bluuebunny/crossref_metadata_2025 huggingface dataset:
Real Time Monitoring System Dari Active Solar Photovoltaic Tracker Berbasis Internet Of Things
Authors: Bagus Kurniansyah Izra , Ronilaya Ferdian , Fahmi Hakim Muhammad
Published: November 2020

Abstract: This monitoring system is used to monitor currents and voltages from Solar Power Plants (PLTS) with solar cell capacities of 50WP, 80WP, and 100WP. PLTS used is an active type of solar tracker, where solar cells used can find the maximum solar irradiation position by determining the upper and lower voltages as the reference voltage in the Arduino program. After PLTS can produce energy, then the energy can be used to turn on AC and DC electrical loads. From the energy used, here of course there are currents and voltages starting from the output of the solar cell, the accumulator output, the input at the AC load, and the input at the DC load. The monitoring results that have been carried out subsequently will be automatically sent to the Thingspeak application by using the SIM800L Module. This thingspeak application will send data in the form of numbers and graphs in real time. By comparing the value of the measurement results on Arduino and the thingspeak application, we get the size of the percentage of reading errors on the measuring instrument.
Implementasi Metode Naive Bayes Untuk Memprediksi Resiko Penyakit Jantung
Authors: Tempola firman
Published: November 2020

Kematian akibat penyakit jantung terus meningkat dan tak mengenal usia muda dan tua. World Health Organization menyebutkan 7,3 juta penduduk dunia meninggal akibat dari penyakit jantung. Bahkan disebutkan penyakit jantung adalah salah penyakit nomor satu paling mematikan. Untuk itu penting diketahui resiko dari pentakit jantung dengan menerapkan model-model yang ada pada machine learning. Tujuan dari penelitian ini yaitu untuk mengimplementasikan metode Naive Bayes untuk memprediksi penyakit jantung, serta dilakukan ujii kinerja algoritma dengan menghitung presisi, recall dan akurasi. Adapun Kriteria-kriteria yang digunakan pada penelitian ini yaitu umur, jenis kelamin, jenis sakit dada, tekanan darah, kolestrol, kadar gula, elektrokardiografi, tekanan jantung, angina induksi, old-peak, segmen_st, Fluoroskopi, denyut jantung. Sedangkan class yang diprediksi ada 2 beresiko dan tidak beresiko. Hasil dalam penelitian ini menunjukan bahwa metode berhasil memprediksi atau mengklasifikasi pasien beresiko penyakit jantung dan tidak beresiko penyakit jantung dengan persentase precision 90%, recall 100% serta mendapatkan akurasi 92.85% dan termaksuk exellent classification.
PERANCANGAN APLIKASI GERBANG LOGIKA DENGAN MENGGUNAKAN ELECTRONIK WORKBANCH PADA MATAKULIAH ELEKTRONIKA DIGITAL
Authors: Rosmiati Rosmiati , Ruhamah Ruhamah
Published: November 2020

Dalam Penelitian dengan judul “Perancangan Aplikasi Gerbang Logika dengan Menggunakan Electronic Workbanch pada Matakuliah Elektronika Digital” bertujuan untuk merancang dan membuat Aplikasi Gerbang Logika dengan Menggunakan Electronic Workbanch pada Matakuliah Elektronika Digital. Dalam matakuliah Elektronika Digital terdapat beberapa materi yang dibahas sesuai dengan deskripsi matakuliah pada kurikulum Program Studi Informatika salah satunya yaitu materi gerbang logika. Pada materi gerbang logika diperlukan suatu aplikasi untuk lebih memahami prinsip dari gerbang logika dasar salah satunya dengan menggunakan aplikasi Elektronic Workbanch. Penelitian ini menghasilkan suatu Perancangan aplikasi Gerbang Logika dengan menggunakan Elektronic Workbanch yang dapat diterapkan pada matakuliah Elektronika digital yang dapat bermanfaat dalam menunjang kegiatan pembelajaran di dalam kelas. Dengan adanya Perancangan Aplikasi Gerbang Logika dapat membantu dosen dalam pelaksanaan kegiatan perkuliahan khususnya pada Matakuliah Elektronika Digital. Materi Gerbang Logika merupakan matakuliah dasar yang ada pada Program Studi Informatika Fakultas Teknik Komputer Universitas Cokroaminoto Palopo
Algumas Notas Sobre a Perspectiva Histórico-Cultural na Investigação da Esquizofrenia
Authors: Carvalho Bruno Peixoto
Published: November 2020

Este texto reúne – sob a forma de notas – um conjunto de reflexões realizadas entre os anos de 2013 e 2017 em torno do problema da esquizofrenia na perspectiva histórico-cultural. As notas aqui presentes se nutrem das discussões feitas no Grupo de Pesquisa Marxismo e Psicologia (UFMS) e também nas atividades de ensino de psicopatologia no curso de psicologia pelo autor deste trabalho. O trabalho aqui objetivado assume a forma da exposição que fiz no III Evento do Método e Metodologia em pesquisa na abordagem do materialismo histórico-dialético e da psicologia histórico-cultural, ou seja, a de um esboço pouco sistemático de questões importantes dirigidas a quem se dedique à investigação dos problemas das psicopatologias em geral e da esquizofrenia em particular. Justifica ainda a forma ensaística deste texto o fato de que é muito recente (em relação à psiquiatria moderna) a incursão da psicologia histórico-cultural na tentativa de explicar estas formas de sofrimento a que se costuma chamar psicopatologia. O leitor poderá encontrar parte importante destes esforços na obra O processo de desenvolvimento normal e anormal para a Psicologia Histórico-Cultural: estudos contemporâneos (Tuleski & Franco, no prelo) e em particular sobre o problema da esquizofrenia, poderá encontrar subsídios no capítulo de Almeida, Carvalho e Tuleski (2018), do mesmo livro.
O Método em Marx: Derivações para Pesquisa Educacional
Authors: Aquino Orlando Fernández , González Alberto Matías
Published: November 2020

