Miracle-dz/UniFAR-FTUs huggingface dataset:
Stalk rots complex diseases related to kind of animal manure and insecticide and its effect on the quality of maize grains

Maize genotypes' reactions against stalk rot causal organisms showed that the lowest disease incidence was recorded in cases fertilized by decomposing animal manure (7-8 weeks old) and insect control, compared with those fertilized by fresh animal manure and no insect control. The highest percent of insect infection as well as the highest lodging percent were recorded in soil treated with fresh manure with no insect control. The weight of 100 kernels decreased as well as the yield per two rows with plots treated with fresh animal manure and no insect control. Maize hybrids single cross 10 (SC10) had a suitable level of resistance to tested diseases and recorded a lower infection percent of tested diseases, higher values of weight of 100 kernels, and higher yield per tested row than those recorded with the tested open-pollinated variety (Balady). Fresh animal manure resulted in increasing disease severity for each tested disease, indicating the danger of farmers fertilizing their farms with fresh animal manure before storing it for a few weeks. The obtained results also illustrated high germination percent and high grain component percent, i.e., protein, oil, ash, fiber, carbohydrates, and phenols, in all grains collected from plots that were fertilized by stored animal manure (7-8 weeks old) and sprayed against insects, as compared with the control treatment. Overall, this study never recommended the use of fresh farmyard animal manure before storing it for at least 7-8 weeks for fertilization of the soil. All in all, true disease control, the lowest kernel rot diseases, and high quantitative and qualitative yields per 2 rows were obtained from the plots sprayed with insecticide and fertilized by stored animal manure (decomposing animal manure). In short, the study found that using decomposing animal manure (7-8 weeks old) and insect control is the best way to prevent stalk rot diseases in maize. Fresh animal manure should not be used, as it can increase the severity of the diseases.
Optical refractive index biosensor using evanescently coupled lateral Bragg gratings on silicon-on-insulator

In this paper, we present a compact silicon-on-insulator optical biosensor based on lateral Bragg gratings evanescently coupled to a waveguide. The device is fabricated by electron-beam lithography and dry-etched in a single step with inductive coupled plasma reactive ion etching (ICP-RIE). Fully etched grating couplers are used to couple the light in and out of the chip, while lateral Bragg gratings are used as the sensing element of the device. A sensitivity of 22 nm/RIU is obtained by exposing the device to deionized water with different NaCl concentrations with a footprint area of 15 × 4 µm2 that allows for densely multiplexed solutions.
Mode feedback control strategy for continuous‐time Markovian jump linear systems with controllable mode transition rate matrix

This paper investigates mode feedback control strategy for continuous‐time Markovian jump linear systems with controllable mode transition rate matrix (MTRM). Based on the fact that system stability as well as its performance is dependent on MTRM, a mode feedback controller is proposed to perform control on MTRM such that system stability is achieved. Meanwhile, this strategy can help to improve system performance since it can adjust the occurrence probability of each subsystem. Firstly, taking into account that MTRM will totally determine system stability in absence of state feedback controller, the existence and restrictions on mode feedback controller are discussed where two cases are included. Then, based on a quadratic stabilization cost function that is a combination of state cost and control cost, a feasible solution of mode feedback control strategy is then obtained with its detailed algorithm given. Simulation results including comparisons with current state feedback mechanism are provided to illustrate the effectiveness of the proposed strategy.
Incremental Algorithms: Solving Problems in a Changing World

A typical algorithm for a combinatorial optimization problem is given a static set of input, and finds a single solution. This kind of algorithm cannot be used, however, in situations where the input and solutions change over time due to evolving constraints. This dissertation explores incremental problems, one class of optimization problems that deals with this type of situation. An incremental algorithm is given a sequence of input, and finds a sequence of solutions that build incrementally while adapting to the changes in the input. Online algorithms also take in a sequence of input and produce incremental solutions; unlike their incremental counterparts, however, they do not know the input sequence in advance. We use our incremental results to better understand online algorithms and to indicate how their performance can be improved. Most combinatorial optimization problems can be extended to the incremental setting. We define general incremental formulations of covering and packing problems, and give incremental algorithms for such classes of problems. We study specific problems in detail, such as incremental bipartite matching, network flow, and edge cover, and find bounds on their complexity and competitiveness. Lastly, we explore different ways to define incremental problems, and discuss how to relax some of the constraints that limit the power of our incremental model.
Phytochemical-Mediated Biosynthesis of Silver Nanoparticles from Strobilanthes glutinosus: Exploring Biological Applications

