Miracle-dz/UniFAR-FTUs huggingface dataset:
Ship Target Detection Method in SAR Imagery Based on Generalized Pareto Manifold

Ship target detection based on Synthetic aperture radar (SAR) imagery is a challenging task. With the continuous improvement of SAR resolution, the false alarm rate set by manual experience in traditional CFAR detection tends to lead to missed detection and weaken the detection performance. To solve this problem, this paper proposes a ship target detection method based on the generalized Pareto manifold in SAR imagery. The generalized Pareto distribution family is used to construct the SAR images’ statistical manifold, and the tangent vector length is applied to represent the local neighborhood of each pixel of SAR images, which indicates the difference between targets and the background clutter significantly, implementing the precise positioning of ship target and the effective suppression of background clutter in SAR images. The test results of Gaofen-3 satellite data show that compared with the traditional CFAR algorithm, this method achieves significantly better performance.
Optimized Ensembled Machine Learning Model for IRIS Plant Classification

Pattern recognition is one of the major concerns in the field of machine learning. Appropriate Recognition of patterns leads to addressing the performance concerns. Machine Learning [ML], a subset of Artificial Intelligence [AI] plays an important role in the process of classification, clustering and predictive modeling. This paper focuses on developing a novel classification technique to classify the iris of the plant in order to categorize the flower pattern. An optimized ensemble model is proposed to recognize and categorize the pattern. Initially, Decision Tree, OneR, Adaboost, Random Forest, and Bayesnet models are applied and to improve the performance an ensemble model is proposed.
A Survey on IoT in Agriculture for the Implementation of Greenhouse Farming

The greenhouse is one of the sustainable forms of smart agricultural farming. It is considered as an alternate method to overcome the food crisis which is generated due to high population growth, climate change, and environmental pollution. Although this method supports off-the-season crops within the enclosed area even in severe climatic zones. It has required to efficiently control and manage the crop parameters at greenhouse in a more precise and secure way. The advancement of the Internet of Things (IoT) has introduced smart solutions to automate the greenhouse farming parameters such as plant monitoring, internal atmosphere control, and irrigation control. The survey presents a hierarchy on the major components of IoT-based greenhouse farming. A rigorous discussion on greenhouse farming techniques, IoT-based greenhouse categories, network technologies (cloud/edge computing, IoT protocols, data analytics, sensors) has been presented. Furthermore, a detailed discussion on mobile-based greenhouse applications and IoT applications has been presented to manage the greenhouse farm. Moreover, the success stories and statistical analysis of some agricultural countries have been presented to standardize the IoT-based greenhouse farming. Lastly, the open issues and research challenges related to IoT-enabled greenhouse farming has been presented with state-of-the-art future research directions.
On the Ky Fan $k$-norm of the $LI$-matrix of graphs

Let $A(G)$ and $D(G)$ be the adjacency matrix and the degree diagonal matrix of a graph $G$, respectively. Then $L(G)=D(G)-A(G)$ is called Laplacian matrix of the graph $G$. Let $G$ be a graph with $n$ vertices and $m$ edges. Then the $LI$-matrix of $G$ is defined as $LI(G)=L(G)-\frac{2m}{n}I_n$, where $I_n$ is the identity matrix. In this paper, we are interested in extremal properties of the Ky Fan $k$-norm of the $LI$-matrix of graphs, which is closely related to the well known problems and results in spectral graph theory, such as the Laplacian spectral radius, the Laplacian spread, the sum of the $k$ largest Laplacian eigenvalues, the Laplacian energy, and other parameters. Some bounds on the Ky Fan $k$-norm of the $LI$-matrix of graphs are given, and the extremal graphs are partly characterized. In addition, upper and lower bounds on the Ky Fan $k$-norm of $LI$-matrix of trees, unicyclic graphs, and bicyclic graphs are determined, and the corresponding extremal graphs are characterized.
CFD modeling of Air-Water Two-phase Annular Flow before a 90° elbow

