Miracle-dz/UniFAR-FTUs huggingface dataset:
Comprehensive Review on Development of Early Diagnostics on Oral Cancer with a Special Focus on Biomarkers

One of the most frequent head and neck cancers is oral cancer, with less than half of those diagnosed surviving five years. Despite breakthroughs in the treatment of many other cancers, the prognosis for people with OSCC remains dismal. The conventional methods of detection include a thorough clinical examination, biochemical investigations, and invasive biopsies. Early identification and treatment are important for a better chance of extending a patient’s life. Early diagnosis may be possible by identifying biomarkers in biological fluids. Currently, the primary method for diagnosing oral lesions is a visual oral examination; however, such a technique has certain drawbacks, as individuals are recognized after their cancer has advanced to a severe degree. The first section of this review discusses several diagnostic techniques for cancer detection, while the second section discusses the present state of knowledge about known existing predictive markers for the timely identification of malignant lesions, as well as disease activity tracking. The aim of the paper is to conduct a critical review of existing oral cancer diagnostic processes and to consider the possible application of innovative technology for early detection. This might broaden our diagnostic choices and enhance our capacity to identify and treat oral malignant tumors more effectively.
Torque Ripple Suppression Method of Switched Reluctance Motor Based on an Improved Torque Distribution Function

Currently, torque ripple is a crucial factor hindering the application of the switched reluctance motor (SRM). Hence, it is of crucial importance to suppress this undesirable torque ripple. This paper proposes a new torque ripple suppression method of SRM based on the improved torque distribution function. Firstly, the electromagnetic characteristic model of a 8/6-pole four-phase SRM is established, and the cerebellar model articulation controller (CMAC) is used to complete the learning of each model. Then, the improved torque distribution function is planned based on the torque model to give the reference torque of each phase, and the inverse torque model is used to realize the mapping of the reference torque to the reference flux linkage. Finally, the duty of each phase voltage PWM wave modulation is output based on the PID control theory. The proposed accurate model-based planning scheme is implemented on the simulation platform, and the results shows that the maximum torque fluctuation of the output results is reduced to within 3%, and the average error is reduced to within 1%, which is much lower than the error of 15% under the traditional direct torque control method.
Histomorphological and histochemical study of the fallopian tube during pregnancy and post-partum of the cape hare rabbit (Lepus Capensis)

This research was investigate the Anatomical and Histochemical structure of uterine tube during period of pregnancy and postpartum in cap hare rabbits. Eighteen female rabbits were used. The target samples were processing with paraffin embedding technique the tissue sections stained with H&E stain, and Masson's trichrom stain. Results; The length and weight of the uterine tube were (91.31 ± 0.72mm), (0.53 ±0.01g) at pregnancy. While. its (84.76 ±0.22mm), (0.41 ±0.01g) at post-partum. The infundibulum has a funnel-shaped end. Simple mucosal folds are bordered with pseudo stratified columnar epithelium. The lamina propriea-sub-mucosa is made up of connective tissue that is both vascular and cellular. The ampulla was highly vascularized and had a twisted appearance. The mucosal folds of the ampulla were lined by pseudo stratified columnar epithelium, which consisted of three cell types: mucous secretory cells, non-secretory cells and basal cells. The lamina propria was a thin layer of fibrous connective tissue that exposed a significant amount of fibroblast. The isthmus was short and straight at post-partum, and it was held in place by the mesosalpinx. Mucosal folds in the tunica mucosa are mild and short.
A Parallel Bidirectional Long Short-Term Memory Model for Energy Disaggregation