Certamente, o que não nos falta no Brasil são relatos que avaliam o desenvolvimento histórico e contraditório da pesquisa educacional, cuja institucionalização aparece com a criação do INEP / Instituto Nacional de Estudos e Pesquisas Educacionais, em 1938, sob a direção do Ministério da Educação. Os primeiros estudos aos quais tivemos acesso (Gouveia, 1971, 1976, Mello, 1983, Gatti, 1983, Demo, 1983), bem como os mais atuais (Warde, 1990; Alves-Mazzotti, 2001; Gatti, 2001, 2006) fazem referência às etapas, problemas, limitações e avanços da pesquisa em educação no Brasil. Apesar do aumento expressivo da pesquisa educacional na progressão histórica, na formação crescente de pesquisadores e nas diferenças contextuais de cada momento, os problemas deste campo poderiam ser resumidos da seguinte forma: inconsistência teórica e metodológica; uso limitado de métodos de coleta e análise de dados; pouca preocupação com a formulação de categorias teóricas, dando origem à aplicação ingênua de conceitos utilizados em outras ciências; linhas teóricas e metodológicas pouco claras; falta de compreensão do fenômeno educacional, sua dinâmica interna e suas conexões com a sociedade e a política. No contexto destas questões, gostaríamos de nos concentrar em uma delas, que foca particularmente na direção de nossa análise. Em 1981, Guiomar Namo de Mello tinha interesse em explicar que a pesquisa educacional no Brasil foi afetada por dois movimentos inter-relacionados: a pobreza teórica e a inconsistência metodológica (Mello, 1983). Nove anos depois (Warde, 1990), assume o fundamento de Mello, mas não vai muito longe no assunto. Surpreendentemente os pesquisadores que vieram depois não deram às falhas teóricas e metodológicas o peso que elas têm para determinar a qualidade dos resultados científicos educacionais (...).
Targeting Bcl-2 Proteins in Acute Myeloid Leukemia
Authors: Wei Yunxiong , Cao Yaqing , Sun Rui , Cheng Lin , Xiong Xia , Jin Xin , He Xiaoyuan , Lu Wenyi , Zhao Mingfeng
Published: November 2020

B cell lymphoma 2 (BCL-2) family proteins play an important role in intrinsic apoptosis. Overexpression of BCL-2 proteins in acute myeloid leukemia can circumvent resistance to apoptosis and chemotherapy. Considering this effect, the exploration of anti-apoptotic BCL-2 inhibitors is considered to have tremendous potential for the discovery of novel pharmacological modulators in cancer. This review outlines the impact of BCL-2 family proteins on intrinsic apoptosis and the development of acute myeloid leukemia (AML). Furthermore, we will also review the new combination therapy with venetoclax that overcomes resistance to venetoclax and discuss biomarkers of treatment response identified in early-phase clinical trials.
Weed Control and Soybean (Glycine max (L.) Merr) Response to Mixtures of a Blended Foliar Fertilizer and Postemergence Herbicides
Authors: Lawrence Benjamin H. , Hydrick Huntington T. , Bond Jason A. , Golden Bobby R. , Allen Thomas W. , Sanders Tameka
Published: November 2020

Growers commonly mix foliar fertilizers with postemergence (POST) herbicides to reduce application costs and/or to decrease soybean injury. Field studies conducted in 2015 and 2016 in Stoneville, MS, evaluated the impact on weed control and soybean (Glycine max (L.) Merr) injury, growth, and yield when combining a blended foliar fertilizer with POST herbicide applications. Herbicide treatments included no herbicide and glyphosate alone and in combination with S-metolachlor, fomesafen, or lactofen. The blended foliar fertilizer was applied at 0, 0.39, and 0.78 kg a.i. ha−1. In the Weed Control Study, 14 antagonistic effects at various evaluations were detected on Palmer amaranth (Amaranthus palmeri (S.) Wats) and barnyardgrass (Echinochloa crus-galli (L.) P. Beauv.) control 7, 14, and 21 d after treatment (DAT) when a blended foliar fertilizer at 0.39 or 0.78 kg a.i. ha−1 was mixed with glyphosate alone or combined with S-metolachlor, fomesafen, or lactofen. Of the 14 total effects, nine were detected with foliar fertilizer at the higher rate of 0.78 kg a.i. ha−1. Seven antagonistic effects were detected for both weed species regardless of herbicide treatment or foliar fertilizer rate. The only treatment combination in which an antagonistic effect was not detected was glyphosate plus lactofen plus foliar fertilizer at 0.78 kg a.i. ha−1. Blended foliar fertilizer did not influence soybean injury. In the Agronomic Study, blended foliar fertilizer did not impact soybean injury, height, dry wt., nutrient conc., or yield. Foliar fertilizer in combination with POST soybean herbicides did not reduce soybean injury and produced inconsistent effects on weed control across herbicide treatments and between weed species.
Histological and Immunohistochemical Features of Trichoblastoma in a Sarda Breed Sheep
Authors: Polinas Marta , Burrai Giovanni P. , Vitiello Veronica , Falchi Laura , Zedda Maria T. , Masala Gerolamo , Marras Vincenzo , Satta Giulia , Alberti Alberto , Antuofermo Elisabetta
Published: November 2020