In this work, a Computational Fluid Dynamics model is presented for the analysis of annular air-water flow before a 90° bend with a radius to diameter ratio (r/D) of 1.5, implementing the Volume of Fluid (VOF) model in STAR-CCM+ v9.2. An 8m-long vertical tube with an internal diameter of 0.076 m was studied for ten different air and water superficial velocities. The mean void fraction was compared between the experimental measurements, the CFD model, and a model in OLGA. The CFD and OLGA model presented an average relative error of 8.79 % and 17.05 %, respectively.
Electromechanical servomechanisms affected by motor static eccentricity: Proposal of fault evaluation algorithm based on spectral analysis techniques

The development of a prognostic algorithm capable of identifying the precursors of incipient failures of primary flight command Electromechanical Actuators (EMA) is beneficial for the anticipation of the incoming failure: a correct interpretation of the failure degradation pattern, in fact, can trig an early alert of the maintenance crew, who can properly schedule the servomechanism replacement. Prognostic, though, is strictly technology-oriented as it is based on accurate analysis of the cause and effect relationships. As a consequence, it is possible that prognostics algorithms that demonstrate great efficacy for certain applications fail in other circumstances, just because the actuator is based on a different technology. In this paper the authors propose an innovative prognostic "model-based" technique able to identify symptoms of an EMA degradation before the actual exhibition of the anomalous behavior. The identification/evaluation of the considered incipient failures is performed analyzing proper critical operational system parameters, able to put in evidence the corresponding degradation path, by means of a numerical algorithm based on spectral analysis techniques. Subsequently, these operational parameters are correlated with the actual health condition of the considered system by means of failure maps created by a reference monitoring model-based algorithm. According to preliminary testing, the proposed method has proved its worth for different types of EMA progressive failure: in particular, in the present work, it has been applied to the case of an actuator having brushless DC motor affected by a progressive increase of the static eccentricity of the rotor. © 2015 Taylor & Francis Group, London
Automated Spontaneity Assessment after Smile Reanimation: A Machine Learning Approach

Background: Recreation of a spontaneous, emotional smile remains a paramount goal of smile reanimation surgery. However, optimal techniques to reliably restore spontaneity remain unknown. Dual automated machine-learning tools were used to develop an objective tool to analyze spontaneous smiling. The feasibility of this tool was tested in a sample of functional free muscle transfers. Methods: Validated humorous videos were used to elicit spontaneous smiles. Automated facial landmark recognition (Emotrics) and emotion detection software (Affdex) were used to analyze video clips of spontaneous smiling in nine normal subjects and 39 facial reanimation cases. Emotionality quotient was used to quantify the ability of spontaneous smiles to express joy. Results: The software could analyze spontaneous smiling in all subjects. Spontaneous smiles of normal subjects exhibited median 100 percent joy and 0 percent negative emotion (emotional quotient score, +100/0). Spontaneous smiles of facial palsy patients after smile reanimation, using cross-facial nerve graft, masseteric nerve, and dual innervation, yielded median emotional quotient scores of +82/0, 0/−48, and +10/−24 respectively (joy, p = 0.006; negative emotion, p = 0.034). Conclusions: Computer vision software can objectively quantify spontaneous smiling outcomes. Of the retrospective sample of cases reviewed in this study, cross-facial nerve graft–innervated gracilis functional free muscle transfer achieved a greater degree of emotionality during spontaneous smiling than masseteric or dually innervated transfer. Quantification of spontaneous smiling from standard video clips could facilitate future, blinded, multicenter trials with sufficient long-term follow-up to definitively establish the rates of spontaneity from a range of reanimation procedures. CLINICAL QUESTION/LEVEL OF EVIDENCE: Diagnostic, IV.
Spheroid Formation Enhances the Regenerative Capacity of Nucleus Pulposus Cells via Regulating N-CDH and ITGβ1 Interaction