Non-intrusive load monitoring (NILM) is an elegant solution for monitoring energy consumption. Essentially, it only requires a set of voltage and current sensors to be installed at the electrical entry point for load disaggregation. However, the main challenge of NILM is to accurately analyze the aggregate load data and determine the electrical consumption of each appliance. Recently, there have been some deep learning (DL) techniques proposed for NILM. These include deep convolutional neural networks (DCNNs), gated linear unit and residual network (GLU-Res), bidirectional long short-term memory (BLSTM), and autoencoder (AE). Generally, they can outperform some of the existing NILM models such as factorial hidden Markov model. Nevertheless, some of these DL methods cannot handle well on multi-state appliances, appliances with sparse patterns, and appliances with rapid changing patterns. This article proposes a new NILM model, which involves parallel convolution neural networks and BLSTM layers. Moreover, a feature extractor is proposed to unmask useful statistical features from aggregate signals to improve the learning capability of the network. The benchmark dataset REDD was used for testing the proposed method and the state-of-the-arts such as DCNN, GLU-Res, BLSTM, and AE. The results indicate that the proposed method can successfully outperform those methods.
Teachers’ Pedagogical Beliefs as Predictors of Teacher Burnout

The presented study examined the relationship between teachers’ pedagogical beliefs and their experience of burnout. Its participants were 230 schoolteachers from fourteen Slovenian primary schools. The Questionnaire of Teacher Pedagogical Beliefs and Maslach Burnout Inventory-Educators Survey were applied. The findings suggest pedagogical beliefs as predictors of teacher burnout dimensions. Teachers’ negative pedagogical beliefs about students’ behavior and discipline maintenance are related to a greater experience of emotional exhaustion whilst negative beliefs about teachers’ trust in students and the role and responsibility of the teacher are related to a greater experience of depersonalization and decreases in personal accomplishment.
Improving Spatial Disaggregation of Crop Yield by Incorporating Machine Learning with Multisource Data: A Case Study of Chinese Maize Yield

Spatially explicit crop yield datasets with continuous long-term series are essential for understanding the spatiotemporal variation of crop yield and the impact of climate change on it. There are several spatial disaggregation methods to generate gridded yield maps, but these either use an oversimplified approach with only a couple of ancillary data or an overly complex approach with limited flexibility and scalability. This study developed a spatial disaggregation method using improved spatial weights generated from machine learning. When applied to Chinese maize yield, extreme gradient boosting (XGB) derived the best prediction results, with a cross-validation coefficient of determination (R2) of 0.81 at the municipal level. The disaggregated yield at 1 km grids could explain 54% of the variance of the county-level statistical yield, which is superior to the existing gridded maize yield dataset in China. At the site level, the disaggregated yields also showed much better agreement with observations than the existing gridded maize yield dataset. This lightweight method is promising for generating spatially explicit crop yield datasets with finer resolution and higher accuracy, and for providing necessary information for maize production risk assessment in China under climate change.
Chronic Lymphocytic Leukemia Progression Diagnosis with Intrinsic Cellular Patterns via Unsupervised Clustering

Simple Summary Distinguishing between chronic lymphocytic leukemia (CLL), accelerated CLL (aCLL), and full-blown transformation to diffuse large B-cell lymphoma (Richter transformation; RT) has significant clinical implications. Identifying cellular phenotypes via unsupervised clustering provides the most robust analytic performance in analyzing digitized pathology slides. This study serves as a proof of concept that using an unsupervised machine learning scheme can enhance diagnostic accuracy. Abstract Identifying the progression of chronic lymphocytic leukemia (CLL) to accelerated CLL (aCLL) or transformation to diffuse large B-cell lymphoma (Richter transformation; RT) has significant clinical implications as it prompts a major change in patient management. However, the differentiation between these disease phases may be challenging in routine practice. Unsupervised learning has gained increased attention because of its substantial potential in data intrinsic pattern discovery. Here, we demonstrate that cellular feature engineering, identifying cellular phenotypes via unsupervised clustering, provides the most robust analytic performance in analyzing digitized pathology slides (accuracy = 0.925, AUC = 0.978) when compared to alternative approaches, such as mixed features, supervised features, unsupervised/mixed/supervised feature fusion and selection, as well as patch-based convolutional neural network (CNN) feature extraction. We further validate the reproducibility and robustness of unsupervised feature extraction via stability and repeated splitting analysis, supporting its utility as a diagnostic aid in identifying CLL patients with histologic evidence of disease progression. The outcome of this study serves as proof of principle using an unsupervised machine learning scheme to enhance the diagnostic accuracy of the heterogeneous histology patterns that pathologists might not easily see.
Benthic Microbial Communities in a Seasonally Ice-Covered Sub-Arctic River (Pasvik River, Norway) Are Shaped by Site-Specific Environmental Conditions

