bluuebunny/crossref_metadata_2025 huggingface dataset:
Forgetting Rates on the Recency Portion of a Word List Predict Conversion from Mild Cognitive Impairment to Alzheimer’s Disease
Authors: Turchetta Chiara Stella , De Simone Maria Stefania , Perri Roberta , Fadda Lucia , Caruso Giulia , De Tollis Massimo , Caltagirone Carlo , Carlesimo Giovanni Augusto
Published: February 2020

Amnestic mild cognitive impairment has a greater risk of progressing to Alzheimer’s disease (AD). Consistent with AD patients’ distinctive deficit in consolidating new memory traces, in a recent study we demonstrated that the forgetting rate on the recency portion of a word list differentiates AD from other forms of dementia. In line with this finding, the aim of this study was to investigate whether increased recency forgetting could be a reliable index for predicting amnestic mild cognitive impairment (MCI) patients’ conversion to AD. For this purpose, we compared accuracy in immediate and delayed recall from different portions of a word list in a group of patients with amnestic MCI who converted (C-MCI) or did not convert (S-MCI) to AD during a three-year follow-up period and in a group of normal controls. The results of the present study show that the forgetting from the recency portion of the list (operationalized as a ratio between immediate and delayed recall) was significantly larger in C-MCI than in S-MCI patients. Consistently, the hierarchical logistic regression analyses demonstrated that the recency ratio is a strong predictor of group membership. Similar to what occurs in full-blown AD patients, the results of our study suggest that the increased forgetting rate from the recency portion of the list in C-MCI patients is due to severely reduced efficiency in converting transitory short-term memory representations into stable long-term memory traces. This is consistent with prominent involvement of neuropathological changes in the cortical areas of the medial-temporal lobes and suggests that the recency ratio is a cognitive marker able to identify MCI patients who have a greater likelihood of progressing to AD.
An improved neural network for domain adaptive Chinese word segmentation
Authors: Jiang Ming , Huang Tao , Zhang Min , Tang Jingfan , Liu Zhiyong
Published: February 2020

Various methods have been proposed recently to solve the problem of weak domain adaptability of Chinese word segmentation (CWS) models based on neural networks. However, although some of these improved models achieve high segmentation accuracy in a specific domain, they need to be retrained when applied to another. After rethinking the domain adaptability, two criteria, including the segmentation accuracy and the universality, are suggested for measuring it. Taking the above two criteria into consideration, an improved neural-based CWS model is proposed, which incorporates the common lexicon and unlabeled data into BERT. To make the most use of lexicon, a new method is proposed to construct the lexicon-based feature vector. In addition, the domain-specific words can be effectively extracted by pre-training a language model on the unlabeled data. Finally, a GRU-like gate structure is used to integrate the lexicon-based feature vector and language model into BERT. Experiments on five different domains reveal that the domain adaptability of this model is very strong.
Chinese shallow semantic parsing based on multilevel linguistic clues
Authors: Wan Fucheng , Yang Fangtao , Wu Tiantian , Zhang Dongjiao , Zhang Lei , Wang Yicheng
Published: February 2020

With rapid development of artificial intelligence and Chinese information processing technology, research related to natural language processing have reached the level of semantic understanding gradually, while Chinese Shallow Semantic Parsing is the key technique in the semantic understanding field. In this paper, a further improvement is conducted on the basic model of Chinese semantic role labeling for linear classification based on conditional random fields. In this paper, a method of combination of linguistic clues, combining with the existing linear sequence labeling algorithm and integrating some multilevel linguistic clues, such as morphology is related to syntax, in the model training to reconstruct and improve the Chinese semantic role labeling model of linear sequence. Through the experimental comparison and linguistic assistant analysis, this paper puts forward a targeted improvement method to significantly improve the accuracy of model labeling and proves that the integration of related linguistic clues in the semantic role labeling model based on linear sequence can improve the effect of model labeling.
Improved algorithm of Context Graph based on feature selection
Authors: Liu Wei , Zhao Jian , Yang Yongji
Published: February 2020

In order to solve the problem of low efficiency of traditional theme crawlers in searching theme pages, the crawling algorithm based on Context Graph was discussed. After analyzing the working principle and process of the algorithm, we introduced a new algorithm idea named feature selection algorithm. This new algorithm improved the original TF-IDF formula accordingly and solved the algorithm problems.
Os nazistas eram de esquerda?
Authors: Ruzza Antonio
Published: February 2020