Skin tumors with adnexal differentiation are commonly reported in dogs and cats, while only anecdotal evidence is available in sheep. Here we illustrate the macroscopic, histologic, and immunohistochemical features of a cutaneous lesion with adnexal differentiation in a 6-year-old female Sarda breed sheep, surgically treated for a horn-like mass located in the left pinna. Additionally, we investigate a possible contribution of Ovine Papillomaviruses (OaPVs). Histologically, the dermis was expanded by an expansive and unencapsulated multilobulated nodule composed of cuboidal to spindle basaloid cells arranged in variably-sized cytokeratins (CK) AE1-AE3, CK 5/6 and CK 34 beta E12, p63—positive winding cords with a characteristic palisade arrangement of neoplastic cells in the periphery of the tumor. Based on these results, the cutaneous neoplasm was diagnosed as a trabecular trichoblastoma with spindle cells and rare structures resembling papillary mesenchymal bodies. Additionally, multiple enlarged sebaceous lobules clustered around dilated ducts suggestive of sebaceous gland hyperplasia were detected near the trichoblastoma. No PV DNA was found in the examined tissues, suggesting that ovine PVs are not involved in the pathogenesis of the present skin tumors with adnexal differentiation. Further investigations and efforts are required to elucidate the prevalence of skin tumors with adnexal differentiation in this species.
The Effect of Bacillus licheniformis-Fermented Products and Postpartum Dysgalactia Syndrome on Litter Performance Traits, Milk Composition, and Fecal Microbiota in Sows
Authors: Yu Yu-Hsiang , Hsu Ting-Yu , Chen Wei-Jung , Horng Yi-Bing , Cheng Yeong-Hsiang
Published: November 2020

This study was designed to evaluate the effects of Bacillus licheniformis-fermented products (BLFP) and postpartum dysgalactia syndrome (PDS) on litter performance traits, milk composition, and fecal microbiota in sows in a commercial farrow to finish pig farm. Fifty multiparous cross-bred pregnant sows were randomly assigned to two groups in a completely randomized design. The dietary treatments comprised a basal diet (pregnancy and nursery diet) as control and basal diet supplemented with 1.5 g/kg of BLFP. Sows with PDS in the two groups were further verified 12 h post-partum. Results show that the piglet body weight at weaning was increased in sows fed the BLFP compared to those fed the control diet. The milk fat content of prepartum sows was reduced in sows fed the BLFP. Postpartum sows with PDS had increased milk solid content compared with healthy sows. Microbial composition and species relative abundance analysis indicated distinct bacterial clusters between the groups. The abundance of the family Prevotellaceae in the feces decreased in sows with PDS. BLFP increased the average abundance of the genus (Eubacterium) coprostanoligenes group in feces of sows. These findings demonstrate that BLFP in the diet of sows can improve the piglet body weight at weaning and modulate the fecal microbiota of sows. PDS also has an impact on milk composition and fecal microbiota in sows.
Cats at the Vet: The Effect of Alpha-s1 Casozepin
Authors: Makawey Adjet , Iben Christine , Palme Rupert
Published: November 2020

The aim of this study was to evaluate the impact of α-s1 casozepin on cat stress responses at a veterinary practice. Cats feel confident in their familiar surroundings and daily routine. A visit, and transport, to the veterinarian is a stressful experience for cats and their owners. Stress can mask clinical signs and has physiological impacts. Alpha-s1 casozepin (Zylkène; Vétoquinol) could potentially minimize stress in cats with its calming and anxiolytic characteristics. A randomized, partial double-blind and placebo-controlled study was carried out with 60 adult cats. The trial was designed for three groups: low dose (15 mg/kg q24 h α-s1 casozepin for six days), high dose (75 mg/kg q24 h α-s1 casozepin for three days), and a placebo (one fructose capsule per day for three days). For the study, cats had a checkup at their trusted veterinarian without the dietary supplement, followed by a second one four weeks later. Alpha-s1 casozepin or a placebo was administered three to six days before the checkup. Fecal cortisol metabolites (FCMs) were measured to non-invasively evaluate the impact of α-s1 casozepin on adrenocortical activity. The cat owners and veterinarians also assessed the physiological reactions (respiratory rate, sweaty paws, pupils, panting, and vocalization) of the cats at home, in the waiting area, and in the examination room. The only significant effect (kappa coefficient κ = 0.007 and κ = 0.003) found in this study was the absence of sweaty paws in cats who were treated with the high dose of α-s1 casozepin over three days, observed in the waiting area and examination room of the veterinarian’s practice, respectively. Alpha-s1 casozepin also showed a small but insignificant reduction in FCM levels. Alpha-s1 casozepin influences the autonomic nervous system, and can inhibit sweaty paws during stressful situations for cats.
Complement and Cancer—A Dysfunctional Relationship?
Authors: Thurman Joshua M. , Laskowski Jennifer , Nemenoff Raphael A.
Published: November 2020

Although it was long believed that the complement system helps the body to identify and remove transformed cells, it is now clear that complement activation contributes to carcinogenesis and can also help tumors to escape immune-elimination. Complement is activated by several different mechanisms in various types of cancer, and complement activation fragments have multiple different downstream effects on cancer cells and throughout the tumor microenvironment. Thus, the role of complement activation in tumor biology may vary among different types of cancer and over time within a single tumor. In multiple different pre-clinical models, however, complement activation has been shown to recruit immunosuppressive myeloid cells into the tumor microenvironment. These cells, in turn, suppress anti-tumor T cell immunity, enabling the tumor to grow. Based on extensive pre-clinical work, therapeutic complement inhibitors hold great promise as a new class of immunotherapy. A greater understanding of the role of complement in tumor biology will improve our ability to identify those patients most likely to benefit from this treatment and to rationally combine complement inhibitors with other cancer therapies.
MARIE: A Context-Aware Term Mapping with String Matching and Embedding Vectors
Authors: Kim Han Kyul , Choi Sae Won , Bae Ye Seul , Choi Jiin , Kwon Hyein , Lee Christine P. , Lee Hae-Young , Ko Taehoon
Published: November 2020

