Miracle-dz/UniFAR-FTUs huggingface dataset:
Disease Detection of Solanaceous Crops Using Deep Learning for Robot Vision

Traditionally, the farmers manage the crops from the early growth stage until the mature harvest stage by manually identifying and monitoring plant diseases, nutrient deficiencies, controlled irrigation, and controlled fertilizers and pesticides. Even the farmers have difficulty detecting crop diseases using their naked eyes due to several similar crop diseases. Identifying the correct diseases is crucial since it can improve the quality and quantity of crop production. With the advent of Artificial Intelligence (AI) technology, all crop-managing tasks can be automated using a robot that mimics a farmer's ability. However, designing a robot with human capability, especially in detecting the crop's diseases in real-time, is another challenge to consider. Other research works are focusing on improving the mean average precision and the best result reported so far is 93% of mean Average Precision (mAP) by YOLOv5. This paper focuses on object detection of the Convolutional Neural Network (CNN) architecture-based to detect the disease of solanaceous crops for robot vision. This study's contribution involved reporting the developmental specifics and a suggested solution for issues that appear along with the conducted study. In addition, the output of this study is expected to become the algorithm of the robot's vision. This study uses images of four crops (tomato, potato, eggplant, and pepper), including 23 classes of healthy and diseased crops infected on the leaf and fruits. The dataset utilized combines the public dataset (PlantVillage) and self-collected samples. The total dataset of all 23 classes is 16580 images divided into three parts: training set, validation set, and testing set. The dataset used for training is 88% of the total dataset (15000 images), 8% of the dataset performed a validation process (1400 images), and the rest of the 4% dataset is for the test process (699 images). The performances of YOLOv5 were more robust in terms of 94.2% mAP, and the speed was slightly faster than Scaled-YOLOv4. This object detection-based approach has proven to be a promising solution in efficiently detecting crop disease in real-time.
Influence by hypothyroidism on the level of sex hormones in blood and their intracrine content in the tumor in rats with Guerin’s carcinoma

The aim of our research work was to study the level of sex steroids in blood, the tumor and the perifocal zone in rats of both sexes with Guerin’s carcinoma against the background of hypothyroidism. Materials and methods. The experiment was performed in 110 outbred rats of both sexes. Hypothyroidism was induced in animals for 30 days with Mercazolil medication, and then Guerin’s carcinoma was transplanted (the main group). The reference groups included animals with an independent growth of Guerin’s carcinoma and with independent hypothyroidism, as well as intact animals (the norm). On the 18th day of the tumor growth, the animals were sacrificed, and, using standard RIA kits, in the serum, the tumor homogenates and the perifocal zone, the levels of estradiol (E2), testosterone (T) and progesterone (P4) were determined. Results. In comparison with intact animals, hypothyroidism caused an increase in the blood content of E2 in animals of both sexes by 2.2-2.4 times and T by 1.4-16 times, and P4 by 1.7 times only in females, but recorded was a decrease therein in males by 2.4 times. The growth of Guerin’s carcinoma resulted in a 2.5-5.5-fold decrease in E2 in blood of the animals of both sexes, an increase in T by 2.1 times and P4 by 3 times in the females, but a decrease in T by 2.6 times without changing P4 in the males. In the main group, in the animals of both sexes, similarly to the processes in hypothyroidism, the level of E2 and P4 increased by 1.4-1.6 times, and in females also T by 4.4 times, compared with the intact animals. Conclusion. Hypothyroidism and the growth of Guerin’s carcinoma changed E2 in different directions in animals of both sexes the level of sex hormones in blood and shifted the steroid balance in the tumor and its perifocal zone. In the females of the main group, the saturation of the tumor with estrogens, androgens and progesterone decreased, while in the males, on the contrary, the concentration of steroids increased.
Non-invasive research of biological objects by the method of laser polarimetry

