Miracle-dz/UniFAR-FTUs huggingface dataset:
Silver Nano Chito Oligomer Hybrid Solution for the Treatment of Citrus Greening Disease (CGD) and Biostimulants in Citrus Horticulture

Citrus greening disease (CGD), or Huanglongbing (HLB), is principal in Citrus farming because of its severe damage, decreased yield, poor quality of fruit, and frequent disappearance before harvest. Present research blended silver nanoparticles (AgNPs) colloid with chitooligomers and monomers (COAMs) to create the composites referred to as a “hybrid solution”. The hybrid solution has been synthesized for antimicrobial effects and plant growth stimulation. The hybrid solution was applied to cure the CGD, which was then tested using the results of the iodine test kit. Study results revealed that the mechanism for antibacterial properties is efficient and leads to cell death by silver ions (positive charge) attached to the cell wall of pathogens (negative charge). COAMs increase AgNPs’ ability to adhere to negatively charged bacterial cytoplasmic membranes and amplify their electrostatic interaction. There are synergistic antibacterial effects of AgNPs–COAMs. The findings reveal a notable increase in the shoot length of leaves which may be the reason for the growth stimulation function of the hybrid solution due to the properties of COAMs as a biostimulant. The hybrid solution-treated trees yielded around 104.50 ± 4.56 kg of fruits by the trunk or foliar application. Citrus fruits did not show the presence of any silver residues, as displayed by the results of the accumulation test. Compared to conventional ampicillin, the hybrid treatment of CGD was significantly more cost-effective, increased productivity, and had minor accumulation. The acquired results may also be applied to further plant disease treatment.
Injectable Hydrated Calcium Phosphate Bone-like Paste: Synthesis, In Vitro, and In Vivo Biocompatibility Assessment

The injectable hydrated calcium phosphate bone-like paste (hCPP) was developed with suitable rheological characteristics, enabling unhindered injection through standard 23G needles. In vitro assays showed the cytocompatibility of hCPP with mesenchymal embryonic C3H10T1/2 cell cultures. The hCPP was composed of aggregated micro-sized particles with sphere-like shapes and low crystallinity. The ability of hCPP particles to adsorb serum proteins (FBS) was investigated. The hCPP demonstrated high protein adsorption capacity, indicating its potential in various biomedical applications. The results of the in vivo assay upon subcutaneous injection in Wistar rats indicated nontoxicity and biocompatibility of experimental hCPP, as well as gradual resorption of hCPP, comparable to the period of bone regeneration. The data obtained are of great interest for the development of commercial highly effective osteoplastic materials for bone tissue regeneration and augmentation.
SegFuzz: Segmentizing Thread Interleaving to Discover Kernel Concurrency Bugs through Fuzzing

Discovering kernel concurrency bugs through fuzzing is challenging. Identifying kernel concurrency bugs, as opposed to non-concurrency bugs, necessitates an analysis of possible interleavings between two or more threads. However, because the search space of thread interleaving is vast, it is impractical to investigate all conceivable thread interleavings. To explore the vast search space, most previous approaches perform random or simple heuristic searches without having coverage for thread interleaving or with an insufficient form of coverage. As a result, they either conduct wasteful searches with redundant executions or overlook concurrent bugs that their coverage cannot address.To overcome such limitations, we propose SegFuzz, a fuzzing framework for kernel concurrency bugs. When exploring the search space of thread interleavings, SegFuzz decomposes an entire thread interleaving into a set of segments, each of which represents an interleaving of the small number of instructions, and utilizes individual segments as interleaving coverage, called interleaving segment coverage. When searching for thread interleavings, SegFuzz mutates interleavings in explored interleaving segments to construct new thread interleavings that have not yet been explored. With SegFuzz, we discover new 21 concurrency bugs in Linux kernels, and demonstrate the efficiency of SegFuzz by showing that SegFuzz can identify known bugs on average 4.1 times quickly than the state-of-the-art approaches.
Pathophysiology and Treatment of Lipid Abnormalities in Cerebrotendinous Xanthomatosis: An Integrative Review

