Miracle-dz/UniFAR-FTUs huggingface dataset:
A Survey on Precision agriculture using Machine Learning

In modern farming fidelity permits the precise application of information sources, such as toxicant, seed, manure, and effluent, at the precise moment of harvest in order to increase productivity and crop yields. Ranchers may readily determine the crops' range by tracking them using sensors that are collected from the fields, protecting the resources being used and reducing the impact of weeds on the environment. Most Indian ranchers use standard cultivating techniques to determine the crop yield that should be developed in order. In any event, the ranchers don't sacrifice crop productivity because it depends on the characteristics of the soil due to abiotic variables. This research suggestsa yield recommendation apparatus that encourages ranchers to select the appropriate crop to plant in their lands in this manner. selecting information about systems by machine.
Mechanisms of Long Non-Coding RNA in Breast Cancer

The landscape of pervasive transcription in eukaryotic genomes has made space for the identification of thousands of transcripts that are difficult to frame in a specific functional category. A new class has been broadly named as long non-coding RNAs (lncRNAs) and shortly defined as transcripts that are longer than 200 nucleotides with no or limited coding potential. So far, about 19,000 lncRNAs genes have been annotated in the human genome (Gencode 41), nearly matching the number of protein-coding genes. A key scientific priority is the functional characterization of lncRNAs, a major challenge in molecular biology that has encouraged many high-throughput efforts. LncRNA studies have been stimulated by the enormous clinical potential that these molecules promise and have been based on the characterization of their expression and functional mechanisms. In this review, we illustrate some of these mechanisms as they have been pictured in the context of breast cancer.
Surveillance Post Surgery for Retroperitoneal Soft Tissue Sarcoma

Complete en bloc surgical resection offers the best opportunity for the cure of primary retroperitoneal sarcomas (RPS). The potential for disease recurrence, in the form of both loco-regional recurrence and distant metastases, underpins the rationale for postoperative surveillance. There is a paucity of high-quality evidence underpinning follow-up for RPS patients, and most practice guidelines draw from expert opinion and evidence from soft tissue sarcomas of the extremities. The available observational retrospective data analysis has failed to demonstrate that high-intensity radiological surveillance improves the overall survival in patients. The lack of a robust evidence base has given rise to variations in approaches to post-operative surveillance strategies adopted by specialist centres managing RPS across the world. More high-quality prospective research is needed and planned to more clearly support surveillance approaches that balance oncologic outcomes, patient-centric care, and health service value. Risk stratification tools exist and are available for use in routine practice. Their use will likely support more individualised post-operative surveillance moving forward. Surveillance will likely be underpinned by serial radiological imaging for the medium term. However, developments in genomics offer hope for biomarkers such as ctDNA to impact patient care positively in the future and further support individualised patient care pathways.
Increased low frequency fluctuation in the brain after acupuncture treatment in CSVDCI patients: A randomized control trial study

Background Cerebral small vessel disease (CSVD) is one of two cognition-impairing diseases. Acupuncture (Acu) is a flexible treatment with few adverse effects and is thus widely used to treat neurological problems. Methods We recruited a total of 60 patients and assigned them to two groups (n = 30 each group). During the study, some participants were excluded by quality control, and a total of 44 subjects (25 Acu and 19 controls) were completed to investigate the therapeutic efficacy of acupuncture on CSVD cognitive impairment (CSVDCI). The following demographic and clinical variables were compared between the two groups: gender, age, education, smoking, alcohol, Montreal cognitive assessment (MoCA), symbol digit modalities test (SDMT), verbal fluency test (VFT), digit span task (DST), Boston naming test (BNT) scores, and amplitude of low-frequency fluctuation (ALFF) under the typical band (0.01–0.08 Hz). Mixed effect analysis was utilized to test for differences between the two groups before and after the treatment. Results Following acupuncture treatment, the Acu group scored higher on MoCA, SDMT, VFT, DST, and BNT compared to controls (P < 0.05). The brain regions showing substantially greater ALFF values in the Acu group were the right inferior temporal gyrus, left middle occipital gyrus, left superior occipital gyrus, left insula, bilateral postcentral gyrus, right superior parietal gyrus, right cerebellum, right precuneus, and right precentral gyrus (P < 0.005, no correction). The ALFF values in the right inferior temporal gyrus (P = 0.027), left middle occipital gyrus (P = 0.005), left superior occipital gyrus (P = 0.011), and right superior parietal gyrus (P = 0.043) were positively associated with MoCA. Conclusion We found that acupuncture modulates the functional activity of temporal, occipital, and parietal regions of the brain in CSVDCI patients.
Fabrication of novel oxochalcogens halides of manganese and tin nanocomposites as highly efficient photocatalysts for dye degradation and excellent antimicrobial activity