Recent studies have displayed that the biological tissue, especially skin, alters the polarization state of the incident light. Using this property will enable the study of abnormalities and diseases that change not only the light intensity but also its polarization state. This paper briefly considers spatial speckle-correlometry and polarimetry method for measuring changes of polarization state of the light scattered from a biological tissue. This technique provides the possibility to have the most comprehensive information on the optical and polarization properties of the skin sector containing scar structures and other abnormalities and diseases. Practical application of the developed approach is shown in the research.
Individualized surgical treatment in patients with advanced gastrointestinal stromal tumor — a case series

In this case series we present the cases of two patients at a metastatic stage of stomach gastrointestinal stromal tumor, who received treatment with imatinib. After a period of disease stability patients showed signs of resistance to the first-line therapy and despite the promising switch to sunitinib, developed life-threatening complications. Salvage surgeries were performed, aimed at preserving patients life and simultaneously reducing the tumor mass. Operation greatly improved patients condition and allowed for successful continuation of tyrosine kinase inhibitor treatment, showing that surgery should be considered a viable complement to the chemotherapeutical treatment.
A prediction based controller for trajectories tracking and stabilization of a non-minimum phase PVTOL aircraft

: In this paper a nonlinear prediction-based control approach is proposed for stabilization of Planar Vertical Take-Oﬀ and Landing (PVTOL) aircraft. This system has fewer control inputs than degrees of freedom (i.e. under-actuated) and has unstable zero dynamics (i.e. non-minimum phase). The proposed control approach is based on partial feedback linearization, which allows the emergence of a completely linearized sub-system and internal dynamics. Then prediction based optimal trajectories are proposed for the linearized variables, where the optimization objective is to enhance the behavior and the stability of the internal dynamics. Stability analysis of the closed-loop system is performed using a graphical tool based on Poincar´e’s section. The performance of the proposed scheme is illustrated through simulations.
Restorative neurostimulation for chronic mechanical low back pain – Three year results from the United Kingdom post market clinical follow-up registry

Introduction Mechanical chronic low back pain is often associated with impaired neuromuscular control of the lumbar multifidus muscles, the most important stabilizers of the lumbar spine. Restorative neurostimulation is a modality for the treatment for this specific subset of patients aimed to facilitate restoration of neuromuscular control by bilateral stimulation of the L2 medial branches. Evidence from both prospective and randomised clinical trials to date has demonstrated substantial improvements in clinical outcomes such as pain, disability and health-related quality of life. Methods This study is an open label prospective follow-up for the treatment of chronic mechanical low back pain of nociceptive origin with restorative neurostimulation. Patients completed assessments for pain, disability and health-related quality of life. Outcomes were collected at 45, 90 and 180 days, and 1, 2 and 3 years after the activation visit. Results Forty-two patients were implanted with the device and 33 (79%) were available at the 3-year appointment. Patients in this cohort presented with severe chronic low back pain (NRS = 7.0 ± 0.2) and severe disability (ODI 46.6 ± 12.0). The health-related quality of life was also severely impacted at baseline (EQ-5D 0.426 ± 0.061). Changes in pain, disability and quality of life at three-year follow-up demonstrated a statistically significant improvement between baseline and 1, 2 and 3 years. After 3 years of therapy, average NRS scores had reduced to 2.7± 0.3 and mean ODI score to 26.0 ± 3.1 while EQ-5D-5L index improved to 0.707 ± 0.036. Conclusions The ongoing follow-up of this post market cohort continues to demonstrate that restorative neurostimulation provides a statistically significant, clinically meaningful and durable response across pain, disability and quality-of life scores for patients suffering chronic mechanical low back pain that has been refractory to conventional management. Trial Registration ClinicalTrials.gov Identifier: NCT01985230.
Microscopic theory of optical absorption in graphene enhanced by lattices of plasmonic nanoparticles