The Pasvik River experiences chemical, physical, and biological stressors due to the direct discharges of domestic sewage from settlements located within the catchment and runoff from smelter and mine wastes. Sediments, as a natural repository of organic matter and associated contaminants, are of global concern for the possible release of pollutants in the water column, with detrimental effects on aquatic organisms. The present study was aimed at characterizing the riverine benthic microbial community and evaluating its ecological role in relation to the contamination level. Sediments were sampled along the river during two contrasting environmental periods (i.e., beginning and ongoing phases of ice melting). Microbial enzymatic activities, cell abundance, and morphological traits were evaluated, along with the phylogenetic community composition. Amplified 16S rRNA genes from bacteria were sequenced using a next-generation approach. Sediments were also analyzed for a variety of chemical features, namely particulate material characteristics and concentration of polychlorobiphenyls, polycyclic aromatic hydrocarbons, and pesticides. Riverine and brackish sites did not affect the microbial community in terms of main phylogenetic diversity (at phylum level), morphometry, enzymatic activities, and abundance. Instead, bacterial diversity in the river sediments appeared to be influenced by the micro-niche conditions, with differences in the relative abundance of selected taxa. In particular, our results highlighted the occurrence of bacterial taxa directly involved in the C, Fe, and N cycles, as well as in the degradation of organic pollutants and toxic compounds.
CMOS device optimization for system-on-a-chip applications

This paper describes a 0.13-/spl mu/m-generation CMOS technology optimized for system-on-a-chip (SoC) applications. The wide-range of performances obtained using a triple gate oxide and multiple threshold voltage control allows the SoC to operate at high speed with low standby power. Core CMOS transistors, which have a 1.9 nm gate oxide and a 95-nm physical gate length, show an excellent drive current of 740/335 /spl mu/A//spl mu/m at 1.2 V. Low power CMOS transistors have a standby current of only 2-0.2 pA//spl mu/m with a 2.6-nm gate oxide and a 120-nm gate length. This technology has also been used to make a 1.4-/spl mu/m/sup 2/ loadless 4T SRAM cell as well as a 2.5-/spl mu/m/sup 2/ 6T cell. The wiring RC delay has been reduced by integrating Cu interconnects with a low-k "ladder-oxide" layer.
Moderating Effect of Structural Holes on Absorptive Capacity and Knowledge-Innovation Performance: Empirical Evidence from Chinese Firms

Under open innovation, the position of the innovation subject in the knowledge network plays a vital role. The purpose of this paper was to identify the role of structural holes in the relationship between the knowledge-absorption capacity and the innovation performance. Previous studies have ignored the role of structural holes in this relationship. Moreover, there are differences between structural-hole theory and weak-relationship theory on the mechanism of the network location on the innovation performance. A hierarchical regression model was applied to test the hypothesis. The findings from a study of 74 Chinese-listed integrated-circuit companies confirm the positive effect that the absorptive capacity has on the innovation performance, as well as the moderating role of structural holes in this relationship. By benefiting from the advantages of information and control, structural-hole spanners often have stronger knowledge-absorption abilities, and they thus achieve higher innovation performances. The results suggest that the synergy of structural holes should be taken seriously by those enterprises that are trying to strengthen their knowledge-absorption abilities to improve their innovation performances.
Development of a Visualisation Approach for Analysing Incipient and Clinically Unrecorded Enamel Fissure Caries Using Laser-Induced Contrast Imaging, MicroRaman Spectroscopy and Biomimetic Composites: A Pilot Study