The dark brown and white crystals of manganese and tin (Mn2Se3Cl2O7 and SnSe3O4Cl) have been synthesized by solid-state reaction at 450 C. The morphology and the elemental analysis of newly synthesized compounds were studied by SEM and EDX Analysis. SEM analysis reveals that the particle size for Mn2Se3Cl2O7 was found to be 0.2–2.5 μm and for SnSe3O4Cl 2.0–6.0 μm. The EDX studies showed the presence of Mn, Se, O, Cl, and Sn elements. Powdered XRD confirmed the presence of a new phase present in these compounds. Under UV-vis irradiation, the kinetics of methylene blue (MB) degradation catalyzed by produced nanoparticles were monitored. The dye degradation efficiency was estimated, and results reveals that after 150 min of irradiation, almost 75% of the dye was degraded in the presence of Mn compound while 71% degradation was shown by Sn compound. Both composites display antimicrobial activity against Staphylococcus aureus and Escherichia coli with a maximum value of 34.5 mm. The maximum antimicrobial activity shown by Mn-incorporated nanocomposites estimated at 32.5 mm was against Gram-positive bacteria and 26.4 mm against Gram-negative bacteria. Similarly, the maximum antifungal activity shown by Sn incorporated estimated at 33.9 mm was compared to Gram-positive bacteria and 27.8 mm against Gram-negative bacteria.
Target-Conformal Optimization-Based Actuator Placement for Ultrasound-Mediated Hyperthermia in Cancer Treatments

In hyperthermia for cancer treatments, tumors are heated to improve the outcome of radio- and chemotherapies. Using extracorporeal high-intensity focused ultrasound (HIFU) transducers, the heating can be applied noninvasively, accurately, and with high acoustic power. The heating location can be changed by electronic beam steering, within the transducer’s small local heating range, and by mechanically repositioning the transducer, which effectively shifts the local range to enable the treatment of larger tumors. An important problem is the selection of the sonication points, i.e., the discrete locations reachable by electronic beam steering, and the admissible mechanical transducer positions, which must be performed prior to treatment, and can be seen as an actuator selection problem. Clearly, the selected sonication points and transducer positions have a major impact on the achievable tumor temperatures, and their number is directly related to the controller’s complexity and, thereby, real-time feasibility. To address this challenging problem, this brief presents a target-conformal optimization-based actuator placement procedure, designed to assist the clinician in enabling maximum treatment quality using only a limited number of sonication points and transducer positions. The method is computationally tractable, and takes into account the specific tumor geometry and tissue properties.
High-Order Semantic Decoupling Network for Remote Sensing Image Semantic Segmentation

Low-order features based on convolution kernel are easy to be distorted when encountering dramatic view angle transformation and atmospheric scattering in remote sensing (RS) images. To address this concern, this article first proposes to operate semantic segmentation of RS images based on the high-order information, which can represent the relative relationship of low-order features and is robust and stable when suffering feature distortion. Besides, semantic decouples have recently been well researched and have achieved significant improvement in image understanding. Thus, in this article, a high-order semantic decoupling network (HSDN) is proposed to disentangle features by semantics based on high-order features. Specifically, HSDN first represents each pixel by calculating the pixel-level affinity as a high-order feature and then clusters these pixels into different semantics. Afterward, an attention-like mask generation module is designed for both intra-semantic and inter-semantic groups, leading to three kinds of masks, including the semantic decoupling mask (SDM), which utilizes each high-order cluster centroid as a mask to compact features intracluster and expand different interclusters, so as to improve semantic disentangle performance to a better extent; semantic enhancement mask (SEM), which records pixel-level relative correlation within a class to sufficiently exploit high-order features and could enhance feature robustness; and boundary supplementary mask (BSM), which aims to process borderline pixels to reduce cluster errors. Finally, by applying masks on pixels both within classes and on borderlines, semantic decoupled features are generated and concatenated to realize segmentation. The quantitative and qualitative experiments are conducted on two large-scale fine-resolution RS image datasets to demonstrate the significant performance of adopting high-order representation. Besides, we also implement numerous experiments to validate the effectiveness of the proposed semantic decouple framework in dealing with complicated and distortion-prone RS image segmentation tasks.
Logical necessity and transitivity of causal relations in stories

central concern of this study is the problem of identifying inferences that connect units in narrative discourse. A recursive transition network model is described that analyzes and represents a story as a causal network of categorized clauses and labeled relations. Procedural criteria used to identify inferences and the assumptions that inferences operate over distances in the text and are transitive, resulting in a network representation, are then tested. In each of two experiments, naive judges rated the strength of relations between pairs of clauses sampled from four different stories. In one experiment, the causal distance between clauses was varied and compared to temporal and reference factors; in the other, the judgment criteria and kinds of relations were varied. The data show that the causal relations are operative and transitive, in that the strength of the relations declined linearly as a function of causal distance in the network representation, independent of temporal and reference distanc.
Robust Assessment of Macromolecular Fraction (MMF) in Muscle with Differing Fat Fraction Using Ultrashort Echo Time (UTE) Magnetization Transfer Modeling with Measured T1