With growing interest in machine learning, text standardization is becoming an increasingly important aspect of data pre-processing within biomedical communities. As performances of machine learning algorithms are affected by both the amount and the quality of their training data, effective data standardization is needed to guarantee consistent data integrity. Furthermore, biomedical organizations, depending on their geographical locations or affiliations, rely on different sets of text standardization in practice. To facilitate easier machine learning-related collaborations between these organizations, an effective yet practical text data standardization method is needed. In this paper, we introduce MARIE (a context-aware term mapping method with string matching and embedding vectors), an unsupervised learning-based tool, to find standardized clinical terminologies for queries, such as a hospital’s own codes. By incorporating both string matching methods and term embedding vectors generated by BioBERT (bidirectional encoder representations from transformers for biomedical text mining), it utilizes both structural and contextual information to calculate similarity measures between source and target terms. Compared to previous term mapping methods, MARIE shows improved mapping accuracy. Furthermore, it can be easily expanded to incorporate any string matching or term embedding methods. Without requiring any additional model training, it is not only effective, but also a practical term mapping method for text data standardization and pre-processing.
High-Quality, InN-Based, Saturable Absorbers for Ultrafast Laser Development
Authors: Monroy Laura , Jiménez-Rodríguez Marco , Monroy Eva , González-Herráez Miguel , B. Naranjo Fernando
Published: November 2020

New fabrication methods are strongly demanded for the development of thin-film saturable absorbers with improved optical properties (absorption band, modulation depth, nonlinear optical response). In this sense, we investigate the performance of indium nitride (InN) epitaxial layers with low residual carrier concentration (<1018 cm−3), which results in improved performance at telecom wavelengths (1560 nm). These materials have demonstrated a huge modulation depth of 23% and a saturation fluence of 830 µJ/cm2, and a large saturable absorption around −3 × 104 cm/GW has been observed, attaining an enhanced, nonlinear change in transmittance. We have studied the use of such InN layers as semiconductor saturable absorber mirrors (SESAMs) for an erbium (Er)-doped fiber laser to perform mode-locking generation at 1560 nm. We demonstrate highly stable, ultrashort (134 fs) pulses with an energy of up to 5.6 nJ.
A Review of Video Object Detection: Datasets, Metrics and Methods
Authors: Zhu Haidi , Wei Haoran , Li Baoqing , Yuan Xiaobing , Kehtarnavaz Nasser
Published: November 2020

Although there are well established object detection methods based on static images, their application to video data on a frame by frame basis faces two shortcomings: (i) lack of computational efficiency due to redundancy across image frames or by not using a temporal and spatial correlation of features across image frames, and (ii) lack of robustness to real-world conditions such as motion blur and occlusion. Since the introduction of the ImageNet Large Scale Visual Recognition Challenge (ILSVRC) in 2015, a growing number of methods have appeared in the literature on video object detection, many of which have utilized deep learning models. The aim of this paper is to provide a review of these papers on video object detection. An overview of the existing datasets for video object detection together with commonly used evaluation metrics is first presented. Video object detection methods are then categorized and a description of each of them is stated. Two comparison tables are provided to see their differences in terms of both accuracy and computational efficiency. Finally, some future trends in video object detection to address the challenges involved are noted.
Pre-Training Autoencoder for Lung Nodule Malignancy Assessment Using CT Images
Authors: Silva Francisco , Pereira Tania , Frade Julieta , Mendes José , Freitas Claudia , Hespanhol Venceslau , Costa José Luis , Cunha António , Oliveira Hélder P.
Published: November 2020

Lung cancer late diagnosis has a large impact on the mortality rate numbers, leading to a very low five-year survival rate of 5%. This issue emphasises the importance of developing systems to support a diagnostic at earlier stages. Clinicians use Computed Tomography (CT) scans to assess the nodules and the likelihood of malignancy. Automatic solutions can help to make a faster and more accurate diagnosis, which is crucial for the early detection of lung cancer. Convolutional neural networks (CNN) based approaches have shown to provide a reliable feature extraction ability to detect the malignancy risk associated with pulmonary nodules. This type of approach requires a massive amount of data to model training, which usually represents a limitation in the biomedical field due to medical data privacy and security issues. Transfer learning (TL) methods have been widely explored in medical imaging applications, offering a solution to overcome problems related to the lack of training data publicly available. For the clinical annotations experts with a deep understanding of the complex physiological phenomena represented in the data are required, which represents a huge investment. In this direction, this work explored a TL method based on unsupervised learning achieved when training a Convolutional Autoencoder (CAE) using images in the same domain. For this, lung nodules from the Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI) were extracted and used to train a CAE. Then, the encoder part was transferred, and the malignancy risk was assessed in a binary classification—benign and malignant lung nodules, achieving an Area Under the Curve (AUC) value of 0.936. To evaluate the reliability of this TL approach, the same architecture was trained from scratch and achieved an AUC value of 0.928. The results reported in this comparison suggested that the feature learning achieved when reconstructing the input with an encoder-decoder based architecture can be considered an useful knowledge that might allow overcoming labelling constraints.
Integration of Topology Optimisation and Design Variants Selection for Additive Manufacturing-Based Systematic Product Redesign
Authors: Dalpadulo Enrico , Gherardini Francesco , Pini Fabio , Leali Francesco
Published: November 2020