The application of green synthesis for silver nanoparticles in nanomedicine has experienced significant growth. Strobilanthes glutinosus, a plant primarily located in the Himalayas, remains largely unexplored. Considering the biomedical value of S. glutinosus, phytochemicals from this plant were used for the biosynthesis of silver nanoparticles. Silver nanoparticles were synthesized from aqueous extract of root and leaves of Strobilanthes glutinosus. The synthesized silver nanoparticles were characterized using UV–Vis spectrophotometry, Fourier-transform infrared spectroscopy, transmission electron microscopy, and X-ray diffraction. Total phenolic and flavonoid contents of plants were determined and compared with nanoparticles. The biomedical efficacy of plant extracts and silver nanoparticles was assessed using antioxidant and antibacterial assays. The UV–Vis spectra of leaf- and root-extract-mediated AgNPs showed characteristic peaks at 428 nm and 429 nm, respectively. TEM images revealed the polycrystalline and spherical shapes of leaf- and root-extract-mediated AgNPs with size ranges of 15–60 nm and 20–52 nm, respectively. FTIR findings shown the involvement of phytochemicals of root and leaf extracts in the reduction of silver ions into silver nanoparticles. The crystalline face-centered cubic structure of nanoparticles is depicted by the XRD spectra of leaf and root AgNPs. The plant has an ample amount of total phenolic content (TPC) and total flavonoid content (TFC), which enhance the scavenging activity of plant samples and their respective AgNPs. Leaf and root AgNPs have also shown good antibacterial activity, which may enhance the medicinal value of AgNPs.
On The Continuity of the Spectrum of Fields of Operators

Based on a paper by Beckus and Bellisard, we study the continuity of fields of operators, mainly by studying their associated spectra. We discuss and extend Beckus and Bellisard’s results about self-adjoint operators, including unbounded, self-adjoint operators, and we also look briefly at bounded, normal operators.
Generalized Colorings of Graphs

A graph coloring is an assignment of labels called “colors” to certain elements of a graph subject to certain constraints. The proper vertex coloring is the most common type of graph coloring, where each vertex of a graph is assigned one color such that no two adjacent vertices share the same color, with the objective of minimizing the number of colors used. One can obtain various generalizations of the proper vertex coloring problem, by strengthening or relaxing the constraints or changing the objective. We study several types of such generalizations in this thesis. Series-parallel graphs are multigraphs that have no K4-minor. We provide bounds on their fractional and circular chromatic numbers and the defective version of these parameters. In particular we show that the fractional chromatic number of any series-parallel graph of odd girth k is exactly 2k/(k − 1), confirming a conjecture by Wang and Yu. We introduce a generalization of defective coloring: each vertex of a graph is assigned a fraction of each color, with the total amount of colors at each vertex summing to 1. We define the fractional defect of a vertex v to be the sum of the overlaps with each neighbor of v, and the fractional defect of the graph to be the maximum of the defects over all vertices. We provide results on the minimum fractional defect of 2-colorings of some graphs. We also propose some open questions and conjectures. Given a (not necessarily proper) vertex coloring of a graph, a subgraph is called rainbow if all its vertices receive different colors, and monochromatic if all its vertices receive the same color. We consider several types of coloring here: a no-rainbow-F coloring of G ii is a coloring of the vertices of G without rainbow subgraph isomorphic to F ; an F -WORM coloring of G is a coloring of the vertices of G without rainbow or monochromatic subgraph isomorphic to F ; an (M,R)-WORM coloring of G is a coloring of the vertices of G with neither a monochromatic subgraph isomorphic to M nor a rainbow subgraph isomorphic to R. We present some results on these concepts especially with regards to the existence of colorings, complexity, and optimization within certain graph classes. Our focus is on the case that F , M or R is a path, cycle, star, or clique.
Identification of Isomorphism in Kinematic Chains by Using the Reduced Graph Matrix

