Miracle-dz/UniFAR-FTUs huggingface dataset:
Detection of diseases in rice leaf using convolutional neural network with transfer learning based on ResNeXt

Rice is the most cultivated crop in the agricultural field and is a major food source for more than 60% of the population in India. Occurrence of disease in rice leaves, majorly affects the rice quality, production and also the farmers’ income. Nowadays, new variety of diseases in rice leaves are identified and detected periodically throughout the world. Manual monitoring and detection of plant diseases proves to be time consuming for the farmer and also a costly affair for using chemicals in the disease treatment. In this paper, a deep learning method of convolutional neural networks (CNN) with a transfer learning technique is proposed for the detection of a variety of diseases in rice leaves. This method uses the ResNeXt network model for classifying the images of disease-affected plants. The proposed model’s performance is evaluated using accuracy, precision, recall, F1-score and specificity. The experimental results of ResNeXt model measured for accuracy, precision, recall, F1-score, and specificity, are respectively 99.22%, 92.87%, 91.97%, 90.95%, and 99.05%, which proves greater accuracy improvement than the existing methods of SG2-ADA, YOLOV5, InceptionResNetV2 and Raspberry Pi.
Identification of a novel RPGR mutation associated with retinitis pigmentosa and primary ciliary dyskinesia in a Slovak family: a case report

Background The mutations in the RPGR (retinitis pigmentosa GTPase regulator) gene are the most common cause of X-linked retinitis pigmentosa (XLRP), a rare genetic disorder affecting the photoreceptor cells in the retina. Several reported cases identified this gene as a genetic link between retinitis pigmentosa (RP) and primary ciliary dyskinesia (PCD), characterised by impaired ciliary function predominantly in the respiratory tract. Since different mutations in the same gene can result in various clinical manifestations, it is important to describe a correlation between the gene variant and the observed phenotype. Methods Two young brothers from a non-consanguineous Slovak family with diagnosed retinal dystrophy and recurrent respiratory infections were examined. Suspected PCD was diagnosed based on a PICADAR questionnaire, nasal nitric oxide analysis, transmission electron microscopy, high-speed video microscopy analysis, and genetic testing. Results We identified a novel frameshift RPGR mutation NM_001034853: c. 309_310insA, p.Glu104Argfs*12, resulting in a complex X-linked phenotype combining PCD and RP. In our patients, this mutation was associated with normal ultrastructure of respiratory cilia, reduced ciliary epithelium, more aciliary respiratory epithelium, shorter cilia, and uncoordinated beating with a frequency at a lower limit of normal beating, explaining the clinical manifestation of PCD in our patients. Conclusion The identified novel pathogenic mutation in the RPGR gene expands the spectrum of genetic variants associated with the X-linked PCD phenotype overlapping with RP, highlighting the diversity of mutations contributing to the disorder. The described genotype–phenotype correlation can be useful in clinical practice to recognise a broader spectrum of PCD phenotypes as well as for future research focused on the genetic basis of PCD, gene interactions, the pathways implicated in PCD pathogenesis, and the role of RPGR protein for the proper functioning of cilia in various tissues throughout the body.
Morphology Distribution in Injection Molded Parts

A more sustainable use of plastic parts makes it necessary to replace current plastic parts with recyclable components, also allowing the modulation of the part properties through the process. Injection molding is one of the most widely used technologies for obtaining rigid plastic parts, so it is crucial to understand how to tailor properties by adopting the correct processing conditions. One way is to perform annealing steps directly inside the mold: in-mold annealing improves the structural integrity and durability of the material, reduces defects, increases the resistance of parts against certain chemicals, reduces wear and tear, increases ductility, and lowers brittleness. In this work, several in-mold annealing steps were conducted, changing the mold temperature and annealing duration selected on the basis of the half crystallization time of the adopted isotactic polypropylene. The typical molded part morphology, composed of oriented layers at the surface, transition zones, and spherulitic core, is strongly affected by in-mold annealing. In particular, the thickness of the oriented layer, which forms in the early phase of the process, decreases, and the spherulites increase in size. Concerning mechanical behavior, the orientation degree mostly determines the elastic modulus value close to the surface, whereas the conditions under which crystallization occurs determine the modulus in the core.
Plasma Cleaning of Hydrocarbon and Carbon Contaminated Surfaces of Accelerator Components

