Miracle-dz/UniFAR-FTUs huggingface dataset:
Ano1 is a Prognostic Biomarker That is Correlated with Immune Infiltration in Colorectal Cancer

Background Anoctamin 1 (ANO1) has been observed to be overexpressed in gastrointestinal and pulmonary epithelial cells, as well as in a number of cancers. Although Ano1 is involved in the prognosis of colorectal cancer (CRC), its mechanism of action in metastatic CRC has not been fully elucidated. Methods The expression of Ano1 was assessed in samples obtained from The Cancer Genome Atlas (TCGA) database. Then, we used Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, Gene set enrichment analysis (GSEA), Gene set variation analysis (GSVA), and Weighted Correlation Network Analysis (WGCNA) to determine the functions of Ano1. Additionally, random survival forest, Cox multivariate analysis, Kaplan Meier analysis, and ROC were used to determine the predictive value of Ano1 on clinical outcomes in CRC patients. Finally, HE staining, immunohistochemical (IHC) analysis and qRT-PCR were used to explore the expression of the Ano1 gene in CRC tissue. Results The expression level of Ano1 in CRC was significantly elevated, and the prognosis was poor. The modules with a higher proportion of upregulated genes tended to be positively correlated with Ano1-high. KNG1, GNG4, F2, POSTN, THBS2, SPP1 and FGA were identified as hub proteins of the PPI network. The heatmap showed that the expression level of the Ano1-high group was significantly negatively correlated with immune infiltrate. The overexpression of the Ano1 gene in CRC tissue samples was also confirmed by HE staining, immunohistochemical (IHC) analysis and qRT-PCR. Conclusion High expression of Ano1 is closely related to a poor prognosis in patients with colorectal cancer. Ano1 may participate in the metastasis and progression, as well as the immune regulation of CRC. In summary, Ano1 can act as a potential prognostic biomarker and a novel target for CRC therapy.
A 1.7–2.7-GHz 4-bit Phase shifter based on packaged RF MEMS switches

This study presents a 4-bit phase shifter with a maximum phase shift degree of 75° based on packaged metal-contact single-pole double-throw (SPDT) radio frequency microelectromechanical system (RF MEMS) switches mounted on a 20 mil RO4350 substrate and assembled with its driver module on a 4-layer printed circuit board (PCB) board. Electric length of 10° and characteristic impedance of 61.7 Ω are selected for T-stub matching. Standard PCB processing makes it easy to develop and suitable for taking place of mechanical tilt employed in recent base station. Measurements indicate a maximum insertion loss of 1.37 dB at 2.7 GHz and a minimum return loss of 11.71 dB. The phase accuracy is within 1.75° at 2.7 GHz.
Predicting the flexural capacity of corroded reinforced concrete beams using artificial intelligence models

Predicting the residual flexural capacity of corroded reinforced concrete (RC) structures is to help civil engineers decide to repair or strengthen the structures. This study presents the application of six single algorithm-based models of artificial intelligence, such as artificial neural network (ANN), support vector machine (SVM), classification and regression trees (CART), linear regression (LR), general linear model (GENLIN), and automatic Chi-squared interaction detection (CHAID) to predict the residual flexural capacity of corroded RC structures. The predicting results are compared to the surveyed data including 120 corroded RC beams from the projects built before 1975 to rank the efficiency of single models. Some combined models are applied to investigate the improvement in predicting the flexural capacity of corroded RC structures compared to the single models. The result shows that LR and GENLIN models give almost the same results and the best efficiency. The combined models can not improve the efficiency compared to the two best single models
Face Recognition Software

UGC Sponsored two-day national conference on ‘Collection Development of Resources in an Electronic Environment’ was organised by Gokhale Education Society's College of Education, Mumbai on 17-18 February, 2011 in Mumbai. For details contact the Organising Secretary: Librarian Dr. Shilpa Waghchoure on sswaghchoure@gmail.com
Reaction-Diffusion Inspired Sensor Networking: From Theory to Application