Magnetic resonance imaging (MRI) is widely regarded as the most comprehensive imaging modality to assess skeletal muscle quality and quantity. Magnetization transfer (MT) imaging can be used to estimate the fraction of water and macromolecular proton pools, with the latter including the myofibrillar proteins and collagen, which are related to the muscle quality and its ability to generate force. MT modeling combined with ultrashort echo time (UTE-MT modeling) may improve the evaluation of the myotendinous junction and regions with fibrotic tissues in the skeletal muscles, which possess short T2 values and higher bound-water concentration. The fat present in muscle has always been a source of concern in macromolecular fraction (MMF) calculation. This study aimed to investigate the impact of fat fraction (FF) on the estimated MMF in bovine skeletal muscle phantoms embedded in pure fat. MMF was calculated for several regions of interest (ROIs) with differing FFs using UTE-MT modeling with and without T1 measurement and B1 correction. Calculated MMF using measured T1 showed a robust trend, particularly with a negligible error (<3%) for FF < 20%. Around 5% MMF reduction occurred for FF > 30%. However, MMF estimation using a constant T1 was robust only for regions with FF < 10%. The MTR and T1 values were also robust for only FF < 10%. This study highlights the potential of the UTE-MT modeling with accurate T1 measurement for robust muscle assessment while remaining insensitive to fat infiltration up to moderate levels.
Automated Classification of MRI Brain Images

The death rate due to brain tumor is increasing rapidly. The accumulation of cells in an uncontrolled manner leads to brain tumor. The life taking tumor can be cured if it is detected in the early stage. This paper deals with analyzing the performance of the different kernels functions on SVM classification algorithm. The performance of the proposed algorithm is being measured by parameters like accuracy, sensitivity, specificity and precision. The kernels like Laplace RBF kernel, Gaussian kernel, polynomial kernel, Hyperbolic tangent kernel, and Sigmoid kernel are applied on SVM. Among the various kernel functions, Gaussian kernel SVM gave good results. Otsu segmentation is applied on the abnormal images to high light the tumor region in the brain MRI images.
Trans-generational immune priming against American Foulbrood does not affect the performance of honeybee colonies

Honeybees are major pollinators for our food crops, but at the same time they face many stressors all over the world. One of the major threats to honeybee health are bacterial diseases, the most severe of which is the American Foulbrood (AFB). Recently a trans-generational vaccination approach against AFB has been proposed, showing strong potential in protecting the colonies from AFB outbreaks. Yet, what remains unstudied is whether the priming of the colony has any undesired side-effects. It is widely accepted that immune function is often a trade-off against other life-history traits, hence immune priming could have an effect on the colony performance. In this experiment we set up 48 hives, half of them with primed queens and half of them as controls. The hives were placed in six apiaries, located as pair of apiaries in three regions. Through a 2-year study we monitored the hives and measured their health and performance. We measured hive weight and frame contents such as brood amount, worker numbers, and honey yield. We studied the prevalence of the most common honeybee pathogens in the hives and expression of relevant immune genes in the offspring at larval stage. No effect of trans-generational immune priming on any of the hive parameters was found. Instead, we did find other factors contributing on various hive performance parameters. Interestingly not only time but also the region, although only 10 km apart from each other, had an effect on the performance and health of the colonies, suggesting that the local environment plays an important role in hive performance. Our results suggest that exploiting the trans-generational priming could serve as a safe tool in fighting the AFB in apiaries.
Clinical Outcomes of the Intraocular Lens Injector and Busin Glide for Descemet Stripping Automated Endothelial Keratoplasty in Patients with Iridocorneal Endothelial Syndrome

Purpose: To report the outcomes of Descemet stripping automated endothelial keratoplasty (DSAEK) performed in iridocorneal endothelial (ICE) syndrome patients using the intraocular lens injector (injector), in comparison with those using the Busin glide. Methods: In this retrospective, interventional comparative study, we evaluated the outcomes of DSAEK performed using the injector (n = 12) or the Busin glide (n = 12) for patients with ICE syndrome. Their graft position and postoperative complications were recorded. Their best-corrected visual acuity (BCVA) and endothelial cell loss (ECL) were monitored over a 12-month follow-up period. Results: DSAEK was conducted successfully in the 24 cases. The BCVA improved from the preoperative 0.99 ± 0.61 to 0.36 ± 0.35 at 12 months after operation (p < 0.001), with no significant difference between the two groups (the injector group and the Busin group) (p = 0.933). ECL at 1 month after DSAEK was 21.80 ± 15.01% in the injector group, which was significantly lower than 33.69 ± 9.75% of the Busin group (p = 0.031). No surgery-related complications were observed in the 24 cases intraoperatively or postoperatively except that one case suffered from postoperative graft dislocation, without statistical difference between the two groups. Conclusions: At 1 month after surgery, the use of graft injector for delivering DSAEK-based endothelial graft may cause significantly less endothelial cell damage than the pull-through technique used in the application of Busin glide. The injector allows safe endothelial graft delivery without the need of anterior chamber irrigation, which increases the ratio of successful graft attachment.
A Universal Adaptive Neural Control Scheme for Nonlinear Uncertain System