—Kinematic chain synthesis normally begins with the generation of a comprehensive list of candidate solutions followed by a time-consuming procedure for isomorph elimination. As a result, the search for isomorphisms in kinematic chains has long attracted the attention of many researchers. Several methods and algorithms have been proposed in the past. Nonetheless, the field still needs fast, efficient and reliable means to prevent duplications across kinematic chains (KC) (i.e., isomorphisms), particularly for configurations with a significant number of bars. Mechanical designers are resorting to kinematic chains and mechanisms with multiple bars to accomplish more complex operations and movements. This complicates the procedure of determining isomorphism. In this paper, we present a simple and efficient method for identifying isomorphisms in kinematic chains by employing a reduced graph matrix, which reduces the adjacency matrix into a compact matrix corresponding to linkages between non-binary bars while implicitly accounting for binary bars. The algorithm’s efficiency and computing complexity are assessed for a number of published situations, including single-joint kinematic chains with 8, 10, 12 bars, and three-complex 13, 15, 28 bars, and lastly 42-bar kinematic chains. This comparison demonstrates the validity and effectiveness of the proposed method.
Computational pharmacogenotype extraction from clinical next-generation sequencing

Background Next-generation sequencing (NGS), including whole genome sequencing (WGS) and whole exome sequencing (WES), is increasingly being used for clinic care. While NGS data have the potential to be repurposed to support clinical pharmacogenomics (PGx), current computational approaches have not been widely validated using clinical data. In this study, we assessed the accuracy of the Aldy computational method to extract PGx genotypes from WGS and WES data for 14 and 13 major pharmacogenes, respectively. Methods Germline DNA was isolated from whole blood samples collected for 264 patients seen at our institutional molecular solid tumor board. DNA was used for panel-based genotyping within our institutional Clinical Laboratory Improvement Amendments- (CLIA-) certified PGx laboratory. DNA was also sent to other CLIA-certified commercial laboratories for clinical WGS or WES. Aldy v3.3 and v4.4 were used to extract PGx genotypes from these NGS data, and results were compared to the panel-based genotyping reference standard that contained 45 star allele-defining variants within CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, CYP4F2, DPYD, G6PD, NUDT15, SLCO1B1, TPMT, and VKORC1. Results Mean WGS read depth was >30x for all variant regions except for G6PD (average read depth was 29 reads), and mean WES read depth was >30x for all variant regions. For 94 patients with WGS, Aldy v3.3 diplotype calls were concordant with those from the genotyping reference standard in 99.5% of cases when excluding diplotypes with additional major star alleles not tested by targeted genotyping, ambiguous phasing, and CYP2D6 hybrid alleles. Aldy v3.3 identified 15 additional clinically actionable star alleles not covered by genotyping within CYP2B6, CYP2C19, DPYD, SLCO1B1, and NUDT15. Within the WGS cohort, Aldy v4.4 diplotype calls were concordant with those from genotyping in 99.7% of cases. When excluding patients with CYP2D6 copy number variation, all Aldy v4.4 diplotype calls except for one CYP3A4 diplotype call were concordant with genotyping for 161 patients in the WES cohort. Conclusion Aldy v3.3 and v4.4 called diplotypes for major pharmacogenes from clinical WES and WGS data with >99% accuracy. These findings support the use of Aldy to repurpose clinical NGS data to inform clinical PGx.
Proteome Landscape during Ripening of Solid Endosperm from Two Different Coconut Cultivars Reveals Contrasting Carbohydrate and Fatty Acid Metabolic Pathway Modulation