The development of additive manufacturing allows the transformation of technological processes and the redesign of products. Among the most used methods to support additive manufacturing, the design can be optimised through the integration of topology optimisation techniques, allowing for creating complex shapes. However, there are critical issues (i.e., definition of product and process parameters, selection of redesign variants, optimised designs interpretation, file exchange and data management, etc.) in identifying the most appropriate process and set-ups, as well as in selecting the best variant on a functional and morphological level. Therefore, to fully exploit the technological potentials and overcome the drawbacks, this paper proposes a systematic redesign approach based on additive manufacturing technologies that integrate topology optimisation and a tool for selecting design variants based on the optimisation of both product and process features. The method leads to the objective selection of the best redesigned configuration in accordance with the key performance indicators (KPIs) (i.e., functional and production requirements). As a case study, the redesign of a medical assistive device is proposed, previously developed in fused filament fabrication and now optimised for being 3D printed with selective laser melting.
An Overview of GIS-Based Assessment and Mapping of Mining-Induced Subsidence
Authors: Suh Jangwon
Published: November 2020

This article reviews numerous published studies on geographic information system (GIS)-based assessment and mapping of mining-induced subsidence. The various types of mine subsidence maps were first classified into susceptibility, hazard, and risk maps according to the various types of the engineering geology maps. Subsequently, the mapping studies were also reclassified into several groups according to the analytic methods used in the correlation derivation or elements of the risk of interest. Data uncertainty, analytic methods and techniques, and usability of the prediction map were considered in the discussion of the limitations and future perspectives of mining subsidence zonation studies. Because GIS can process geospatial data in relation to mining subsidence, the application and feasibility of exploiting GIS-assisted geospatial predictive mapping may be expanded further. GIS-based subsidence predictive maps are helpful for both engineers and for planners responsible for the design and implementation of risk mitigation and management strategies in mining areas.
Mechanism and Characteristics of Global Varying Compliance Parametric Resonances in a Ball Bearing
Authors: Zhang Zhiyong , Sattel Thomas , Zhu Yujie , Li Xuan , Dong Yawei , Rui Xiaoting
Published: November 2020

Varying compliance (VC) is an unavoidable form of parametric excitation in rolling bearings and can affect the stability and safety of the bearing and its supporting rotor system. To date, we have investigated VC primary resonance in ball bearings, and in this paper other parametric VC resonance types are addressed. For a classical ball bearing model with Hertzian contact and clearance nonlinearities between the rolling elements and raceway, the harmonic balance and alternating frequency/time domain (HB–AFT) method and Floquet theory are adopted to analyze the VC parametric resonances and their stabilities. It is found that the 1/2-order subharmonic resonances, 2-order superharmonic resonances, and various VC combination resonances, such as the 1-order and 2-order summed types, can be excited, thus resulting in period-1, period-2, period-4, period-8, period-35, quasi-period, and even chaotic VC motions in the system. Furthermore, the bifurcation and hysteresis characteristics of complex VC resonant responses are discussed, in which cyclic fold, period doubling, and the second Hopf bifurcation can occur. Finally, the global involution of VC resonances around bearing clearance-free operations (i.e., adjusting the bearing clearance to zero or one with low interference) are provided. The overall results extend the investigation of VC parametric resonance cases in rolling bearings.
Interaction between Polyphenolic Antioxidants and Saccharomyces cerevisiae Cells Defective in Heavy Metal Transport across the Plasma Membrane
Authors: Ruta Lavinia Liliana , Farcasanu Ileana Cornelia
Published: November 2020

Natural polyphenols are compounds with important biological implications which include antioxidant and metal-chelating characteristics relevant for their antimicrobial, antitumor, or antiaging potential. The mechanisms linking polyphenols and heavy metals in their concerted actions on cells are not completely elucidated. In this study, we used the model eukaryotic microorganism Saccharomyces cerevisiae to detect the action of widely prevalent natural polyphenols on yeast cells defective in the main components involved in essential heavy metal transport across the plasma membrane. We found that caffeic and gallic acids interfered with Zn accumulation, causing delays in cell growth that were alleviated by Zn supplementation. The flavones morin and quercetin interfered with both Mn and Zn accumulation, which resulted in growth improvement, but supplemental Mn and especially Zn turned the initially benefic action of morin and quercetin into potential toxicity. Our results imply that caution is needed when administering food supplements or nutraceuticals which contain both natural polyphenols and essential elements, especially zinc.
Poziotinib Inhibits the Efflux Activity of the ABCB1 and ABCG2 Transporters and the Expression of the ABCG2 Transporter Protein in Multidrug Resistant Colon Cancer Cells
Authors: Zhang Yongchao , Wu Zhuo-Xun , Yang Yuqi , Wang Jing-Quan , Li Jun , Sun Zoey , Teng Qiu-Xu , Ashby Charles R. , Yang Dong-Hua
Published: November 2020