To achieve the vacuum quality required for the operation of particle accelerators, the surface of the vacuum vessels must be clean from hydrocarbons. This is usually achieved by wet chemistry processes, e.g., degreasing chemical baths that, in case of radioactive vessels, must be disposed accordingly. An alternative way exploits the oxygen plasma produced by a downstream RF plasma source. This technique offers the possibility of operating in-situ, which is an advantageous option to avoid the handling of voluminous and/or fragile components and a more sustainable alternative to large volume disposable baths. In this work, we test a commercial plasma source in dedicated vacuum systems equipped with quartz crystal microbalances (QCMs). The evolution of the etching rates of amorphous carbon (a-C) thin films deposited on the QCMs to mimic contamination are studied as function of operating parameters. We present the results of the plasma cleaning process applied to the real case of a hydrocarbons-contaminated large vacuum vessel. The studies are complemented by transport simulations and surface contamination monitoring by X-ray photoelectron spectroscopy (XPS) analysis. The evaluation of the vessel cleanliness, which is performed via residual gas analysis (RGA) measurements, is based on CERN’s outgassing acceptance criteria and agrees with both simulations and XPS results.
Super-Resolution of Lightweight Images Based on Deep Learning

As digital imaging technology advances, a significant breakthrough is the emergence of super-resolution technology, a method to enhance the quality of low-resolution images to high-resolution. When there are some developing of the newest digital camera's skills, the super-resolution technology is appearing and getting more and more importance. In the simplest terms, the image super-resolution skill is the technology of which one cover the process from low resolution images to high resolution images skills. This technology differs from the traditional approach in that it is attracting more and more attention from researchers and practitioners. This method is important in the future. With the passage of time, it will be more and more mature. In this paper, we focus on how to improve image resolution by using various technologies, and summarise the results obtained in recent years. Then, we briefly introduce the background and development of super resolution, then briefly introduce the technology. Finally, we come to a few conclusions regarding Deep Learning.
Diagnostic Performance of a Novel Ultra-Thin Endoscopy under Narrow-Band Imaging for Superficial Squamous Cell Carcinoma of the Pharynx and Esophagus

Simple Summary A newly developed ultra-thin endoscope (UTE) provides higher-resolution images, allowing for the evaluation of microvascular patterns. This prospective study aimed to demonstrate the diagnostic performance of UTE for superficial squamous cell carcinoma (SSCC) in the pharynx and esophagus. The Japan Esophageal Society classification is the most common diagnostic system for SESCC. This system requires a precise evaluation of microvessels under magnification with narrow-band imaging. We confirmed that the UTE exhibited sufficient diagnostic performance for the detection and diagnosis of SSCC compared to magnifying endoscopy. The study results showed that most lesions can be accurately diagnosed with high confidence without magnification (i.e., UTE), and the confidence level did not improve, even when the lesion was observed under magnification. UTE, which provides higher-resolution images, can be a reliable tool for the screening or surveillance of SSCC in the pharynx and esophagus. Abstract This study aimed to evaluate the diagnostic utility of the ultra-thin endoscope (UTE) for superficial squamous cell carcinoma (SSCC) compared to magnifying endoscopy (ME) under narrow-band imaging. Participants underwent endoscopic examination, and images of pharyngeal and esophageal SCCs, as along with suspicious SSCC lesions, were collected using UTE and ME on the same day. Three image catalogs (UTE, ME-1, and ME-2) were created and reviewed by three expert endoscopists. ME-1 and ME-2 contained the same endoscopic images. The primary endpoint was the intra-observer agreement for diagnosing SCC. Eighty-six lesions (SCC = thirty-nine, non-SCC = forty-seven) in 43 participants were identified. The kappa values for the intra-observer agreement between UTE and ME-1 vs. the control (ME-1 vs. ME-2) were 0.74 vs. 0.84, 0.63 vs. 0.76, and 0.79 vs. 0.88, respectively. The accuracies for diagnosing SCC by UTE and ME-1 were 87.2% vs. 86.0%, 78.0% vs. 73,2%, and 75.6 vs. 82.6%, respectively, with no significant differences (p > 0.05). The rates of lesions that were diagnosed with confidence by UTE and ME-1 were 30.2% vs. 27.9%, 55.8% vs. 62.8%, and 58.1% vs. 55.8%, respectively. UTE demonstrates substantial diagnostic performance for SSCC in the pharynx and esophagus.
Spatial and Temporal Variation in the Occurrence of Gremmeniella abietina in Scots Pine in Finland