Background: Nucleus pulposus (NP) degeneration is the core pathological change of intervertebral disc (IVD) degenerative diseases, but currently, no effective therapy is available. With the rapid development of biomaterials and tissue engineering in recent years, biomaterial-assisted cell transplantation becomes a promising therapy for IVD degeneration. However, the application is severely limited by the weak biological characteristics of NP cells (NPCs), such as a moderate proliferation ability, weak self-renewal capacity, and minimal extracellular matrix (ECM) synthesis capacity, caused by the current inappropriate cell seeding or grafting methods. Methods: Here, we developed a three-dimensional (3D) spheroidizing culture method to construct NPC spheroids and investigated repair and regeneration potential of these spheroids in vitro and in vivo. The in vitro biological characteristics (including cell viability and proliferation), and in vivo functions (including anti-degeneration potential and ability to induce tissue repair) of NPC spheroids and monolayer-cultured NPCs were compared. Furthermore, an RNA-seq-based transcriptome analysis and a series of function experiments were performed to elucidate the potential mechanisms of their differences that were involved in the tissue regeneration process. Results: NPC spheroids exhibited obviously superior self-renewal and ECM synthesis capacities compared to monolayers of NPCs in vitro. In vivo, NPC spheroids generated more functional ECM components, primarily aggrecan (ACAN) and collagen type II (Col2), and markedly promoted NP regeneration in the disc degeneration model induced by partial NP excision. Additionally, the biological characteristics and functions of NPC spheroids were to some extent regulated by the interaction of N-cadherin (N-CDH) and Integrinβ1 (ITGβ1), two key mechanosensing ECM-receptors expressed on NPCs. Conclusions: The NPC spheroidizing culture method is beneficial for cell renewal and the generation of functional ECM in NP tissue. The molecular mechanism involved in this regeneration process is closely associated with the regulation of the N-CDH and ITGβ1 interaction-mediated ECM homeostesis. Moreover, the strategy of hydrogel-assisted NPC spheroids transplantation may potentially be used in the future treatment of IVD degeneration.
Synthetic Data Generation and Joint Learning for Robust Code-Mixed Translation

The widespread online communication in a modern multilingual world has provided opportunities to blend more than one language (aka code-mixed language) in a single utterance. This has resulted a formidable challenge for the computational models due to the scarcity of annotated data and presence of noise. A potential solution to mitigate the data scarcity problem in low-resource setup is to leverage existing data in resource-rich language through translation. In this paper, we tackle the problem of code-mixed (Hinglish and Bengalish) to English machine translation. First, we synthetically develop HINMIX, a parallel corpus of Hinglish to English, with ~4.2M sentence pairs. Subsequently, we propose RCMT, a robust perturbation based joint-training model that learns to handle noise in the real-world code-mixed text by parameter sharing across clean and noisy words. Further, we show the adaptability of RCMT in a zero-shot setup for Bengalish to English translation. Our evaluation and comprehensive analyses qualitatively and quantitatively demonstrate the superiority of RCMT over state-of-the-art code-mixed and robust translation methods.
A design approach to a standard manipulator

New structures for gripping objects in robotic manipulation processes are oriented to the new arrangement of mechanical structures using new materials and processing technologies and innovative procedures for the implementation of contact gripping element links to an object with a high degree of adaptively of applications together with the ability to alter the structure of grip and limiting the intensity of the contact stiffness variation of snap elements custody and pliability. The application of elastomeric materials and surface finishes is important. This paper presents both a new gripper design for robot arms but also the search of the selected materials to make an experimental evaluation of technical parameters that are used to assess their application potential and suitability for the targeted applications. Also the results and conclusions for gripper testing in manipulation operations with two different robot arms are presented.
Statistics in Biopharmaceutical Research 2023 Associate Editors

Bio ACADEMIC APPOINTMENTS • Professor, Biomedical Data Science • Professor (By courtesy), Statistics • Member, Cardiovascular Institute BOARDS, ADVISORY COMMITTEES, PROFESSIONAL ORGANIZATIONS • Elected Fellow, American Statistical Association (2022 present) PROFESSIONAL EDUCATION • Bachelor of Science, Nankai University , Mathematics (1995) • Master of Science, Nankai University , Mathematics (1998) • Doctor of Science, Harvard University , Biostatistics (2002) LINKS • personal site: https://web.stanford. edu/~lutian/home.HTML • course site: https://web.stanford. edu/~lutian/stat331.HTML Research & Scholarship CURRENT RESEARCH AND SCHOLARLY INTERESTS My research interest includes (1) Survival Analysis and Semiparametric Modeling; (2) Resampling Method ; (3) Meta Analysis ; (4) High Dimensional Data Analysis; (5) Precision Medicine for Disease Diagnosis, Prognosis and Treatment.
The benefit of Silybum marianum in ethanol-induced reprotoxicity of male Wistar rat