: Alan Turing introduced a novel Reaction-Diffusion (RD) model in 1952 to explain biological pattern formation found in animals. Since then, studies based on the RD model have long proved the feasibility of adapting it to spatial patern formation in distributed systems, especially in networking systems. In the past two decades, RD mechanism started being applied to Wireless Sensor Networks, and the possiblity of expanding to new applications is promising. In this paper, we ﬁrst review the original RD model and further show its variants, known as activator-inhibitor models. Several research efforts on applying them to model tasks in wireless sensor networks will be presented and summarized.
Response of an Indicator Species, Dryopteris crassirhizoma, to Temporal and Spatial Variations in Sika Deer Density

Simple Summary Deer can affect forest ecosystems through foraging behavior. Using indicator species that are sensitive to temporal and spatial variations in deer density has the advantage of managing deer effectively and practically. We examined the response of Dryopteris crassirhizoma to the variations in sika deer density in Hokkaido, Japan. We showed that the grazing intensity of D. crassirhizoma was sensitive to short-term decreases in deer density and positively related to spatial variation in deer density within regions. Dryopteris crassirhizoma can be a useful indicator species and using grazing intensity could help managers rapidly determine their management direction and decide where to focus their efforts. Abstract Identifying appropriate indicator species for the impact of deer on forest vegetation is crucial for forest management in deer habitats and is required to be sensitive to temporal and spatial variations in deer density. Dryopteris crassirhizoma was selected as a new indicator to evaluate the response to these variations. We examined the population-level characteristics, morphological characteristics at the individual level, and grazing intensity of D. crassirhizoma at temporally different deer density sites in Hokkaido, Japan. The response of D. crassirhizoma to spatial variation in deer density was also examined within and between two regions in Hokkaido, Japan. Although the population-level characteristics and morphological characteristics did not significantly respond to short-term decreases in deer density, grazing intensity significantly decreased with decreasing deer density. The grazing intensity was also positively related to the spatial variation of deer density within both regions, but the estimated coefficient of the grazing intensity differed between regions. We concluded that D. crassirhizoma can be a useful indicator species of the impact of deer on forest vegetation. The grazing intensity of the indicator species was sensitive to temporal and spatial variations in deer density within the region.
A Comparison of Deep Reinforcement Learning Models for Isolated Traffic Signal Control

Traditional control methods may not be adaptive enough for ever-changing traffic dynamics. Hence, extensive deep reinforcement learning (DRL) methods have been utilized to solve the traffic signal timing control problem because DRL can adaptively learn optimal policy through analyzing experience samples generated by interaction with the environment. However, there is an urgent need for researchers to answer which DRL algorithm should be adopted in practice and how to select model settings. Therefore, we introduce a reasonable simulation platform to test and compare different DRL methods. Specifically, we evaluate seven prevailing DRL algorithms under our defined model settings from two aspects: training and execution performance. Testing results indicate that the soft actor–critic (SAC) outperforms other DRL algorithms and the maximum pressure method in most cases. To our best knowledge, this is also the first study to apply SAC and value distribution methods for traffic signal control. To answer how to select model settings, we compare the execution performance of the DRL algorithms with different state, action, and reward settings. Experimental results reveal the superiority of our model-setting choices. All these findings have enlightening effects on other traffic decision management problems, such as ramp and multi-intersection control.
Multi-Center Agent Loss for Visual Identification of Chinese Simmental in the Wild