Cerebrotendinous xanthomatosis (CTX) is an autosomal recessive disorder caused by pathogenic variants in CYP27A1, leading to a deficiency in sterol 27-hydroxylase. This defect results in the accumulation of cholestanol and bile alcohols in various tissues, including the brain, tendons and peripheral nerves. We conducted this review to evaluate lipid profile abnormalities in patients with CTX. A search was conducted in PubMed, Embase and the Virtual Health Library in January 2023 to evaluate studies reporting the lipid profiles of CTX patients, including the levels of cholestanol, cholesterol and other lipids. Elevated levels of cholestanol were consistently observed. Most patients presented normal or low serum cholesterol levels. A decrease in chenodeoxycholic acid (CDCA) leads to increased synthesis of cholesterol metabolites, such as bile alcohols 23S-pentol and 25-tetrol 3-glucuronide, which may serve as surrogate follow-up markers in patients with CTX. Lipid abnormalities in CTX have clinical implications. Cholestanol deposition in tissues contributes to clinical manifestations, including neurological symptoms and tendon xanthomas. Dyslipidemia and abnormal cholesterol metabolism may also contribute to the increased risk of atherosclerosis and cardiovascular complications observed in some CTX patients.
Influence of Storing Composite Filling Materials in a Low-pH Artificial Saliva on Their Mechanical Properties—An In Vitro Study

Restorative composites are subjected to various influences in the oral cavity environment, such as high or low temperatures, the mechanical force generated during mastication, colonization of various microorganisms, and low pH, which may result from ingested food and the influence of microbial flora. This study aimed to investigate the effect of a recently developed commercial artificial saliva (pH = 4, highly acidic) on 17 commercially available restorative materials. After polymerization, the samples were stored in an artificial solution for 3 and 60 days and subjected to crushing resistance and flexural strength tests. The surface additions of the materials were examined in terms of the shapes and sizes of the fillers and elemental composition. When stored in an acidic environment, the resistance of the composite materials was reduced by 2–12%. Larger compressive and flexural strength resistance values were observed for composites that could be bonded to microfilled materials (invented before 2000). This may result from the filler structure taking an irregular form, which results in a faster hydrolysis of silane bonds. All composite materials meet the standard requirements when stored for a long period in an acidic environment. However, storage of the materials in an acid environment has a destructive impact on the materials’ properties.
A Review of IsomiRs in Colorectal Cancer

As advancements in sequencing technology rapidly continue to develop, a new classification of microRNAs has occurred with the discovery of isomiRs, which are relatively common microRNAs with sequence variations compared to their established template microRNAs. This review article seeks to compile all known information about isomiRs in colorectal cancer (CRC), which has not, to our knowledge, been gathered previously to any great extent. A brief overview is given of the history of microRNAs, their implications in colon cancer, the canonical pathway of biogenesis and isomiR classification. This is followed by a comprehensive review of the literature that is available on microRNA isoforms in CRC. The information on isomiRs presented herein shows that isomiRs hold great promise for translation into new diagnostics and therapeutics in clinical medicine.
Transparent, High-Strength, and Antimicrobial Polyvinyl Alcohol/Boric Acid/Poly Hexamethylene Guanidine Hydrochloride Films

It is still crucial to improve the mechanical characteristics of polyvinyl alcohol (PVA) films without resorting to chemical cross-linking. In this study, boric acid (BA) was used to enhance the mechanical characteristics of PVA films while maintaining their excellent transparency and biodegradability. The hydrogen bond interaction between PVA and BA resulted in a 70% increase in tensile strength (from 48.5 to 82.1 MPa) and a 46% increase in elongation at break (from 150 to 220%). To introduce antibacterial properties, polyhexamethylene guanidine hydrochloride (PHMG) was incorporated into PVA/BA composite films resulting in PVA/BA/PHMG composite films. The PVA/BA/PHMG films exhibited 99.99% bacterial inhibition against Escherichia coli and Staphylococcus aureus with negligible leaching of PHMG. The PVA/BA/PHMG films maintained a tensile strength of 75.3 MPa and an elongation at a break of 208%. These improved mechanical and antimicrobial properties make PVA/BA and PVA/BA/PHMG films promising for applications in food and medicinal packaging.
In-Domain Transfer Learning Strategy for Tumor Detection on Brain MRI