We present a microscopic description of plasmon-enhanced optical absorption in graphene, which is based on perturbation theory. We consider the interaction of graphene with a lattice of plasmonic nanoparticles, as was previously realized experimentally. By using tight-binding wave functions for the electronic states of graphene and the dipole approximation for the plasmon, we obtain analytic expressions for the coupling matrix element and enhanced optical absorption. The plasmonic nanostructure induces nonvertical optical transitions in the band structure of graphene with selection rules for the momentum transfer that depend on the periodicity of the plasmonic lattice. The plasmon-mediated optical absorption leads to an anisotropic carrier population around the K point in phase space, which depends on the polarization pattern of the plasmonic near field in the graphene plane. Using Fourier optics, we draw a connection to a macroscopic approach, which is independent from graphene-specific parameters. Each Fourier component of the plasmonic near field corresponds to the momentum transfer of an optical transition. Both approaches lead to the same expression for the integrated optical absorption enhancement, which is relevant for the photocurrent enhancement in graphene-based optoelectronic devices.
Caching and 3D Deployment Strategy for Scalable Videos in Cache-Enabled Multi-UAV Networks

Unleashing the potential of unmanned aerial vehicles (UAVs) to play the role of caching devices for furnishing layered video services to ground users (GUs) holds tremendous promise. However, it is crucial to strike a balance between the quality and the diversity of video content when deciding the placement strategies of video caching. In this study, we examine the feasibility of implementing a layered caching scheme utilizing scalable video coding (SVC) in three-dimensional (3D) multi-UAV networks with cache capabilities. The objective is to investigate the minimization of the cumulative video access delay experienced by all GUs through the joint design of layered scalable video caching, user-UAV association, and 3D UAV deployment. This approach enables the network to offer video services across a range of quality levels. We have formulated an intricate mixed-integer non-convex optimization problem which poses a significant challenge to solve directly. Then we decompose the formulated problem into three interrelated sub-problems and put forth specific algorithms designed to address each component, i.e., layered caching strategy and UAV's two-dimensional (2D) deployment optimization with penalty based difference-of-convex (penalty-DC) framework, user-UAV association optimization with bipartite graph based linear programming (LP) relaxation, as well as UAV altitude optimization with successive convex approximation (SCA) method. Then we introduce a highly efficient iterative algorithm that employs an alternate optimization approach for three sub-problems until convergence. Our simulation results demonstrate that our proposed algorithm surpasses other benchmark schemes significantly in terms of mitigating video access delay.
Optimizing the Cyclic K-conflict-free Shortest Path Problem in a Network-on-chip

We study a combinatorial optimization problem for conflict-free routing in a Network-on-Chip. Based on time division multiplexing and cyclic emission, the problem consists in finding a set of K shortest paths, such that packets will never conflict through the network but can use shared communication links in an efficient way. The model allows to avoid collisions and deadlocks in irregular network topologies, while minimizing latency. A time-expanded graph approach is retained for the solution process. First, we present a mixed integer linear programming model for the problem. Second, a set of shortest paths operators are combined within three iterated local search schemes able to quickly generate admissible solutions for the problem. To evaluate the method, experiments are conducted on a set of five real-life problem instances, and on many artificial unstructured random instances derived from them. We detail the problem of traffic instance generation, that also illustrates the designer’s task of flow decomposition between communicating components. Intensive simulations illustrate the accuracy of the solution method.
Történeti tabló a pozitív pszichológiai jóllét és mentális egészség elméletekről és előzményeikről

Az elmúlt két évtizedben terjedelmes irodalom gyűlt össze, amely fel szeretné tárni azt a számtalan, egymással összefüggő tényezőt, amely a boldogságot egyéni és kollektív szinten is befolyásolja. Az elméletek nehezen különböztethetők meg egymástól, ezért a jelen tanulmány a pozitív pszichológia főbb irányvonalainak és előzményeinek felvázolásával szeretne egyértelműséget nyújtani ebben. Egy történeti tabló segítségével integrált keretet és „útmutatót” adunk a pozitív pszichológiában fellelhető jóllételméletek és -modellek értelmezéséhez. Az egyes koncepciókhoz mérőeszközöket is kapcsolunk, melyek példaképp illusztrálják a szóban forgó elméletek megjelenését. Végül azonosítjuk azokat a kérdéseket, amelyek tisztázást és további alapos vizsgálatot igényelnek a területen.
Measuring Usability on User-Centered Mobile Web Application: Case Study on Financial Mathematics Calculator