Colorectal cancer (CRC) is a leading cause of cancer deaths in the United States. Currently, chemotherapy is a first-line treatment for CRC. However, one major drawback of chemotherapy is the emergence of multidrug resistance (MDR). It has been well-established that the overexpression of the ABCB1 and/or ABCG2 transporters can produce MDR in cancer cells. In this study, we report that in vitro, poziotinib can antagonize both ABCB1- and ABCG2-mediated MDR at 0.1–0.6 μM in the human colon cancer cell lines, SW620/Ad300 and S1-M1-80. Mechanistic studies indicated that poziotinib increases the intracellular accumulation of the ABCB1 transporter substrates, paclitaxel and doxorubicin, and the ABCG2 transporter substrates, mitoxantrone and SN-38, by inhibiting their substrate efflux function. Accumulation assay results suggested that poziotinib binds reversibly to the ABCG2 and ABCB1 transporter. Furthermore, western blot experiments indicated that poziotinib, at 0.6 μM, significantly downregulates the expression of the ABCG2 but not the ABCB1 transporter protein, suggesting that the ABCG2 reversal effect produced by poziotinib is due to transporter downregulation and inhibition of substrate efflux. Poziotinib concentration-dependently stimulated the ATPase activity of both ABCB1 and ABCG2, with EC50 values of 0.02 μM and 0.21 μM, respectively, suggesting that it interacts with the drug-substrate binding site. Molecular docking analysis indicated that poziotinib binds to the ABCB1 (−6.6 kcal/mol) and ABCG2 (−10.1 kcal/mol) drug-substrate binding site. In summary, our novel results show that poziotinib interacts with the ABCB1 and ABCG2 transporter, suggesting that poziotinib may increase the efficacy of certain chemotherapeutic drugs used in treating MDR CRC.
Selective Oxidation of Citronellol over Titanosilicate Catalysts
Authors: Aldhayan Daifallah , Kalíková Květa , Shaik Mohammed Rafi , Siddiqui Mohammed Rafiq H. , Přech Jan
Published: November 2020

Citronellol is one of the most widely used fragrances for bouquetting purposes and it is a starting material for synthesis of several other terpenoids. Nevertheless, few data have been reported on citronellol selective oxidation. Accordingly, we report our findings on the selective oxidation of citronellol with hydrogen peroxide using a set of titanosilicate catalysts with different morphologies and textural properties—conventional titanium silicalite 1 (TS-1), mesoporous TS-1, layered TS-1 and silica-titania pillared TS-1 and also studying the effect of the solvent used. Epoxidation of C6=C7 double bond was the main primary reaction in this system and trace signals of C5 allylic oxidation products were observed without formation of citronellal. Due to the presence of post-synthesis introduced additional Ti sites, the silica-titania pillared TS-1 (TS-1-PITi) provided the highest conversion among the tested catalysts; nevertheless, citronellol was oxidized over all the studied catalysts including conventional TS-1; therefore, showing that it penetrates even into MFI micropores (0.55 nm in diameter). When using acetonitrile as a solvent, the conversion was proportional to the titanium content of the catalyst. When studying the effect of the solvent, acetonitrile provided the highest epoxide selectivity (55%) while in methanol, 2-propanol and 1,4-dioxane, ring opening reactions caused epoxide decomposition.
The Mimic Enzyme Properties of Au@PtNRs and the Detection for Ascorbic Acid Based on Their Catalytic Properties
Authors: Gan Hao , Han Wenzhao , Liu Jiadi , Qi Juntian , Li Hui , Wang Liping
Published: November 2020

Being superior to natural enzymes, nanoenzymes are drawing a great deal of attention in the field of biosensing. Herein, we developed an ultrasensitive, stable and selective colorimetric assay having dual functionalities of Au-tipped Pt nanorods (NRs). The optical and catalytic properties of Au-tipped Pt NRs were monitored using a spectrophotometer and the chromogenic substrate 3, 3′, 5, 5′-tetramethylbenzidine (TMB) in the presence of H2O2, respectively. We found that Au-tipped Pt NRs exhibited excellent peroxidase-like activity, which decomposed hydrogen peroxide (H2O2) into oxygen (O2). The produced O2 oxidized the chromogenic substrate into a blue color product. The oxidation rate of the chromogenic substrate could be monitored using a spectrophotometer at 652 nm. Notably, the peroxidase-like activity of Au-tipped Pt NRs decreased in the presence of ascorbic acid (AA). The produced O2 preferentially reacted with AA, generating ascorbyl radicals (AA·) instead of oxidizing TMB, and thereby decreased the oxidation rate of TMB. Based on this inhibitory property, a selective colorimetric assay was developed using Au-tipped Pt NRs for the detection of AA. This work offers a novel detection method for AA.
Acetonitrile’s Effect on the Efficiency of Ethanol Electrooxidation at a Polycrystalline Pt Electrode in Relation to pH-Dependent Fuel Cell Applications
Authors: Pierożynski Bogusław , Mikołajczyk Tomasz , Łuba Mateusz , Wojtacha Paweł , Smoczyński Lech
Published: November 2020

The present paper reports cyclic voltammetric and a.c. impedance spectroscopy investigations on the influence of the acetonitrile concentration on the kinetics (and individual product’s efficiency) of the ethanol oxidation reaction (EOR), performed on a polycrystalline Pt electrode surface in 0.5 M H2SO4 and 0.1 M NaOH supporting solutions. The kinetics of the EOR were examined at room temperature over the voltammetric potential range, which covers the electrooxidation of surface-adsorbed COAds species, as well as the formation of acetaldehyde molecules. In addition, the time-dependent efficiency of acetate and acetaldehyde formation in relation to the initial acetonitrile content for both acidic and alkaline electrolytes was evaluated by means of spectrophotometric Ultraviolet/ Visible Spectroscopy (UV-VIS) instrumental analysis.
Functional Characterization of the N-Acetylmuramyl-l-Alanine Amidase, Ami1, from Mycobacterium abscessus
Authors: Küssau Tanja , Van Wyk Niël , Johansen Matt D. , Alsarraf Husam M. A. B. , Neyret Aymeric , Hamela Claire , Sørensen Kasper K. , Thygesen Mikkel B. , Beauvineau Claire , Kremer Laurent , Blaise Mickaël
Published: November 2020