Cocos nucifera L. is a crop grown in the humid tropics. It is grouped into two classes of varieties: dwarf and tall; regardless of the variety, the endosperm of the coconut accumulates carbohydrates in the early stages of maturation and fatty acids in the later stages, although the biochemical factors that determine such behavior remain unknown. We used tandem mass tagging with synchronous precursor selection (TMT-SPS-MS3) to analyze the proteomes of solid endosperms from Yucatan green dwarf (YGD) and Mexican pacific tall (MPT) coconut cultivars. The analysis was conducted at immature, intermediate, and mature development stages to better understand the regulation of carbohydrate and lipid metabolisms. Proteomic analyses showed 244 proteins in YGD and 347 in MPT; from these, 155 proteins were shared between both cultivars. Furthermore, the proteomes related to glycolysis, photosynthesis, and gluconeogenesis, and those associated with the biosynthesis and elongation of fatty acids, were up-accumulated in the solid endosperm of MPT, while in YGD, they were down-accumulated. These results support that carbohydrate and fatty acid metabolisms differ among the developmental stages of the solid endosperm and between the dwarf and tall cultivars. This is the first proteomics study comparing different stages of maturity in two contrasting coconut cultivars and may help in understanding the maturity process in other palms.
Optical frequency comb profilometry based on a single-pixel phase imaging

In this research, we introduce a new system based on the ghost imaging, for measuring the surface profile of an object using optical frequency comb laser and a single-pixel camera. The optical frequency comb laser was used to record the relative phase of the object precisely whilst the ghost imaging technique was applied to reconstruct the object's profile. The effect of using a mask on the parameters such as number of object point, number of measurements and sparse number related to the complexity of the object for reconstruction was studied by a simulation. The performance of the system strongly depends on the design of the mask. The random mask and the Hadamard mask were used to estimate the performances in the optical frequency comb profilometry.
DESIGN AND IMPLEMENTATION OF BAND-PASS FILTERS FOR THE 5TH GENERATION WIRELESS SYSTEM

This paper proposes a band-pass filter with a center frequency of 4.2 GHz, which can be applied in fifth - generation (5G) mobile communication. Currently, 5G networks are experiencing rapid development and are highly regarded as the primary network technology. Currently, 5G technology can be divided into two major frequency ranges. The first range is defined by 3GPP and operates below 6 GHz, known as the sub-6 GHz frequency range. The second range falls approximately between 30 GHz and 100 GHz. This paper aims to design a microstrip band-pass filter with a center frequency of 4.2 GHz. By modifying the line width, shape, and the number of couplings in the filter, we can achieve the desired frequency range and increase the bandwidth. A 4.2 GHz bandpass filter was fabricated on an FR4 substrate with a relative dielectric constant of 4.4, and the overall dimensions is 17×5×1.55 mm3.and measured. T Through simulation analysis, it can be understood that adding the inner ring with a gap can improve the overall performance of the filter.
A Modified Enucleation and Deflation to Treat Large Ameloblastoma in the Mandible

Objective Treatment of large ameloblastoma with a conservative method. Case Presentation. Ameloblastomas are benign tumors of odontogenic origin. These tumors are locally invasive with a high recurrence rate. This case report will present a conservative approach to treating large ameloblastoma in the mandible using modified enucleation and deflation technique. The patient presents with a recurrence of large unicystic ameloblastoma. The following patient is treated with the two-stage enucleation and deflation technique. One-year post-treatment follow-up shows satisfactory healing, with good bone regeneration in the defected area, showing no signs of recurrence. Conclusion The technique that will be discussed in this case report provides an alternative treatment for ameloblastomas of the mandible. This approach can avoid radical operative procedures, such as jaw resection and bone reconstruction.
The Effects of the Badminton Teaching-Assisted System Using Electromyography and Gyroscope on Learners' Badminton Skills