Financial literacy is a person's skills regarding financial knowledge and behavior. In 2019, the National Survey of Financial Literacy and Inclusion (SNLIK) stated that Indonesia had a low level of financial literacy with a percentage of 38.03%. In 2016, the Indonesian government incorporated financial literacy into the K13 curriculum for the high school level to improve financial literacy at the student level. In line with that, students need facilities to help them learn financial literacy. This study aims to build an interaction design of financial mathematics calculators using the User-Centered Design method. The limitation of this study is the design uses a mobile web platform that targets high school students. The results of usability testing on effectiveness get an average task-completion rate score of 92.3%, an average efficiency of 92.0% overall relative efficiency, user satisfaction using the System Usability Scale (SUS) gets a score of 93.2 for the usability factor and a score of 74 for the learnability factor. The findings of this study indicate that the application is easy to use and provides a positive experience in learning financial literacy. The current study's results will support this application's use in future research as a new tool for providing financial literacy.
Molecular and Immunopathological Investigations of Marek’s Disease in HVT Vaccinated Chicken Flocks

Background: The present investigation was carried out on poultry carcasses brought to the Department of Veterinary Pathology, LUVAS, Hisar from Herpesvirus of turkeys (HVT) vaccinated chicken flocks and suspected for viral neoplastic conditions on the basis of necropsy. Conventional and molecular techniques for the confirmation of the Marek’s disease (MD) were studied. For differential diagnosis from other oncogenic viral infections immunohistochemistry as an important tool was investigated. Methods: The conventional diagnosis of MD) was done on basis of clinical signs, gross lesions and histopathology of proliferate lesions; as lymphomatous lesions consist of pleomorphic lymphocytes. For confirmatory diagnosis molecular techniques were employed to detect MD virus specific Meq gene by Taqman probe real time PCR and nested PCR. For differential diagnosis of mixed oncogenic viral infections, immunohistochemistry (IHC) using B and T cell differentiation markers (CD79 alpha and CD3) was employed. Result: Specific Meq gene by Taqman probe real time PCR was positive in 92.5% suspected cases; while nested PCR technique gave positivity in 55% cases. The immunohistochemical reactivity for CD3 gave positive reactivity in the cytoplasm and cell membrane and negative reaction for CD79 alpha in MD positive cases, while in cases with mixed infections of MDV and other viral neoplastic conditions, cells showed positive reactivity to both CD3 and CD79 alpha in neoplastic proliferates.
Investigating interactions in multivariable model-building with continuous covariates

In multivariable model-building interactions between two continuous predictors are often ignored. If considered, the most popular approach is to assume linearity for both variables and test the multiplicative interaction term for significance. However, the model may fit poorly if one or both of the main effects is non-linear. Fractional polynomials (Royston & Altman 1994, Sauerbrei & Royston 1999) have been proposed for investigating main effects of predictors for possible non-linearity. With the multivariable fractional polynomial procedure (MFP), selection of variables and simultaneous determination of functional relationships are possible. If the main effects of two continuous variables derived by MFP include non-linear functions, Royston & Sauerbrei (2008) proposed considering products of these FP functions, which may also be linear, as a candidate for the interaction between the two continuous covariates. This procedure called MFPIgen is a generalization of the MFPI procedure which investigates interactions between a continuous and a binary variable (Royston & Sauerbrei 2004). Key issues of the method will be illustrated by assessing predictors for 10-year allcause mortality in the Whitehall I data set, a large cohort study (N=17260, 1670 events) in British civil servants. Six continuous and one categorical predictor will be considered in a logistic regression model. Using MFPIgen we will illustrate that mismodelling of non-linear main effects as linear may introduce spurious interactions and that a systematic search for interactions will reveal further structure in the data. Our new procedure allows the analyst to consider continuous by continuous interactions in a systematic way. It can also handle non-linear effects, an important issue too often ignored in practical data analysis. To reduce the chance of spurious interactions being detected, a stringent significance level such as 1% should be used.
Residual DNN-CRF Model for Audio Chord Recognition