Peptidoglycan (PG) is made of a polymer of disaccharides organized as a three-dimensional mesh-like network connected together by peptidic cross-links. PG is a dynamic structure that is essential for resistance to environmental stressors. Remodeling of PG occurs throughout the bacterial life cycle, particularly during bacterial division and separation into daughter cells. Numerous autolysins with various substrate specificities participate in PG remodeling. Expression of these enzymes must be tightly regulated, as an excess of hydrolytic activity can be detrimental for the bacteria. In non-tuberculous mycobacteria such as Mycobacterium abscessus, the function of PG-modifying enzymes has been poorly investigated. In this study, we characterized the function of the PG amidase, Ami1 from M. abscessus. An ami1 deletion mutant was generated and the phenotypes of the mutant were evaluated with respect to susceptibility to antibiotics and virulence in human macrophages and zebrafish. The capacity of purified Ami1 to hydrolyze muramyl-dipeptide was demonstrated in vitro. In addition, the screening of a 9200 compounds library led to the selection of three compounds inhibiting Ami1 in vitro. We also report the structural characterization of Ami1 which, combined with in silico docking studies, allows us to propose a mode of action for these inhibitors.
Amyotrophic Lateral Sclerosis and Autophagy: Dysfunction and Therapeutic Targeting
Authors: Amin Azin , Perera Nirma D. , Beart Philip M. , Turner Bradley J. , Shabanpoor Fazel
Published: November 2020

Over the past 20 years, there has been a drastically increased understanding of the genetic basis of Amyotrophic Lateral Sclerosis. Despite the identification of more than 40 different ALS-causing mutations, the accumulation of neurotoxic misfolded proteins, inclusions, and aggregates within motor neurons is the main pathological hallmark in all cases of ALS. These protein aggregates are proposed to disrupt cellular processes and ultimately result in neurodegeneration. One of the main reasons implicated in the accumulation of protein aggregates may be defective autophagy, a highly conserved intracellular “clearance” system delivering misfolded proteins, aggregates, and damaged organelles to lysosomes for degradation. Autophagy is one of the primary stress response mechanisms activated in highly sensitive and specialised neurons following insult to ensure their survival. The upregulation of autophagy through pharmacological autophagy-inducing agents has largely been shown to reduce intracellular protein aggregate levels and disease phenotypes in different in vitro and in vivo models of neurodegenerative diseases. In this review, we explore the intriguing interface between ALS and autophagy, provide a most comprehensive summary of autophagy-targeted drugs that have been examined or are being developed as potential treatments for ALS to date, and discuss potential therapeutic strategies for targeting autophagy in ALS.
An Overview of Astrocyte Responses in Genetically Induced Alzheimer’s Disease Mouse Models
Authors: Spanos Fokion , Liddelow Shane A.
Published: November 2020

Alzheimer’s disease (AD) is the most common form of dementia. Despite many years of intense research, there is currently still no effective treatment. Multiple cell types contribute to disease pathogenesis, with an increasing body of data pointing to the active participation of astrocytes. Astrocytes play a pivotal role in the physiology and metabolic functions of neurons and other cells in the central nervous system. Because of their interactions with other cell types, astrocyte functions must be understood in their biologic context, thus many studies have used mouse models, of which there are over 190 available for AD research. However, none appear able to fully recapitulate the many functional changes in astrocytes reported in human AD brains. Our review summarizes the observations of astrocyte biology noted in mouse models of familial and sporadic AD. The limitations of AD mouse models will be discussed and current attempts to overcome these disadvantages will be described. With increasing understanding of the non-neuronal contributions to disease, the development of new methods and models will provide further insights and address important questions regarding the roles of astrocytes and other non-neuronal cells in AD pathophysiology. The next decade will prove to be full of exciting opportunities to address this devastating disease.
DFO@EVOH and 3,4-HP@EVOH: Towards New Polymeric Sorbents for Iron(III)
Authors: Alberti Giancarla , Zanoni Camilla , Magnaghi Lisa Rita , Santos Maria Amélia , Nurchi Valeria Marina , Biesuz Raffaela
Published: November 2020

The paper presents the synthesis and preliminary characterization of two novel solid-phase sorbents for iron(III), resulting from the functionalization of ethylene-vinyl alcohol copolymer (EVOH) with deferoxamine, DFO (DFO@EVOH), and a novel tripodal 3-hydroxy-4-pyridinone, named 3,4-HP (3,4-HP@EVOH). DFO and 3,4-HP have been covalently bonded to EVOH, using carbonyldiimidazole as a coupling agent. Before their use as Fe(III) sorbents, they were warm-pressed to obtain a thin film. Polymers have been characterized by conventional physico-chemical techniques; furthermore, the sorption properties towards Fe(III) were investigated. The physico-chemical characterization of the new solid-state devices demonstrates the effective linkage of the two receptors on the polymeric support. Despite a relatively low sorption capacity for both materials, the stoichiometry and the complexation constants of Fe(III)/DFO@EVOH and Fe(III)/3,4-HP@EVOH are in pretty good agreement with those obtained for the same ligands in aqueous solutions.
Sensing and Interaction of His-Tagged CA19-9 Antigen with Graphene-Modified Electrodes
Authors: Mic Mihaela , Varodi Codruta , Pogacean Florina , Socaci Crina , Coros Maria , Stefan-van Staden Raluca-Ioana , Pruneanu Stela
Published: November 2020