O presente artigo tem o objetivo de argumentar contra a afirmação feita por alguns representantes ideológicos do governo brasileiro de que o nazismo foi um fenômeno de esquerda, porque no seu partido aparecia o nome “socialista” e ele fazia largo uso da violência. Como entendem a totalidade de historiadores sérios, o nazismo deve ser enquadrado na extrema direita, por uma série de motivos: o significado oposto dado ao nome “socialismo”; a intenção declarada de acabar com o marxismo; a chegada ao poder com o apoio das elites conservadoras e liberais, além das autoridades eclesiásticas; a propaganda anticapitalista nunca executada; a luta contra o Modernismo; a rejeição dos valores do Iluminismo e da Revolução Francesa, em particular a igualdade; uma política centrada no racismo e na superioridade alemã; o nacionalismo de dominação; o desprezo pela vida na cidade; o papel inferior reservado às mulheres; a capacidade demagógica de apropriar-se das insatisfações e ressentimentos populares (populismo). Entendemos que todos esses elementos não fazem parte da ideologia esquerdista.
SILÊNCIO: A CENSURA DE INFORMAÇÕES NA DITADURA MILITAR DO BRASIL
Authors: Palhares Maria Cristina , Galvão Michell Silva
Published: February 2020

O presente artigo analisa o romance Zero, de Ignácio de Loyola Brandão, como uma das obras que surgiram com o intuito de denunciar o que ocorria no regime militar. Neste sentido, verifica-se o conteúdo informacional em relação ao potencial de instigação do indivíduo à reflexão sobre seu meio e, assim, (re)significá-lo e como os mecanismos atuais de censura tornam-se empecilho ao acesso à informação para parte da sociedade. Autores, como Bobbio, Bastos da Cunha, Cavalcanti, Eco, Howe, Lajolo e Gaspari, apoiam este texto, visando à compreensão do presente por meio de uma parte do passado contida na obra analisada.
O modo de relação do surdo com a língua materna e língua escrita.
Authors: BIZIO LUCIMAR
Published: February 2020

 

 

Este artigo tece considerações sobre a aquisição da língua materna, pelo surdo, e sobre como esta questão foi e tem sido tratada teoricamente até aqui. Para encaminhar a reflexão sobre o tema em questão foi necessário desnaturalizar termos que circulam livremente no campo dos estudos sobre a surdez. Entre eles, destaca-se o de língua materna, L1 e L2, uma vez que, na abordagem bilinguista, entende-se a Língua de Sinais como L1, enquanto a escrita do português é considerada como segunda língua – L.2. Alguns autores foram selecionados para falar sobre o assunto. Foram abordadas as possibilidades de contribuição do diálogo com a Linguística e também com a Psicanálise, com vistas a considerar a singularidade do surdo. Neste trabalho está em questão a relação singular da pessoa surda com a linguagem, que movimentou as discussões sobre a língua materna do surdo, o que é L1 e L2.

 

 

Palavras-chave: escrita do surdo, língua materna, primeira língua, segunda língua.
WACANA KRITIS PADA IKLAN PROVIDER TAHUN 2018
Authors: Insani Harninda Rizka , Anggraini Nori , Purawinangun Ira Anisa
Published: February 2020

Abstrak Penelitian ini bertujuan untuk mengetahui struktur mikro dalam analisis wacana kritis pada iklan provider pada tahun 2018 melalui model analisis wacana kritis Teun A. van Dijk pada aspek semantik dan sintaksis. Penelitian ini menggunakan metode penelitian analisis isi yang diterapkan terhadap sebuah wacana iklan dengan menggunakan pendekatan kualitatif. Teknik pengambilan data dengan cara simak dan catat. Peneliti menyimak rekaman video iklan provider dan mencatat tuturan yang disampaikan di dalam iklan provider. Teknik analisis data menggunakan tiga tahap yaitu reduksi data, penyajian data dan penarikan simpulan. Tahap reduksi data peneliti menganalisis pada struktur mikro pada iklan provider tahun 2018.Hasil penelitian menunjukkan temuan elemen semantik diantaranya pada elemen latar terdapat 3 temuan, detil sebanyak 1 temuan, maksud terdapat 2 temuan, dan praanggapan sebanyak 2 temuan., pengingkaran 2 temuan, dan kata ganti sebanyak 2 temuan. Kata kunci: wacana kritis, iklan provider
TINDAK TUTUR DIREKTIF DALAM NOVEL SUSAH SINYAL KARYA IKA NATASSA & ERNEST PRAKASA (KAJIAN PRAGMATIK)
Authors: Murti Aska Rizkia , Nurhuda Zamzam
Published: February 2020