Simple Summary Visual identification of cattle in a realistic farming environment is helpful for real-time cattle monitoring. Based on continuous cattle detection, identification, and behavior recognition, it is possible to utilize cameras on farms within company or government networks to provide the services of production supervision, early disease detection, and animal science research for precision livestock farming. However, cattle identification in the wild is still a difficult problem due to the high similarities of different identities and the variances of the same identity as posture or perspective changes. Our proposed method based on deep convolutional neural networks and deep metric learning provides a promising approach for cattle identification and paves the way toward continuous monitoring of cattle in a nearly natural state. Abstract Visual identification of cattle in the wild provides an essential way for real-time cattle monitoring applicable to precision livestock farming. Chinese Simmental exhibit a yellow or brown coat with individually characteristic white stripes or spots, which makes a biometric identifier for identification possible. This work employed the observable biometric characteristics to perform cattle identification with an image from any viewpoint. We propose multi-center agent loss to jointly supervise the learning of DCNNs by SoftMax with multiple centers and the agent triplet. We reformulated SoftMax with multiple centers to reduce intra-class variance by offering more centers for feature clustering. Then, we utilized the agent triplet, which consisted of the features and the agents, to enforce separation among different classes. As there are no datasets for the identification of cattle with multi-view images, we created CNSID100, consisting of 11,635 images from 100 Chinese Simmental identities. Our proposed loss was comprehensively compared with several well-known losses on CNSID100 and OpenCows2020 and analyzed in an engineering application in the farming environment. It was encouraging to find that our approach outperformed the state-of-the-art models on the datasets above. The engineering application demonstrated that our pipeline with detection and recognition is promising for continuous cattle identification in real livestock farming scenarios.
Experimental and Theoretical Investigations of Low-Dimensional BiFeO3 System for Photocatalytic Applications

We report on the fabrication of sub-20 nm BiFeO3 (BFO) nanoparticles using a solid-state approach and preferential leching process. The nanoparticles were subsequently used to deposit, through spray pyrolysis, BFO thin films in a rhombohedral (R3c) crystallographic structure. Then, systematic investigations of the optical and the photocatalytic properties were conducted to determine the effects of the particles size, the microstructure and the increased surface area on their catalytic performances. Especially, improved optical properties were observed, with an optical bandgap energy of 2.20 eV compared to reported 2.7 eV for the bulk system. In addition, high optical absorption was obtained in the UV–visible light region reaching up to 90% at 400 nm. The photoelectrochemical measurements revealed a high photocurrent density under visible light irradiation. Besides, density functional theory calculations were performed on both bulk and thin film BFO structures, revealing an interesting comparison of the electronic, magnetic, ferroelectric and optical properties for bulk and thin film BFO systems. Both theoretical and experimental findings show that the alignment of the band edges of BFO thin film is coherent with good photocatalytic water splitting potential, making them desirable photoanode materials.
Effect of Axial Fluid Conduction on Heat Transfer in the Entrance Regions of Parallel Plates and Tubes

The laminar heat transfer in thermal-entry regions of parallel plates and tubes is investigated for special conditions under which the contribution of axial fluid conduction is comparable to or greater than the axial convection (low Peclet numbers). Zero and finite axial-conduction solutions for the local and mean fluid temperature and the local total Nusselt number are presented for uniform-velocity flow, finite wall resistance, and for both a uniform ambient temperature and step discontinuity in the ambient temperature. Calculated mean fluid temperatures, local total Nusselt numbers, and thermal-entry lengths are compared with corresponding predictions for the conventional case of zero axial conduction.
Improving classroom assessment in primary mathematics education in the Netherlands

We report on the results of the Improving Classroom Assessment (ICA) project in the Netherlands that was aimed at improving primary students' mathematics achievement through improving their teachers' classroom assessment. Towards this end we first investigated primary teachers' assessment practice in a large-scale survey study. After having described and profiled teach-ers' current assessment practice, we designed a number of classroom assessment techniques, which were tested for feasibility in two small-scale sub-studies. Finally, we evaluated the effectiveness of the use of these classroom assessment techniques in a large-scale evaluation. Results indicate that students generally benefit from their teachers' improved use of classroom assessment techniques in mathematics.
An improved co-evolutionary algorithm for green manufacturing by integration of recovery option selection and disassembly planning for end-of-life products