Spatial and temporal patterns in the occurrence of the infections caused by Gremmeniella abietina in Scots pine stands in Finland during the years 1985-2005 were described in this paper The study utilized data from forest health monitoring plots (Forest Focus Level I plots) and permanent and temporal plots of the National Forest Inventories. The National Forest Inventories showed that the disease was far more common in southern than in the northern parts of the country. The disease was also clearly spatially clustered. The proportion of diseased stands decreased between the 8th NFI (1986-1994) and 9th NFI (1996-2003). The forest health monitoring revealed a heavy outbreak of Gremmeniella in 1988-89, and smaller peaks in 1997 and 2001. Temporal and spatial distributions of the disease were obtained using the level I data. The usability of various datasets were also compared with each other.
Heterogeneous interactions and transformations of dibasic esters with indoor relevant surfaces.

Dibasic esters (DBEs) have recently become emerging indoor air pollutants due to their usage as a solvent for mixtures of paints and coatings. In this study, we explored the adsorption/desorption kinetics, heterogeneous interactions, and chemical transformations of dimethyl succinate (DMS, C6H10O4), a component of commercial dibasic ester solvent mixtures, on indoor relevant surfaces using transmission Fourier-transform infrared (FTIR) spectroscopy and high-resolution mass spectrometry (HRMS). Silica (SiO2) and rutile (TiO2) were used as proxies for window glass, and an active component in paint and self-cleaning surfaces, respectively. FTIR spectroscopy of these surfaces shows that DMS can interact with SiO2 and TiO2 through hydrogen bonding between the carbonyl oxygen and surface hydroxyl groups. The kinetics show fast adsorption of DMS onto these surfaces followed by slow desorption. Furthermore, new products formed observed on TiO2 surfaces in addition to molecularly adsorbed DMS. In particular, succinate (C5H7O) was observed binding to the surface in a bidentate chelating coordination mode as indicated by the appearance of νas(COO-) and νs(COO-) bands in the FTIR spectra. These absorption bands grow in intensity over time and the resulting product remains strongly adsorbed on the surface. The formation of adsorbed succinate is a result of a reaction with DMS on Lewis acid sites of the TiO2 surface. Overall, the slow desorption of these adsorbed species indicates that indoor surfaces can become long term reservoirs for dibasic esters and their surface products. Moreover, in the presence of ∼50% relative humidity, water displaces outer layers of adsorbed DMS on SiO2 and TiO2, while having no impact on the more strongly bound surface species.
Development of a Multimodal, Personalized Intervention of Virtual Reality Integrated Within Physiotherapy for Patients With Complex Chronic Low-Back Pain

Background: Chronic low-back pain (CLBP) is the leading cause of years lived with disability. Physiotherapy is the most common treatment option for CLBP, but effects are often unsatisfactory. Virtual reality (VR) offers possibilities to enhance the effectiveness of physiotherapy treatment. Primary aim was to develop and test a personalized VR intervention integrated within a physiotherapy treatment for patients with CLBP. Methods: This study describes an intervention development process using mixed methods design that followed the Medical Research Council (MRC) framework. This involved a cocreation process with patients, physiotherapists, and researchers. A draft intervention was constructed based on a literature review and focus groups, and subsequently tested in a feasibility study and evaluated in focus groups. Focus group data were analyzed using thematic analysis. This intervention development process resulted in a final intervention. Results: Focus group data showed that VR and physiotherapy can strengthen each other when they are well integrated, and that VR needs to be administered under the right conditions including flawless technology, physiotherapists with sufficient affinity and training, and the right expectations from patients. The draft intervention was considered feasible after evaluation by four patients and three physiotherapists and was further complemented by expanding the training for physiotherapists and improving the protocols for physiotherapists and patients. The final intervention consisted of a 12-week physiotherapy treatment with three integrated VR modules: pain education, physical exercise, and relaxation. Conclusion: Using the MRC framework in cocreation with the end users, a personalized VR intervention integrated within a physiotherapy treatment for patients with CLBP was developed. This intervention was found to be feasible and will subsequently be evaluated for (cost-)effectiveness in a cluster randomized controlled trial.
Block-Wise Separable Convolutions: An Alternative Way to Factorize Standard Convolutions