This pilot study presents a practical approach to detecting and visualising the initial forms of caries that are not clinically registered. The use of a laser-induced contrast visualisation (LICV) technique was shown to provide detection of the originating caries based on the separation of emissions from sound tissue, areas with destroyed tissue and regions of bacterial invasion. Adding microRaman spectroscopy to the measuring system enables reliable detection of the transformation of the organic–mineral component in the dental tissue and the spread of bacterial microflora in the affected region. Further laboratory and clinical studies of the comprehensive use of LICV and microRaman spectroscopy enable data extension on the application of this approach for accurate determination of the boundaries in the changed dental tissue as a result of initial caries. The obtained data has the potential to develop an effective preventive medical diagnostic approach and as a result, further personalised medical treatment can be specified.
Seleksi Fitur Terhadap Performa Kinerja Sistem E-Nose untuk Klasifikasi Aroma Kopi Gayo

Tujuan dari penelitian ini adalah mengoptimasi kinerja system E-Nose dengan melakukan seleksi fitur untuk memperoleh kombinasi fitur yang terbaik dalam mengklasifikasi aroma jenis kopi arabika Gayo. Kopi ini merupakan salah satu kopi spesial dari Indonesia yang berasal dari Provinsi Aceh. Berbagai faktor dapat mempengaruhi hasil akhir kopi salah satunya pada proses pengolahan pasca panen diantaranya teknik proses kering (drying) dengan metode Natural dan Wine. Perbedaan metode pengolahan pasca panen ini dapat mempengaruhi aroma kopi yang dihasilkan dari setiap kopi yang memiliki aroma dan cita rasa yang khas. Penerapan sistem Electronic Nose (E-Nose) dapat diaplikasikan untuk mengklasifikasi aroma yang berbeda dari jenis kopi Gayo natural dan Gayo wine, namun kesamaan respon sensor dan banyaknya data menyebabkan kurang spesifik dan menurunkan performa kinerja sistem. Implementasi seleksi fitur dapat diterapkan pada proses klasifikasi dengan menggunakan metode Support Vector Machine (SVM) berdasarkan jumlah galat Sum of Absolute Errors (SAE) untuk mendapatkan kombinasi fitur terbaik sehingga mendapatkan kinerja sistem yang lebih optimal. Hasil penelitian ini mendapatkan 5 fitur terbaik dengan nilai akurasi sebesar 93,33%, presisi sebesar 93,33% dan sensitivitas sebesar 93,33%.
Distinct Tomato Cultivars Are Characterized by a Differential Pattern of Biochemical Responses to Drought Stress

Future climate scenarios suggest that crop plants will experience environmental changes capable of affecting their productivity. Among the most harmful environmental stresses is drought, defined as a total or partial lack of water availability. It is essential to study and understand both the damage caused by drought on crop plants and the mechanisms implemented to tolerate the stress. In this study, we focused on four cultivars of tomato, an economically important crop in the Mediterranean basin. We investigated the biochemical mechanisms of plant defense against drought by focusing on proteins specifically involved in this stress, such as osmotin, dehydrin, and aquaporin, and on proteins involved in the general stress response, such as HSP70 and cyclophilins. Since sugars are also known to act as osmoprotectants in plant cells, proteins involved in sugar metabolism (such as RuBisCO and sucrose synthase) were also analyzed. The results show crucial differences in biochemical behavior among the selected cultivars and highlight that the most tolerant tomato cultivars adopt quite specific biochemical strategies such as different accumulations of aquaporins and osmotins. The data set also suggests that RuBisCO isoforms and aquaporins can be used as markers of tolerance/susceptibility to drought stress and be used to select tomato cultivars within breeding programs.
CONGESTION MANAGEMENT IN DEREGULATED POWER SYSTEM USING REAL CODED GENETIC ALGORITHM