This study investigates the toxic effects of ethanol (Eth) on the reproductive system of male rats and the possible protective role of Silybum marianum seeds-infused solution (SMI) over six consecutive weeks of administration. Animals were divided into the following groups: control, SMI positive control (200 mg/kg/day), Eth1 (1 g/kg/day), Eth2 (2 g/kg/day), Eth1+SMI, and Eth2+SMI. Plasma testosterone concentration, epididymal spermatozoa biology, and testicular and epididymal MDA, GSH and GPx levels were evaluated. The results indicated a significant decrease in testis and epididymis weight, testosterone level, sperm concentration, sperm vitality and sperm motility (total motility, progressive motility, curvilinear velocity, straightline velocity, velocity average path, beat cross frequency, and lateral head displacement) in both Eth1 and Eth2 compared to the control groups and the combined-treatment groups (Eth1+SMI and Eth2+SMI). Furthermore, results showed a significant elevation in MDA concentration with a significant decrease of testicular and epididymal GSH concentration and GPx activity in theEth1 and Eth2 groups compared to the combined-treatment groups. The administration of SMI succeeded in improving the parameters cited above in the combined-treatment groups compared to the Eth1 and Eth2 groups, and bring them to the levels seen in the control groups. To conclude, SMI has clearly protected reproductive indices against ethanol-induced reprotoxicity in male rats
Internet of Things Approaches for Monitoring and Control of Smart Greenhouses in Industry 4.0

In recent decades, climate change and a shortage of resources have brought about the need for technology in agriculture. Farmers have been forced to use information and innovation in communication in order to enhance production efficiency and crop resilience. Systems engineering and information infrastructure based on the Internet of Things (IoT) are the main novel approaches that have generated growing interest. In agriculture, IoT solutions according to the challenges for Industry 4.0 can be applied to greenhouses. Greenhouses are protected environments in which best plant growth can be achieved. IoT for smart greenhouses relates to sensors, devices, and information and communication infrastructure for real-time monitoring and data collection and processing, in order to efficiently control indoor parameters such as exposure to light, ventilation, humidity, temperature, and carbon dioxide level. This paper presents the current state of the art in the IoT-based applications to smart greenhouses, underlining benefits and opportunities of this technology in the agriculture environment.
QUALIDADE E INOVAÇÃO EM SERVIÇOS DE TRANSPORTE COLETIVO PÚBLICO EM GOIÂNIA - GO - BRASIL QUALITY AND INNOVATION IN PUBLIC TRANSPORTATION SERVICE IN GOIANIA - GO - BRAZIL

The objective of this paper is to assess the dynamics of an intelligent transportation system (ITS) in the public sphere in Goiania (GO), Midwest region of Brazil, from the point of view of players related to the service - government, transportation companies and the citizen (user). Based on the literature of services quality and innovation, interviews with specialists and a survey were conducted. The results pointed to divergence in opinions. For the user, the new system did not overcome most of the deficiencies of the public transportation, although government and
Design and protection of microgrid clusters: A comprehensive review