In this paper, we introduce block-wise separable convolutions (BlkSConv) to replace the standard convolutions for compressing deep CNN models. First, BlkSConv expresses the standard convolutional kernel as an ordered set of block vectors each of which is a linear combination of fixed basis block vectors. Then it eliminates most basis block vectors and their corresponding coefficients to obtain an approximated convolutional kernel. Moreover, the proposed BlkSConv operation can be efficiently realized via a combination of pointwise and group-wise convolutions. Thus the constructed networks have smaller model size and fewer multiply-adds operations while keeping comparable prediction accuracy. We also develop a hyperparameter search framework based on principal component analysis (PCA) to determine a qualified hyperparameter setting of the block depth and number of basis block vectors. By this search framework, we construct networks which achieve nice prediction performance while simultaneously satisfying the constraints of model size and model efficiency. Our code, data, and models are available at https://github.com/yanjenhuang/blksconv.
Toward Quantum-Informed Atom Pairs

In the following research, a new modification of traditional atom pairs is studied. The atom pairs are enriched with values originating from quantum chemistry calculations. A random forest machine learning algorithm is applied to model 10 different properties and biological activities based on different molecular representations, and it is evaluated via repeated cross-validation. The predictive power of modified atom pairs, quantum atom pairs, are compared to the predictive powers of traditional molecular representations known and widely applied in cheminformatics. The root mean squared error (RMSE), R2, area under the receiver operating characteristic curve (AUC) and balanced accuracy were used to evaluate the predictive power of the applied molecular representations. Research has shown that while performing regression tasks, quantum atom pairs provide better fits to the data than do their precursors.
Predictive value of multiple imaging predictive models for spread through air spaces of lung adenocarcinoma: A systematic review and network meta‑analysis

Spread Through Air Spaces (STAS) is involved in lung adenocarcinoma (LUAD) recurrence, where cancer cells spread into adjacent lung tissue, impacting surgical planning and prognosis assessment. Radiomics-based models show promise in predicting STAS preoperatively, enhancing surgical precision and prognostic evaluations. The present study performed network meta-analysis to assess the predictive efficacy of imaging models for STAS in LUAD. Data were systematically sourced from PubMed, Embase, Scopus, Wiley and Web of Science, according to the Cochrane Handbook for Systematic Reviews of Interventions) and A Measurement Tool to Assess systematic Reviews 2. Using Stata software v17.0 for meta-analysis, surface under the cumulative ranking area (SUCRA) was applied to identify the most effective diagnostic method. Quality assessments were performed using Cochrane Collaboration's risk-of-bias tool and publication bias was assessed using Deeks' funnel plot. The analysis encompassed 14 articles, involving 3,734 patients, and assessed 17 predictive models for STAS in LUAD. According to comprehensive analysis of SUCRA, the machine learning (ML)_Peri_tumour model had the highest accuracy (56.5), the Features_computed tomography (CT) model had the highest sensitivity (51.9) and the positron emission tomography (pet)_CT model had the highest specificity (53.9). ML_Peri_tumour model had the highest predictive performance. The accuracy was as follows: ML_Peri_tumour vs. Features_CT [relative risk (RR)=1.14; 95% confidence interval (CI), 0.99–1.32]; ML_Peri_tumour vs. ML_Tumour (RR=1.04; 95% CI, 0.83–1.30) and ML_Peri_tumour vs. pet_CT (RR=1.04; 95% CI, 0.84–1.29). Comparative analyses revealed heightened predictive accuracy of the ML_Peri_tumour compared with other models. Nonetheless, the field of radiological feature analysis for STAS prediction remains nascent, necessitating improvements in technical reproducibility and comprehensive model evaluation.
In vitro evaluation of the immunomodulatory and wakame assimilation properties of Lactiplantibacillus plantarum strains from swine milk