Transfer learning has gained importance in areas where there is a labeled data shortage. However, it is still controversial as to what extent natural image datasets as pre-training sources contribute scientifically to success in different fields, such as medical imaging. In this study, the effect of transfer learning for medical object detection was quantitatively compared using natural and medical image datasets. Within the scope of this study, transfer learning strategies based on five different weight initialization methods were discussed. A natural image dataset MS COCO and brain tumor dataset BraTS 2020 were used as the transfer learning source, and Gazi Brains 2020 was used for the target. Mask R-CNN was adopted as a deep learning architecture for its capability to effectively handle both object detection and segmentation tasks. The experimental results show that transfer learning from the medical image dataset was found to be 10% more successful and showed 24% better convergence performance than the MS COCO pre-trained model, although it contains fewer data. While the effect of data augmentation on the natural image pre-trained model was 5%, the same domain pre-trained model was measured as 2%. According to the most widely used object detection metric, transfer learning strategies using MS COCO weights and random weights showed the same object detection performance as data augmentation. The performance of the most effective strategies identified in the Mask R-CNN model was also tested with YOLOv8. Results showed that even if the amount of data is less than the natural dataset, in-domain transfer learning is more efficient than cross-domain transfer learning. Moreover, this study demonstrates the first use of the Gazi Brains 2020 dataset, which was generated to address the lack of labeled and qualified brain MRI data in the medical field for in-domain transfer learning. Thus, knowledge transfer was carried out from the deep neural network, which was trained with brain tumor data and tested on a different brain tumor dataset.
Region-Based Sea Ice Mapping Using Compact Polarimetric Synthetic Aperture Radar Imagery with Learned Features and Contextual Information

Operational sea ice maps are usually generated manually using dual-polarization (DP) synthetic aperture radar (SAR) satellite imagery, but there is strong interest in automating this process. Recently launched satellites offer compact polarimetry (CP) imagery that provides more comprehensive polarimetric information compared to DP, which compels the use of CP for automated classification of SAR sea ice imagery. Existing sea ice scene classification algorithms using CP imagery rely on handcrafted features, while neural networks offer the potential of features that are more discriminating. We have developed a new and effective sea ice classification algorithm that leverages the nature of CP data. First, a residual-based convolutional neural network (ResCNN) is implemented to classify each pixel. In parallel, an unsupervised segmentation is performed to generate regions based on CP statistical properties. Regions are assigned a single class label by majority voting using the ResCNN output. For testing, quad-polarimetric (QP) SAR sea ice scenes from the RADARSAT Constellation Mission (RCM) are used, and QP, DP, CP, and reconstructed QP modes are compared for classification accuracy, while also comparing them to other classification approaches. Using CP achieves an overall accuracy of 96.86%, which is comparable to QP (97.16%), and higher than reconstructed QP and DP data by about 2% and 10%, respectively. The implemented algorithm using CP imagery provides an improved option for automated sea ice mapping.
Tick-Borne Encephalitis Virus: A Comprehensive Review of Transmission, Pathogenesis, Epidemiology, Clinical Manifestations, Diagnosis, and Prevention