In this paper, we propose Residual DNN-CRF Model for Audio Chord Recognition. The network architecture of chord recognition using deep learning so far consists of a shallow network of about three layers. Even if Convolutional Neural Network is used, if the hidden layer in the network architecture is shallow, the original power of deep learning will not be demonstrated. Of course it is the same for DNN. Therefore, we propose a network architecture with 15 hidden layers. The extracted features are processed by a Conditional Random Field that decodes the final chord sequence. We provide superior results by building deeper network architecture than before. In addition, we compare the results of the proposed model with the results of the Robbie Williams dataset used in other chord recognition network architectures.
Do self-regulated learning and flipped learning assisted by learning video affect learning outcomes? (Indonesian)

This study aims to determine how the influence of Self Regulated learning and Flipped Learning with the help of video learning simultaneously or partially can affect learning outcomes and to find the indicators of Self Regulated Learning that most contribute to learning that is carried out with the help of learning videos within the scope of this model. This research is a type of quantitative research with a total sample of 84 students from the 2021 class of the 2021/2022 even semester. The research used questionnaires and written tests as research tools. The data analysis technique uses multiple regression with the term Dummy Regression using gretl. It is called dummy regression because one of the variables is Flipped Learning as a dummy variable. Based on the results of the study, it was found that Flipped Learning and Self-Regulated Learning simultaneously had a significant and positive effect on learning outcomes, partially Flipped Learning had an effect on learning outcomes while Partial Self-Regulated Learning had no significant effect on learning outcomes. The Revisit indicator was found to be one of the most contributing indicators in flipped learning-assisted learning on learning outcomes. In this study, it resulted in implications through a finding that was different from previous research, partially SRL did not significantly affect student learning outcomes. This is possible because students' SRL is not enough to understand students in a learning material. It takes modifications to the environment outside of the student to optimize the student's SRL in learning activities, one of which is the use of learning videos in flipped learning
Drag and lift measurements of solid sports balls in still air

The following article considers lift and drag measurements of solid sports balls propelled through still air in a laboratory setting. The balls traveled at speeds ranging from 26 to 134 m/s with spin rates up to 3900 r/min. Light gates measured the speed and location of the balls at two locations from which lift and drag values were determined. Ball roughness varied from polished to rough surface protrusions, that is, seams as high as 1.5 mm. Lift and drag were observed to depend on speed, spin rate, surface roughness, and seam orientation. A drag crisis was observed on smooth balls as well as non-rotating seamed balls with seam heights less than 0.9 mm. The drag coefficient of approximately 0.42 was nearly constant with speed for spinning seamed balls with seam height greater than 0.9 mm. The still air drag coefficient of smooth balls was comparable to wind tunnel drag at low speeds (Re < 2 × 105) and higher than wind tunnel results at high speeds (Re > 2 × 105). The lift and drag coefficients of spinning balls increased with increasing spin rate. The lift coefficient of baseballs was not sensitive to ball orientation or seam height.
Biodiversidad de Coníferas del Estado de Nuevo León, México

Las coníferas son plantas vasculares que producen semillas en “conos” o estróbilos ovulíferos. Su importancia ecológica radica en su ubicuidad en los bosques templados y de galería en México. Se aprovechan económicamente en la producción de madera, papel, resinas, semillas comestibles, así como árboles de ornato y árboles de navidad. México es uno de los centros de diversidad de coníferas, con cerca de 94 especies, 43 de ellas endémicas al país. Tras una revisión bibliográfica y taxonómica, se encontró que en el estado de Nuevo León habitan 31 especies de coníferas pertenecientes a los géneros Abies, Cupressus, Juniperus, Picea, Pinus, Pseudotsuga, Taxodium, y Taxus. Los géneros mejor representados son Pinus (15 especies y 5 taxones infraespecíficos) y Juniperus (7 especies). Picea martinezii es la única especie con rango geográfico restringido a Nuevo León.