Professor & Head, Electrical & Electronics Engineering Department, Thiagarajar College of Engineering, Madurai, Tamilnadu, India Abstract : In this paper, an efficient method has been proposed for transmission line over load alleviation in deregulated power system using real coded genetic algorithm (RCGA). For secure operation of power system, the network loading has to be maintained within specified limits. Transmission line congestion initiates the cascading outages which forces the system to collapse. Accurate prediction and alleviation of line overloads is the suitable corrective action to avoid network collapse. In this paper an attempt is made to explore the use of real coded genetic algorithm to find the optimal generation rescheduling for relieving congestion. The effectiveness of the proposed algorithm has been analyzed on IEEE 30 bus test system. The results obtained by the proposed method are found to be quite encouraging when compared with Simulated Annealing (SA) and hence it will be useful in electrical restructuring.
NUMERICAL SIMULATION OF THE FLOW OF A NEWTONIAN FLUID USED IN CURVED PIPES

This paper deals with the numerical simulation of the flow of a Newtonian fluid in curved pipes using the computational fluid dynamics. Settings curved tubes has received attention in the literature due to its use in heat exchangers and process oil exploration, where the flow of crude oil (water, gas and oil) from a reservoir to the maritime unit is carried through pipelines curved rigid applied to heat exchangers. It is considered the main flow (along the axis of curvature of the duct) developed and utilizes a Cartesian coordinate system to express the conservation equations for mass, momentum and energy. The objective of this work is to study the fully developed flow in curved pipes varying some key parameters involved in this process, as the inlet temperature and velocity in the pipe. This problem was investigated in a scale model of a curved duct disk, using water as the working fluid and numerical techniques used to solve using the commercial application CFX version 12. Among the results obtained, it is shown that the effect of elevated temperatures and speeds affecting the input phenomenon being studied as a function of secondary flow generated.
Staphylococcus aureus and Methicillin-Resistant Coagulase-Negative Staphylococci in Nostrils and Buccal Mucosa of Healthy Camels Used for Recreational Purposes

Simple Summary Animal-associated staphylococci have been isolated in human infections. Therefore, these strains may pose a zoonotic risk in addition to constituting a reservoir for antimicrobial resistance genes. In this study, we isolated Staphylococcus aureus and other species of staphylococci from camels used for recreational activities in the Canary Islands. Most S. aureus lacked the antimicrobial resistance genes, but some staphylococci species carried the mecA gene which confers resistance to methicillin. The carriage of this gene conferring resistance to methicillin in staphylococci isolated from camels may be a public health concern since there is a risk of bacterial transmission to humans during recreational activities. Furthermore, since the Canary Islands are the only camel exporter to the European Union, camels could constitute a source of zoonotic agents to the rest of the European countries. Abstract Several different species of animals host staphylococci as normal microbiota. These animals can be a source of staphylococci zoonotic infections. People with routine or occupational exposure to infected/colonized animals are at risk of a potential transmission. Therefore, we aimed to investigate the presence of S. aureus and other staphylococci in camels used for recreational purposes as well as their antimicrobial resistance, virulence factors and genetic lineages. A total of 172 samples were collected from 86 healthy camels (nose and mouth) from different farms located in the Canary Islands, Spain. Antimicrobial susceptibility testing was performed against 14 antimicrobial agents. The presence of virulence genes was studied by PCR. Multilocus sequence typing, spa typing and agr typing were performed in all S. aureus isolates. From the 86 camels tested, 42 staphylococci were isolated, of which there were 11 S. aureus, 13 S. lentus, 12 S. sciuri, 3 S. xylosus, S. epidermidis, S. hominis and S. chromogenes. Staphylococci isolates were resistant to penicillin, ciprofloxacin, clindamycin and fusidic acid. All S. aureus isolates harbored the hla, hlb and hld virulence genes. S. aureus isolates were ascribed to three sequence types (STs) and three spa types. All S. aureus isolates belonged to agr type III. Camels from Gran Canaria used in recreational purposes have a moderate prevalence of S. aureus and other coagulase-negative staphylococci. Nevertheless, S. aureus isolates are susceptible to almost all antibiotics tested.