Tick-borne encephalitis virus (TBEV), a member of the Flaviviridae family, can cause serious infection of the central nervous system in humans, resulting in potential neurological complications and fatal outcomes. TBEV is primarily transmitted to humans through infected tick bites, and the viral agent circulates between ticks and animals, such as deer and small mammals. The occurrence of the infection aligns with the seasonal activity of ticks. As no specific antiviral therapy exists for TBEV infection, treatment approaches primarily focus on symptomatic relief and support. Active immunization is highly effective, especially for individuals in endemic areas. The burden of TBEV infections is increasing, posing a growing health concern. Reported incidence rates rose from 0.4 to 0.9 cases per 100,000 people between 2015 and 2020. The Baltic and Central European countries have the highest incidence, but TBE is endemic across a wide geographic area. Various factors, including social and environmental aspects, improved medical awareness, and advanced diagnostics, have contributed to the observed increase. Diagnosing TBEV infection can be challenging due to the non-specific nature of the initial symptoms and potential co-infections. Accurate diagnosis is crucial for appropriate management, prevention of complications, and effective control measures. In this comprehensive review, we summarize the molecular structure of TBEV, its transmission and circulation in natural environments, the pathogenesis of TBEV infection, the epidemiology and global distribution of the virus, associated risk factors, clinical manifestations, and diagnostic approaches. By improving understanding of these aspects, we aim to enhance knowledge and promote strategies for timely and accurate diagnosis, appropriate management, and the implementation of effective control measures against TBEV infections.
Multifactorial Distress, the Warburg Effect, and Respiratory and pH Imbalance in Cancer Development

Oncogenes are thought to play an important role in aberrant regulation of growth factors, which is believed to be an initiation event of carcinogenesis. However, recent genetic and pharmacological studies have shown that the Warburg effect (WE) is needed for tumour growth. It refers to extensively studied aerobic glycolysis over the past decade, although its impact on cancer remains unclear. Meanwhile, a large body of evidence has indicated that oxidative stress (OS) is connected with the occurrence and progression of various forms of cancer. Psychosocial factors (PSF), such as chronic depression, sadness, stressful life experiences, stress-prone personality, and emotional distress or poor quality of life affect the immune system and contribute to cancer outcomes. Here, we examine the relationship between WE, OS, PSF, metal ions, other carcinogens, and the development of different cancers from the viewpoint of physiological and biochemical mechanisms.
New Insights in the Era of Clinical Biomarkers as Potential Predictors of Systemic Therapy-Induced Cardiotoxicity in Women with Breast Cancer: A Systematic Review

Simple Summary Cancer therapy-related cardiac dysfunction (CTRCD) has been an urgent medical issue in patients that receive breast cancer therapies including anthracycline-based chemotherapies and/or targeted anti-HER2 therapies such as trastuzumab. Traditional biomarkers used as standard of care may be useful indicators of cardiac damage but their use to predict the onset of CTRCD lacks reliability. Ongoing clinical studies aim to explore new insights into the use of traditional biomarkers and investigate the promising role of novel biomarkers as reliable indicators and/or predictors of CTRCD. Patients with breast cancer could benefit from an alternative cardiac risk stratification plan that has the potential to predict the onset of CTRCD and/or detect CTRCD at early stages. The aim of this systematic review is to provide an overview of the human studies, which explore novel insights into traditional biomarkers and/or novel biomarkers that can be used for the early detection and/or prediction of CTRCD in breast cancer patients undergoing cardiotoxic-cancer therapies. Abstract Cardiotoxicity induced by breast cancer therapies is a potentially serious complication associated with the use of various breast cancer therapies. Prediction and better management of cardiotoxicity in patients receiving chemotherapy is of critical importance. However, the management of cancer therapy-related cardiac dysfunction (CTRCD) lacks clinical evidence and is based on limited clinical studies. Aim: To provide an overview of existing and potentially novel biomarkers that possess a promising predictive value for the early and late onset of CTRCD in the clinical setting. Methods: A systematic review of published studies searching for promising biomarkers for the prediction of CTRCD in patients with breast cancer was undertaken according to PRISMA guidelines. A search strategy was performed using PubMed, Google Scholar, and Scopus for the period 2013–2023. All subjects were >18 years old, diagnosed with breast cancer, and received breast cancer therapies. Results: The most promising biomarkers that can be used for the development of an alternative risk cardiac stratification plan for the prediction and/or early detection of CTRCD in patients with breast cancer were identified. Conclusions: We highlighted the new insights associated with the use of currently available biomarkers as a standard of care for the management of CTRCD and identified potentially novel clinical biomarkers that could be further investigated as promising predictors of CTRCD.
Classicality Test in Neutral Pairs

