidirectional long short-term memory (Bi-LSTM) to effectively capture both long-range and short-range interactions within the representation. Furthermore, the attention mechanism was adopted to identify pivotal regions in the sequences that significantly influence sequencing depth. The ratio of the predicted sequencing depth to the actual sequencing depth was in the interval of 1/3—3 as the evaluation metric of model accuracy. The prediction accuracy was 94.3% in the human single-nucleotide polymorphism (SNP) panel and 99.7% in the synthetic DNA information storage sequence (SynDNA) panel. Our model substantially reduced data processing time (from 334 min to 4 min of CPU time in the SNP panel) and model parameters (from 300 k to 70 k) compared with the baseline model. Full article

Peridinin-containing dinoflagellate plastomes are predominantly encoded in nuclear genomes, with less than 20 essential chloroplast proteins carried on “minicircles”. Each minicircle generally carries one gene and a short non-coding region (NCR) with a median length of approximately 400–1000 bp. We report here differential nuclease sensitivity and two-dimensional southern blot patterns, suggesting that dsDNA minicircles are in fact the minor forms, with substantial DNA:RNA hybrids (DRHs). Additionally, we observed large molecular weight intermediates, cell-lysate-dependent NCR secondary structures, multiple bidirectional predicted ssDNA structures, and different southern blot patterns when probed with different NCR fragments. In silico analysis suggested the existence of substantial secondary structures with inverted repeats (IR) and palindrome structures within the initial ~650 bp of the NCR sequences, in accordance with conversion event(s) outcomes with PCR. Based on these findings, we propose a new transcription-templating-translation model, which is associated with cross-hopping shift intermediates. Since dinoflagellate chloroplasts are cytosolic and lack nuclear envelope breakdown, the dynamic DRH minicircle transport could have contributed to the spatial-temporal dynamics required for photosystem repair. This represents a paradigm shift from the previous understanding of “minicircle DNAs” to a “working plastome”, which will have significant implications for its molecular functionality and evolution. Full article

Hearing loss is the most prevalent sensory disorder worldwide. The majority of congenital nonsyndromic hearing loss (NSHL) cases are caused by hereditary factors. Previously, the majority of NSHL studies focused on the GJB2 gene; however, with the availability of next-generation sequencing (NGS) methods, the number of novel variants associated with NSHL has increased. The purpose of this study was to design effective genetic screening for a Hungarian population based on a pilot study with 139 NSHL patients. A stepwise, comprehensive genetic approach was developed, including bidirectional capillary sequencing, multiplex ligation-dependent probe amplification (MLPA), and an NGS panel of 108 hearing loss genes. With our results, a genetic diagnosis was possible for 92 patients. Sanger sequencing and MLPA identified the genetic background of 50% of these diagnosed cases, and the NGS panel identified another 16%. The vast majority (92%) of the diagnosed cases showed autosomal recessive inheritance and 76% were attributed to GJB2. The implementation of this stepwise analysis markedly increased our diagnostic yield and proved to be cost-effective as well. Full article