A microgrid is a concept that has been developed with the increasing penetration of distributed generators. With the increasing penetration of distributed energy resources in the microgrids, along with advanced control and communication technologies, the traditional microgrid concept is being transited towards the concept of microgrid clustering. It decomposes the distribution system into several interconnected microgrids, effectively reducing problems such as voltage rise, harmonics, poor power factor, reverse power flow and failure of the conventional protection schemes. Microgrid clusters effectively coordinate power sharing among microgrids and the main grid, improving the stability, reliability and efficiency of the distribution network at the consumption premises. Despite the evident benefits of microgrid clusters to the consumers and the electrical utility, there are challenges to overcome before adopting the microgrid cluster concept. This paper is aimed at critically reviewing the challenges in design aspects of microgrid clustering. Categorization of multi-microgrids into different architectures based on the layout of the interconnections, evaluation of reported control techniques in microgrid clustering and multi-microgrid protection aspects are presented, highlighting the possible areas of future research that would improve the operational aspects of microgrid clusters.
THE RELATION BETWEEN THE NUMBER OF REPETITIONS AND THE RELATIVE LOAD IN STRENGTH TRAINING

It was the aim of this study to determine the relationship between the number of repetitions that can be lifted at a range of percentages of the 1RM load in leg curl and bench press. Comparisons were made between males and females, and between long distance runners and sprinters. Findings suggest that this relationship is different between the two types of exercise. No differences were found between males and females. When working with highly trained athletes in bench press it is recommended that different regression equations are employed when studying sprint trained or endurance trained athletes.
Secondary Mechanisms of Neurotrauma: A Closer Look at the Evidence

Traumatic central nervous system injury is a leading cause of neurological injury worldwide. While initial neuroresuscitative efforts are focused on ameliorating the effects of primary injury through patient stabilization, secondary injury in neurotrauma is a potential cause of cell death, oxidative stress, and neuroinflammation. These secondary injuries lack defined therapy. The major causes of secondary injury in neurotrauma include endoplasmic reticular stress, mitochondrial dysfunction, and the buildup of reactive oxygen or nitrogenous species. Stress to the endoplasmic reticulum in neurotrauma results in the overactivation of the unfolded protein response with subsequent cell apoptosis. Mitochondrial dysfunction can lead to the release of caspases and the buildup of reactive oxygen species; several characteristics make the central nervous system particularly susceptible to oxidative damage. Together, endoplasmic reticulum, mitochondrial, and oxidative stress can have detrimental consequences, beginning moments and lasting days to months after the primary injury. Understanding these causative pathways has led to the proposal of various potential treatment options.
Common Mistakes in English Speaking Affected by Vietnamese of Master of Business Administration at Tay Do University, in Vietnam

Speaking skill plays an important role in studying a foreign language, especially English. However, learners make a lot of errors in English speaking. The study was conducted to examine the the common mistakes learners had in English speaking. Two instruments were employed to collect data. First, eighty-three participants in four classes - Master of Business Administration (MBA) course 8 and 9 - responded a questionnaire with 4 questions and 45 closed statements. Second, four observation periods were conducted to supply more information to make clear and prove the common mistakes that learners had during the process of speaking. This was a quantitative and qualitative research. It gave a clear and specific view about errors in English speaking faced by MBA learners at Tay Do University as pronunciation (intonation, ending sounds, consonant cluster, and word stress) and grammar (articles, tenses, passive voice, and order of words).
A frequency‐selective rasorber with wideband absorption and in‐band transmission using resistive ink

A polarization‐insensitive frequency‐selective rasorber (FSR) with wideband absorption and in‐band transmission characteristics has been presented and investigated in this letter. The unit cell of the proposed FSR comprises one lossy and one lossless resonator, both printed on FR4 substrates and segregated by an air spacer. Resistive ink patterns are deposited in the top lossy layer to realize a wideband absorption, displaying significant improvement over the existing FSR structures. The absorption bandwidths are obtained from 1.31 to 3.22 GHz and 4.88 to 6.69 GHz having fractional bandwidths of 84.32% and 31.28%, respectively. An in‐band transmission response is occurred, due to the bottom lossless layer, at 4.05 GHz between the two absorption bands with a small insertion loss. The equivalent circuit model is used to develop the proposed FSR and the design variables are formulated accordingly to generate the desired passband and stopband characteristics. Variation in the incident and reflected/transmitted wave properties have also been studied and the topology is found to be polarization‐insensitive as well as angularly stable. Finally, the structure has been fabricated and measured to validate the FSR design principle and its performance.