The emergence and spread of antibiotic resistance threat forced to explore alternative strategies for improving the resistance to pathogens in livestock production. Probiotic lactic acid bacteria represent an alternative for this objective. In this study, seven Lactiplantibacillus plantarum strains from porcine colostrum and milk were isolated, identified and characterized in terms of their abilities to modulate immunity in porcine intestinal epithelial (PIE) cells. Then, two potential immunoregulatory strains were studied in terms of their ability to utilize and grow in wakame (Undaria pinnafida). Isolates were identified by 16S rRNA gene and evaluated by studying their interaction with PIE cells. The expressions of peptidoglycan recognition proteins (PGRPs), nucleotide-binding oligomerization domain (NODs), host defense peptides (pBD), and type I interferons (IFNs) were evaluated by RT-qPCR. The strain 4M4417 showed a remarkable capacity to differentially regulate the expression of PGRP1, PGRP3, NOD1, NOD2, and pBD1 in PIE cells. On the other hand, the strain 4M4326 was the most efficient to improve the expression of IFN-α and IFN-β in PIE cells challenged with poly (I:C). Both L. plantarum 4M4326 and 4M4417 were characterized in terms of their ability to utilize wakame. Results demonstrated that both strains efficiently grew in wakame-based broth. Our results suggest that L. planatrum 4M4326 and 4M4417 are interesting candidates to develop immunomodulatory feeds based on wakame utilization. These new immunosynbiotic feeds could help to reduce severity of intestinal infections and improve immune health status in pigs.
Nanosuspension-Based Drug Delivery Systems for Topical Applications

Abstract Nanosuspensions have garnered recent attention as a promising strategy for mitigating the bioavailability challenges of hydrophobic drugs, particularly those characterized by poor solubility in both aqueous and organic environments. Addressing solubility issues associated with poorly water-soluble drugs has largely resolved the need to enhance drug absorption and bioavailability. As mucosal formulations and topical administration progress in the future, nanosuspension drug delivery, straightforward formulation techniques, and versatile applications will continue to be subjects of interest. Nanosuspensions have undergone extensive scrutiny in preparation for topical applications, encompassing ocular, pulmonary, and dermal usage. Among the numerous methods aimed at improving cutaneous application, nanocrystals represent a relatively recent yet profoundly intriguing approach. Despite the increasing availability of various nanosuspension products, primarily designed for oral administration, only a limited number of studies have explored skin permeability and drug accumulation in the context of nanosuspensions. Nevertheless, the scant published research unequivocally underscores the potential of this approach for enhancing cutaneous bioavailability, particularly for active ingredients with low to medium solubility. Nanocrystals exhibit increased skin adhesiveness in addition to heightened saturation solubility and dissolution rate, thereby augmenting cutaneous distribution. The article provides a comprehensive overview of nanosuspensions for topical application. The methodology employed is robust, with a well-defined experimental design; however, the limited sample size raises concerns about the generalizability of the findings. While the results demonstrate promising outcomes in terms of enhanced drug delivery, the discussion falls short of addressing certain limitations. Additionally, the references largely focus on recent studies, but a more diverse inclusion of historical perspectives could offer a more holistic view of the subject.
Pilsbrylia, a dextral-shelled door snail from South America (Gastropoda, Clausiliidae)

The land snail genus Pilsbrylia Hylton Scott, 1952 has been recently shown to not belong to the superfamily to which it was originally assigned (i.e., the Orthalicoidea), instead pointing out a relationship with the Clausilioidea. In this study, we included the type species of the genus in a multi-marker molecular phylogenetic framework to reassess its family-level classification. Our results show that Pilsbrylia belongs to family Clausiliidae (known as ‘door snails’) and more specifically, to subfamily Peruiniinae. This family is unique among stylommatophorans for consisting almost exclusively of animals with sinistral (left-handed) shells, whilst Pilsbrylia has a “typical” dextral shell.