There is a strong need for recovery decision-making for end-of-life (EOL) products to satisfy sustainable manufacturing requirements. This paper develops and tests a profit maximisation model by simultaneously integrating recovery option selection and disassembly planning. The proposed model considers the quality of EOL components. This paper utilises an integrated method of multi-target reverse recursion and partial topological sorting to generate a feasible EOL solution that also reduces the complexity of genetic constraints handling. In order to determine recovery options, disassembly level and disassembly sequence simultaneously, this paper develops an improved co-evolutionary algorithm (ICA) to search for an optimal EOL solution. The proposed algorithm adopts the evolutionary mechanism of localised interaction and endosymbiotic competition. Further, an advanced local search operator is introduced to improve convergence performance, and a global disturbance strategy is also suggested to prevent premature convergence. Finally, this paper conducts a series of computational experiments under various scenarios to validate the meta-heuristic integrated decision-making model proposed and the superiority of the developed ICA. The results show that the proposed approach offers a strong and flexible decision support tool for intelligent recovery management in a ubiquitous information environment. We discuss the theoretical and practical contributions of this paper and implications for future research.
Examination of Effective Buccal Absorption of Salmon Calcitonin Using Cell-Penetrating Peptide-Conjugated Liposomal Drug Delivery System

Introduction The buccal route has been considered an attractive alternative delivery route for injectable formulations. Cell-penetrating peptides (CPPs) are gaining increased attention for their cellular uptake and tissue permeation effects. This study was aimed to evaluate the in vitro and ex vivo permeation-enhancing effect of penetratin-conjugated liposomes for salmon calcitonin (sCT) in TR146 human buccal cells and porcine buccal tissues. Methods Penetratin was conjugated to phospholipids through a maleimide-thiol reaction. Liposomes were prepared and sCT was encapsulated using a thin-film hydration method. Physical properties such as particle size, zeta potential, encapsulation efficiency, and morphological images via transmission electron microscopy were obtained. Cellular uptake studies were conducted using flow cytometry (FACS) and confocal laser scanning microscopy (CLSM). A cell permeation study was performed using a Transwell® assay, and permeation through porcine buccal tissue was evaluated. The amount of sCT permeated was quantified using an ELISA kit and was optically observed using CLSM. Results The particle size of penetratin-conjugated liposomes was approximately 123.0 nm, their zeta potential was +29.6 mV, and their calcitonin encapsulation efficiency was 18.0%. In the cellular uptake study using FACS and CLSM, stronger fluorescence was observed in penetratin-conjugated liposomes compared with the solution containing free sCT and control liposomes. Likewise, the amount of sCT permeated from penetratin-conjugated liposomes was higher than that from the free sCT solution and control liposomes by 5.8-fold across TR146 cells and 91.5-fold across porcine buccal tissues. Conclusion Penetratin-conjugated liposomes are considered a good drug delivery strategy for sCT via the buccal route.
Review of Microgels for Enhanced Oil Recovery: Properties and Cases of Application

In todays’ world, there is an increasing number of mature oil fields every year, a phenomenon that is leading to the development of more elegant enhanced oil recovery (EOR) technologies that are potentially effective for reservoir profile modification. The technology of conformance control using crosslinked microgels is one the newest trends that is gaining momentum every year. This is due to the simplicity of the treatment process and its management, as well as the guaranteed effect in the case of the correct well candidate selection. We identified the following varieties of microgels: microspheres, thermo- and pH-responsible microgels, thin fracture of preformed particle gels, colloidal dispersed gels. In this publication, we try to combine the available chemical aspects of microgel production with the practical features of their application at oil production facilities. The purpose of this publication is to gather available information about microgels (synthesis method, monomers) and to explore world experience in microgel application for enhanced oil recovery. This article will be of great benefit to specialists engaged in polymer technologies at the initial stage of microgel development.
Dynamic characteristics of single-loop gear system based on bond graph method