The traditional BP algorithm is modified and a kind of novel model reference adaptive control (MRAC) scheme is proposed based on generalized BP (GBP) algorithm. The convergence of the control scheme is also analyzed according to Lyapunov theory. To test its effectiveness, the proposed model is used to control a nonlinear uncertain system. Simulation results indicate that the controller is effective in controlling a general class of nonlinear systems.
Characterising the cave bear Ursus spelaeus Rosenmüller by ZooMS: a review of peptide mass fingerprinting markers

ABSTRACT In the last decade, the identification of bone fragments by peptide mass fingerprinting or zooarchaeology by mass spectrometry is developing as a powerful tool in Quaternary palaeontology. The sequence of amino acids that make up the bone collagen molecule shows slight variations between taxa, which can be studied by mass spectrometry for taxonomic purposes. This requires reference databases that allow peptide identification. Although the cave bear (Ursus spelaeus Rosenmüller, 1794) is a common component in many European Pleistocene cave sites, no peptide fingerprint taxonomic study has paid special attention to this species up to now. For peptide markers in Ursidae, the most recent proposal is based on collagen obtained from a modern brown bear sample. In this work we attempt to cover this gap by studying bone collagen of cave and brown bear samples from different origins and different chronology, applying matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI TOF). We also performed an in-silico study of ursid bone collagen sequences published in databases. In our results we detected some discrepancies between the peptides obtained from both in silico and MALDI TOF analysis of fossil collagen and those published in the literature, in which we conclude that there are some misidentified peptides. The identification of skeletal remains by means of their peptide fingerprint is proving to be a powerful tool in palaeontology, which will bear greater fruit once the limitations of a technique that is in its initial stages have been overcome.
Effects of two-week machine massage on muscle properties in adolescent wrestlers

Objective: This study aimed to investigate the effect of a two-week machine massage on the physical properties of the erector spinae and serum biochemical indexes of adolescent athletes after training. Methods: Sixteen male adolescent wrestlers were recruited (age: 15 ± 1 year; height: 166 ± 7 cm; weight: 56 ± 7 kg) and randomly assigned to machine massage (MA, 8) and control (CO, 8) groups. Participants in the MA group received machine massage for 20 min after each wrestling training from Monday to Saturday (except on Thursday) for two weeks, while the participants in the CO group recovered naturally. Over the course of two weeks, all the participants underwent similar wrestling training program under the guidance of a professional coach. Before and after the intervention, serum urea and creatine kinase (CK) levels were measured in a fasting state. A Myoton Pro digital muscle evaluation system was used to measure the physical properties of the erector spinae, including the oscillation frequency, logarithmic decrement of a muscle’s natural oscillation, and dynamic stiffness. Results: After two weeks of machine massage treatment, the dynamic stiffness of the erector spinae in the MA group decreased by 12.90% and that in the CO group increased by 2.34%, indicating a significant difference between the two groups (p = 0.04, ƞ 2 = 0.286). The decrease in the logarithmic decrement of a muscle’s natural oscillation value in the MA was significantly greater than that in the CO (p = 0.003, ƞ 2 = 0.286). Moreover, the serum CK values decreased by 33.84% in the MA group and by 1.49% in the CO group, despite a trend of change between the groups (p = 0.062, ƞ2 = 0.084). No significant difference was found in the improvement in serum urea levels between the two groups after two weeks of treatment. Conclusion: Results of the present study indicated that a two-week machine massage had a positive effect on the improvement of the physical properties of the erector spinae of wrestlers during training.
An Algorithm for Fuzzy Concept Lattices Building with Application to Social Navigation

Due to the fuzziness of information, fuzzy concept lattices (FCL) are proposed as effective tools for data analysis and knowledge discovery on the fuzzy formal context. But the mining of large database needs efficient algorithms for FCL building. In this paper, a fast and automatic algorithm for FCL building is proposed, called FCLB algorithm, for generating fuzzy concepts from a given fuzzy formal context and a set of fuzzy sets, automatically building a fuzzy concept lattice and representing it graphically. This work has been applied successfully to the social navigation system which aimed to aid users in finding information more effectively.