AbstrakPenelitian ini bertujuan untuk (1) mendeskripsikan fungsi-fungsi tindak tutur direktif dalam dialog novel Susah Sinyal karya Ika Natassa dan Ernest Prakasa. (2) mendeskripsikan modus kalimat pada tindak tutur direktif dalam dialog novel Susah Sinyal karya Ika Natassa dan Ernest Prakasa. Penelitian ini menggunakan metode penelitian deskriptif kualitatif. Objek yang diteliti dalam penelitian ini adalah tuturan yang terdapat dalam novel Susah Sinyal karya Ika Natassa dan Ernest Prakasa. Data yang ditemukan berjumlah 40 data yang diperoleh dengan menggunakan teknik baca dan catat dalam teknik pengumpulan data. Berdasarkan analisis data yang diperoleh, dapat diberi kesimpulan: (1) Fungsi tindak tutur direktif yang ditemukan dalam novel Susah Sinyal karya Ika Natassa dan Ernest Prakasa yaitu fungsi meminta 2 data, memohon 1 data, mengajak 4 data, bertanya 24 data, memerintah 1 data, menuntut 2 data, melarang 2 data, membolehkan 1 data, memaafkan 1 data, menasehatkan 1 data, mengusulkan dan menyarankan 1 data. (2) Modus kalimat pada tindak tutur direktif yang ditemukan dalam novel Susah Sinyal karya Ika Natassa dan Ernest Prakasa yaitu modus kalimat berita, tanya, perintah dan kalimat tanya & perintah. Data yang mengandung modus kalimat tersebut antara lain yaitu kalimat berita 11 data, kalimat tanya 25 data, kalimat perintah 1 data dan kalimat tanya & perintah 3 data.  Kata kunci:    Fungsi dan modus kalimat pada tindak tutur direktif, Pragmatik, novel Susah Sinyal.
Disfungsi Mitokondria pada Gagal Jantung Akut
Authors: Ilhami Yose Ramda
Published: February 2020

Mitokondria merupakan organel penting yang bermanfaat dalam homeostasis tubuh tidak hanya pada pembentukan ATP saja tetapi juga memiliki fungsi lain seperti mengatur pensinyalan sel dengan memodulasi keadaan redoks, memberikan cofactor untuk reaksi biokimia dan menghasilkan ligand untuk transduksi sinyal. Pada keadaan gagal jantung terjadi gangguan mitokondria yang diakibatkan oleh berbagai mekanisme meliputi hiperasetilasi protein, gangguan homeostasis kalsium, pembentukan spesies oksigen reaktif dan peningkatan respons inflamasi.
Analysis of Blood Donor Deferral in a Tertiary Care Hospital
Authors: Parvin Farida , Biswas Daanish Arefin , Naznin Bepasha , Afroz Tamanna , Ali Mohammad , Dipta Tashmim Farhana
Published: February 2020

Introduction: Selection of proper donor according to stringent selection criteria is the prerequisite for safe blood transfusion practice. It is widely known that a large number of blood donors are deferred for different reasons.

Objective: The aim of present study is to evaluate the incidence and different reasons of blood donor deferral in atertiary care hospital.

Methodology: This retrospective cross-sectional study was carried out in Transfusion Medicine and Clinical Haematology Department of BIRDEM General Hospital, Dhaka, during the period from July 2016 to June 2017.The blood donor of either sex attending the mentioned department were selected purposively and categorized into four groups according to their age for this study. Donors were selected and deferred by medical officer according to national guideline. Deferred blood donors were recorded in register book and were analyzed retrospectively.