The complexity of single-loop gear system transmission structure makes it difficult for traditional modeling methods to establish precise dynamic model, which greatly affects the accuracy of its dynamic characteristics research. Firstly, a structure diagram is established by adopting modularization idea according to the structural properties of single-loop gear system. On this basis, a precise bond graph model of the single-loop gear system is obtained combining the modeling principle of bond graph method and the advantages of rich graphics library. Secondly, the dynamic state equation of single-loop gear system is obtained from bond graph model. The simulation model of gear system is established by numerical simulation method. Eventually, the dynamic characteristics of a single-loop gear system are acquired by calculating two dynamic indexes of the system under linear and weakly nonlinear states. The simulation results show that the bond graph method can accurately describe the mathematical model of single-loop gear train and master the dynamic characteristics of complex gear train. This will provide a reference for the structural design and dynamic characteristics of the transmission system.
Nocturnal Birds of Prey as Carriers of Staphylococcus aureus and Other Staphylococci: Diversity, Antimicrobial Resistance and Clonal Lineages

Owls are nocturnal predators that inhabit urbanized and farmlands. They are in direct contact with other animals, both livestock and small wild rodents that they mostly feed on. Staphylococci can be both commensal and pathogenic bacteria that are widespread across the various ecological niches. We aimed to isolate staphylococci from owls and to characterize their antimicrobial resistance, virulence factors and genetic lineages. Swab samples were collected from the throat and cloaca of 114 owls admitted to two rehabilitation centers in Portugal. The identification of staphylococci species was performed by MALDI-TOF. Staphylococci antimicrobial resistance and virulence genes were investigated by means of the disk diffusion method and PCR. Staphylococcus aureus isolates were characterized by MLST, agr and spa-typing. Of the tested animals, 66 isolates were recovered, including 10 different species of staphylococci, of which 25 were coagulase-positive (CoPS) and 41 were coagulase-negative (CoNS). Twenty-three S. aureus were isolated, of which one mecC-MRSA was identified. The isolates were mainly resistant to penicillin, aminoglycosides, clindamycin and tetracycline. mecC-MRSA belonged to ST1245 and spa-type t843 and the remaining S. aureus were ascribed to 12 STs and 15 spa types. A high diversity of clonal lineages was identified among the S. aureus isolated from wild owls. Owls feed mainly on small rodents often exposed to waste and anthropogenic sources, which may explain the moderate prevalence of S. aureus in these animals.
The Different Temozolomide Effects on Tumorigenesis Mechanisms of Pediatric Glioblastoma PBT24 and SF8628 Cell Tumor in CAM Model and on Cells In Vitro

It is necessary to elucidate the individual effects of temozolomide (TMZ) on carcinogenesis and tumor resistance to chemotherapy mechanisms. The study aimed to investigate the TMZ 50 and 100 μM dose effect difference between PBT24 and SF8628 cell line high-grade pediatric glioblastoma (phGBM) xenografts in a chicken chorioallantoic membrane (CAM) model, on PCNA and EZH2 immunohistochemical expression in the tumor and on the expression of NKCC1, KCC2, E- and N-cadherin genes in TMZ-treated and control cell groups in vitro. TMZ at a 100 μg dose reduced the incidence of PBT24 xenograft invasion into the CAM, CAM thickening and the number of blood vessels in the CAM (p < 0.05), but did not affect the SF8628 tumor in the CAM model. The TMZ impact on PBT24 and SF8628 tumor PCNA expression was similarly significantly effective but did not alter EZH2 expression in the studied tumors. The TMZ at 50 μM caused significantly increased RNA expression of the NKCC1 gene in both studied cell types compared with controls (p < 0.05). The expression of the KCC2 gene was increased in PBT24 TMZ-treated cells (p < 0.05), and no TMZ effect was found in SF8628-treated cells. The study supports the suggestion that individual sensitivity to TMZ should be assessed when starting treatment.