In this paper we discuss the possibility of classicality experimental verification at -factories. We show that for three moments of time it is possible to observe violations of Wigner’s inequalities, even with the 50% fraction of background processes. DOI: 10.1134/S1547477123030263 INTRODUCTION Since the early years of quantum mechanics, repeated attempts have been made to reduce the probabilistic quantum paradigm to a more familiar and illustrative deterministic classical paradigm. To test the fundamental possibility of such a reduction, it is necessary to formulate the criteria that physical systems in the classical paradigm must satisfy. 1. CONCEPTS OF LOCAL AND MACROSCOPIC REALISM Currently, two sets of such criteria are the most widely used. The first set of criteria was proposed in the work of A. Einstein, B. Podolsky, and N. Rosen [1]. This set, called the concept of Local Realism (LR), includes three principles: (1) Classical realism (CR): the totality of all characteristics of any physical system exists jointly and independently of the observer. In this case, it may turn out that the observer is not able to jointly measure the entire set of such characteristics with a classical measuring device. The CR principle means that, if a quantum system has observables , , and so on, then there are joint probabilities that the quantum system has a spectrum value observable , spectrum value observable , and so on; that is, there are joint probabilities (1) (2) Locality: if two measurements are made with classical measuring instruments and , at two different points of 4-dimensional space-time, which are separated from each other by a spacelike interval during the entire measurement time, then the state of the classical device does not affect the results of the classic device in any way (and vice versa). Under this condition, the “local experimenter” of the subsystem , which measures the spectrum of the observed , knows nothing about the results of measuring the spectrum of the observed . Therefore, it must sum over all values of the spectrum of the observed . In this case, the principle of locality makes it possible to exclude the influence of the state of the classical device in the measurement results of the observable in the subsystem . This leads to the following equality: (2) Equation (2) is called the no-signaling condition (NSC) [2, 3]. If one of the subsystems has two or more jointly nonmeasurable observables, operations with joint probabilities require an additional assumption so as not to conflict with the requirement of the locality. Such an assumption can be either the requirement that the measurement does not destroy the state of one of 0 0 s s B B
Statistical assessment of evaporation duct propagation

Over-the-horizon propagation from 0.6 to 18 GHz is presented in the form of accumulated frequency distributions of path loss, showing the comparisons between theory and two measurement programs. The path-loss theory is based on waveguide solutions for a family of refractivity/height profiles characterized by evaporation duct height in the range of 1 to 40 m. Annual frequency distributions of evaporation duct height have been prepared based on 15 years of marine surface meteorological observations and are combined with the waveguide path loss/duct height results to give accumulated frequency distributions from experiments performed in the Aegean Sea and the North Sea. Excellent agreement of theory and observation is noted in most cases. >
Explosion Venting Design for a Special Vehicle

Explosion vents are designed for a special vehicle, via which the energy released by ammunition explosion inside the vehicle can be quickly discharged to achieve the goal of explosion venting. These vents aim to reduce the damage of shock waves generated by ammunition explosion to the special vehicle and alleviate the secondary damage the subsequent shock waves may cause.
Edge detection algorithm for noisy remote sensing image using directional filter

Remote sensing image edge detection is the basis of remote sensing image registration and recognition. In view of the noise formed in the process of remote sensing image acquisition, a new edge detection algorithm based on directional filter is proposed to improve the accuracy of remote sensing image registration and recognition. The directional filter is based on wavelet transform denoising, and three main features including scale, direction and shape of wave are introduced. The target edge can be identified more accurately in the noisy image by the directional filter, and the edge detection result image is obtained by binarization segmentation and non-maximum suppression. Through experimental comparison with other denoising detection algorithms, more accurate edge detection results can be obtained, and there are obvious advantages in operation efficiency.