Results: In current study, 1152 blood donor (8.8%) were deferred attending for allogeneic blood donation during the study period. Out of 13082 registered blood donor 11961were male (91.43%) and 1121 were female (8.57%) and deferral rate was 2.37 times more in female. Majority of the deferred donors (55.38%) were under the age of 40 where 26.82% were in between 40-49 years and 17.8% were in the range of 50 years and above. Age range of highest deferred donors (32.20%) was between 30-39 years. The number of temporary and permanent deferral were 836 (72.57 %) and 316 (27.43%) respectively. Anaemia (33.01%), underweight (21.53%) and hypotension (17.34%) were the most common reason of temporary deferral. Chronic uncontrolled hypertension (42.4%), donors with medication (16.77%) and asthma (15.18%) was the most common cause of permanent deferral.

Conclusion: The deferral rate was low and most of the deferred donors were young adult. Temporary deferred donors were higher than permanent deferred donors. The most common reasons for temporary deferral were anemia, underweight and hypotension. Permanent deferral causes were chronic uncontrolled hypertension, donors on medication for various reason and asthma. Donors should be informed with a clear message on their deferral status. It is important to determine the rate and causes of donor deferral for the safety of blood transfusion and to guide the recruitment efforts for safe blood transfusion and to avoid the permanent loss of blood donors.

Northern International Medical College Journal Vol.10 (2) Jan 2019: 373-376
GÜNCEL YARGI KARARLARI IŞIĞINDA TAM YARGI DAVALARINDA TAZMİNATIN İRAT ŞEKLİNDE BELİRLENMESİ
Authors: ASKER Serkan
Published: February 2020

İdarenin işlem ya da eylemleri nedeniyle
kişilerin uğramış olduğu zararlardan idarenin sorumluluğu halinde bu zararların
tazmini tam yargı davaları ile mümkün olmaktadır. Tam yargı davalarında
hükmedilecek tazminatın ödenme şeklinin belirlenmesi hususunda İdari Yargılama
Usulü Kanunu’nda özel bir hüküm bulunmayıp, Türk Borçlar Kanunu'nda
hüküm altına alınacak tazminatın ödenme şeklini belirlemenin hakimin yetkisi
dahilinde olduğu kurala bağlanmıştır. Bununla birlikte, uygulamada mahkemeler
bu yetkilerini tazminatın sermaye şeklinde (bir diğer ifadeyle toptan)
belirlenmesi yolunda kullanmış, tazminatın irat (belirli dönemler halinde kısım
kısım ödenmesi) şeklinde belirlenmesi yöntemi ise birkaç örnekle sınırlı
kalmıştır. Uygulama bu şekilde devam etmekte iken, Danıştay bakım
ücretinden/bakıcı giderinden doğan maddi tazminat istemlerinde tazminatın
sermaye şeklinde değil, irat şeklinde dönemsel olarak belirlenmesi gerektiğine
karar vermiştir. Tazminatın sermaye şeklinde belirlenmesi yolunda yerleşmiş
uygulama, tam yargı davaları bakımından birçok idari yargı uygulamasının da bu
yönde yerleşmesine neden olmuştur. Bununla birlikte, tazminatın sermaye yerine
irat şeklinde belirlenmesi, tazminatın ödenmesi yöntemi, faiz uygulaması,
tazminattan indirim gibi sorunun maddi boyutunda köklü değişikliğe neden
olacağı gibi, bu davalarda uygulanacak olan hüküm sonucunun yazımı, yargılama
giderlerine hükmedilmesi gibi yargılama usulüne dair uygulamalarda da
değişikliğe sebep olacaktır. Verilen bu tür kararların istikrar kazandığı da
gözetildiğinde, ilerleyen dönemde idari yargı uygulamasında (en azından anılan
tazminat unsuru bakımından) bu konu üzerinde durulacağı anlaşılmaktadır. Bunun
yanında, esasen tam yargı davalarına yabancı olmakla birlikte tazminatın irat
şeklinde belirlenmesi yönteminin benimsenmesi halinde önem kazanacak olan
hükmedilecek tazminatın ekonomik değerinin kaybetmemesi için alınması gerekli
tedbirler üzerinde de durulmalıdır.
TÜRK HUKUK TARİHİ AÇISINDAN KUL SİSTEMİ
Authors: KARATAŞ Abdullah Vefa
Published: February 2020