Swing movements and muscle strength are essential for mastering badminton techniques. Traditionally, students learn badminton through their instructor's physical demonstration, verbal instructions, and small group activities. To enhance students' learning experience and assist badminton instructors more effectively, this study proposes an alternative teaching approach that utilizes a Badminton Teaching-Assisted System (BTAS) to teach swing movements. The system uses a gesture control armband to collect electromyography and gyroscope signals from professional players, which are then used to build a machine learning model based on the back propagation neural network. The model can be used as a scoring tool to assess the correctness of the student's swing movements and muscle strength. A total of 87 students participated in an eleven-week experiment focusing on two fundamental badminton skills: The backhand push and backhand lift. The results demonstrated a significant improvement in the correctness of the muscle strength during swing movements for the experimental group, compared to the control group. The BTAS can help to enhance the effectiveness of badminton instruction, thereby improving students' swing techniques. Future research could expand upon this study to develop more precise artificial intelligence-based sports assistance systems, which would facilitate personalized teaching and learning in physical education.
Three-dimensional heterotypic colorectal cancer spheroid models for evaluation of drug response

Colorectal cancer (CRC) is a leading cause of death worldwide. Improved preclinical tumor models are needed to make treatment screening clinically relevant and address disease mortality. Advancements in 3D cell culture have enabled a greater recapitulation of the architecture and heterogeneity of the tumor microenvironment (TME). This has enhanced their pathophysiological relevance and enabled more accurate predictions of tumor progression and drug response in patients. An increasing number of 3D CRC spheroid models include cell populations such as cancer-associated fibroblasts (CAFs), endothelial cells (ECs), immune cells, and gut bacteria to better mimic the in vivo regulation of signaling pathways. Furthermore, cell heterogeneity within the 3D spheroid models enables the identification of new therapeutic targets to develop alternative treatments and test TME-target therapies. In this mini review, we present the advances in mimicking tumor heterogeneity in 3D CRC spheroid models by incorporating CAFs, ECs, immune cells, and gut bacteria. We introduce how, in these models, the diverse cells influence chemoresistance and tumor progression of the CRC spheroids. We also highlight important parameters evaluated during drug screening in the CRC heterocellular spheroids.
The development and application of the moment method in the gas kinetic theory

The moment method is not only a modeling tool that gives macroscopic fluid equations by reducing kinetic equations, but also a numerical method for solving kinetic equations. It has been the subject of rapid development, and in recent years has acquired widespread applications. In this paper, we review and summarize the research development of moment methods in kinetic theory from the aspects of modeling, numerical methods, and applications. First, we discuss the deficiencies of moment methods and summarize the remedy, where in particular the regularized moment method and globally hyperbolic moment method are introduced, owing to the wide interest regarding them. Subsequently, we investigate various numerical methods for solving moment equations, and highlight the numerical regularized method for moment equations of arbitrary orders. In addition, this paper reviews the applications of moment methods in the fields of rarefied gases, microflows, electron transport, plasma, and density functionals and presents an outlook regarding the future development of moment methods.
Joint Sensor Array Path Planning and Attitude Determination for Optimal Emitter Localization

Existing path planning schemes designed for wireless sensor networks generally account for abstract payload sensors, rendering them inapplicable to concrete sensor-array-based localization systems due to differences in measurement models. In this paper, we establish a general framework for path planning of a practical sensor array and factor in an oft-neglected degree of freedom regarding optimality, i.e., the array’s orientation/attitude. The optimization problem is formulated based on the A-optimality criterion under constraints arising from the maximum distance between consecutive waypoints, maximal heading change, and forbidden regions. To facilitate semidefinite relaxation (SDR), we recast the optimization function into a fractional nonhomogeneous quadratic structure and transform the constraints into a bilinear form. By applying SDR and replacing the bilinear terms with a matrix variable, the problem is relaxed into a single-ratio fractional program. By leveraging the Charnes-Cooper variable transformation, we transform the single-ratio fractional program into a mixed semidefinite/second-order cone program (SD/SOCP) that can be solved in polynomial time. Finally, we apply the results to angle-of-arrival (AOA) and direct localization. Simulation results demonstrate that the proposed path planning scheme attains near-optimal performance.