The electrochemical oxidation of CA19-9 tagged with L-Histidine (CA199-His) was investigated for the first time with screen-printed electrodes (DS) modified with graphene oxide (DS/GO) or thermally reduced graphene oxide (DS/TRGO). Successive cyclic voltammograms (CV) measurements performed with bare and DS/TRGO electrodes proved that the intensity of the oxidation peak (I peak) is time-dependent. In fact, the oxidation signal increased over time, reached a maximum and then decreased due to the saturation of the surface with CA199-His molecules. The interaction of CA199-His with GO, TRGO, or graphite was additionally studied by isothermal calorimetry, a useful tool for accessing information regarding the biomolecule adsorption on graphene surface. The adsorption of CA199-His on TRGO was generating a higher heat, suggesting quantitative and efficient interactions. At the same time, in the case of TRGO, the saturation was not reached, indicating the existence of more free binding sites than in the case of GO and graphite. As such, the carbohydrate marker CA199-His showed a higher affinity for the TRGO surface than for the graphite or GO surfaces. The lack of saturation in the case of TRGO may indicate a continuous structural modification of the antigen when interacting with the graphene surface.
Global-Scale Synchronization in the Meteorological Data: A Vectorial Analysis That Includes Higher-Order Differences
Authors: Hayata Kazuya
Published: November 2020

To examine the evidence of global warming, in recent years, there has been a growing interest in the statistical analysis of time-dependent meteorological data. In this paper, for 116 observational stations in the world, sequential variations of the monthly distributions of meteorological data are analyzed vectorially. For specific monthly data, temperatures and precipitations are chosen, both of which are averaged over three decades. Climate change can be revealed through the intersecting angle between two 33-dimensional vectors being composed with monthly mean values. Subsequently, the angle data for the entire stations are analyzed statistically and compared between the former (1931–1980) and the latter (1951–2010) periods. Irrespective of the period and the hemisphere, the variation of the angles is found to show the exponential growth as a function of their latitudes. Furthermore, consistent with other studies, this trend is shown to become stronger in the latter period, indicating that the so-called snow/ice-albedo feedback occurs. In contrast to the temperatures, for the precipitations, no significant correlation is found between the angle and the latitude. To examine the albedo effect in more detail, a regional analysis for 75 stations in Japan is carried out as well. Numerical results show that the effect is significant even for the relatively narrow latitudinal range (19%) of the hemisphere. Finally, a synchronization of the monthly patterns of temperatures is given between the northern district of Japan and both North America and Eastern Europe.
Investigation of Weld Zone and Fracture Surface of Friction Stir Lap Welded 5052 Aluminum Alloy and 304 Stainless Steel Joints
Authors: Chitturi Veerendra , Pedapati Srinivasa Rao , Awang Mokhtar
Published: November 2020

Dissimilar material joining of aluminum and steel in the present scenario is an important criterion in the manufacturing industry, especially because of their low weight and technical performance. In the present investigation, AA5052 and SS304 are friction stir welded in lap configuration with different tilt angles, welding speed, pin depth, and tool rotational speed, with aluminum as the top plate. A maximum of 3.16 kN shear strength was achieved at 2.5° tilt angle when the penetration depth was 4.3 mm. The shear strength samples were studied for fracture analysis and it was found that fracture of the samples mainly occurred on the aluminum side and the fracture demonstrated both brittle and ductile failure, consisting of quasi-cleavage, trans-granular, and intergranular fracture areas. Field emission scanning electron microscope images at the interfacial region of the weld show that different intermetallic compounds were formed at various zones of the joint with respect to the change in process parameters. It was observed from energy dispersive spectroscopy that Al-rich intermetallic compounds were formed at the interfacial region of the welded samples. Amongst the process parameters, change in the tilt angle affected the weld zone significantly. The thickness of the intermetallic compound (IMC) layer formed with 800 and 1000 rpm at 2.5° tilt angle was between 2.5 and 3 μm, which resulted in achieving better joint strength. AlFe, AlFe3, Al13Fe4, and Al5Fe2 were the different intermetallic compounds detected using X-ray diffraction with different process parameters. The hardness of the samples ranged between (300 and 630) HV, which further supports the formation of AlFe and AlFe3 intermetallic compounds.
An Optimal Stacked Ensemble Deep Learning Model for Predicting Time-Series Data Using a Genetic Algorithm—An Application for Aerosol Particle Number Concentrations
Authors: Surakhi Ola M. , Zaidan Martha Arbayani , Serhan Sami , Salah Imad , Hussein Tareq
Published: November 2020

Time-series prediction is an important area that inspires numerous research disciplines for various applications, including air quality databases. Developing a robust and accurate model for time-series data becomes a challenging task, because it involves training different models and optimization. In this paper, we proposed and tested three machine learning techniques—recurrent neural networks (RNN), heuristic algorithm and ensemble learning—to develop a predictive model for estimating atmospheric particle number concentrations in the form of a time-series database. Here, the RNN included three variants—Long-Short Term Memory, Gated Recurrent Network, and Bi-directional Recurrent Neural Network—with various configurations. A Genetic Algorithm (GA) was then used to find the optimal time-lag in order to enhance the model’s performance. The optimized models were used to construct a stacked ensemble model as well as to perform the final prediction. The results demonstrated that the time-lag value can be optimized by using the heuristic algorithm; consequently, this improved the model prediction accuracy. Further improvement can be achieved by using ensemble learning that combines several models for better performance and more accurate predictions.