Hukuk tarihi ilkeleri nazara alınarak yapılan
bu çalışmada, Osmanlı Devleti’nin önemli kurumlarından biri olarak kabul edilen
kul sistemi incelenmiştir. Çalışmada literatürden, şer’iyye sicil kayıtlarından,
mühimme defterlerinden ve Osmanlı dönemine ait Kanunnamelerden yararlanılmıştır.
Gerek Türk gerek yabancı literatürde “devşirme” konusunu içeren eserler bulunsa
da ortaya koyduğumuz çalışmada “kul sistemi” üzerinde durulmuş; meselenin
yalnızca askeri boyutu ve sonuçları değil, idari yönü ve etkileri de
incelenmiştir. Ayrıca sistemin ortaya çıkışından işleyişine, olumlu olumsuz
yönlerinden Osmanlı devleti için nasıl bir değere sahip olduğuna kadar kapsamlı
bir araştırma yapılmaya çalışılmıştır. Bunların dışında kul sisteminin İslam
hukukuna aykırı olup olmadığı “zimmilik” ve “kölelik” başlıkları altında
ayrıntılı olarak araştırılmış ve literatürdeki tezler incelenerek yeni bir
takım bulgular ortaya konulmuştur. Kul sistemi, Osmanlı ordu teşkilatı ve idari
örgütü içinde çok mühim bir yere sahiptir. Ancak sistemin İslam hukukuyla,
özellikle zimmilik anlaşması ile, örtüşmeyen tarafları olduğu görülebilmektedir.
Kul sisteminin bir kölelik modeli olmadığı; Osmanlı’ya has bir kurum olduğu anlaşılmaktadır.
Kulun bazı durumlarda köleden daha aşağı, bazı hallerde hür ile köle arasında
ve bazen hür bir vatandaştan daha üstün bir konumda bulunduğu ifade edilebilir.
Kul sistemi günümüzün değil; yürürlükte olduğu dönemin toplumsal ve hukuki
yapısı içerisinde değerlendirilmeye çalışılmıştır. İnsanı eğitme ve devlet
hizmetine sunma usulü olarak Osmanlı Devleti’nde uzun yıllar başvurulan kul
sisteminden hareketle bugün için söylenecek şudur: Yönetici kadrolara ve hatta
devlet kurumlarına alınacak görevlilerin seçiminde özenli ve titiz bir yöntemin
benimsenmesi gerekir ancak bunu yaparken hukuk sınırları içinde kalınmalı ve
çıkabilecek hak ihlalleri en az seviyeye indirilmelidir.
Infectious hematopoietic necrosis virus truncated G protein effect on survival, immune response, and disease resistance in rainbow trout
Authors: Hua X , Feng Y , Guan X , Wang Y , Zhou Y , Ren X , Li D , Gao S , Huang J , Guan X , Shi W , Liu M
Published: February 2020

The major antigenic protein of infectious hematopoietic necrosis virus (IHNV) is the surface glycoprotein G, which contains neutralizing epitopes that induce the production of immune neutralizing antibodies. In this study, the IHNV G gene sequence was truncated according to bioinformatics principles and then recombinantly expressed via an E. coli expression system. We then assessed the specific antibody immunoglobin M (IgM) levels of rainbow trout immunized with recombinant truncated G protein (emulsified with Freund’s incomplete adjuvant), and showed that antibody IgM levels of immunized fish were significantly higher than in the control group (p < 0.01). The mRNA expression levels of interferon 1 (IFN1) and interleukin-8 (IL-8) were also up-regulated significantly (p < 0.01) in head kidneys and spleens of rainbow trout immunized with recombinant truncated G protein. Also, after challenge with wild-type IHNV HLJ-09 virus on Day 28, rainbow trout immunized with recombinant truncated G protein showed cumulative survival rates of 60%. These results indicate that the truncated G protein of IHNV expressed by the E. coli prokaryotic expression system can be used as a candidate immunogen for an IHNV subunit vaccine, which lays a theoretical foundation for the study of further potential IHNV subunit vaccines.
Neural PD Controller for an Unmanned Aerial Vehicle Trained with Extended Kalman Filter
Authors: Gomez-Avila Javier , Villaseñor Carlos , Hernandez-Barragan Jesus , Arana-Daniel Nancy , Alanis Alma Y. , Lopez-Franco Carlos
Published: February 2020

Flying robots have gained great interest because of their numerous applications. For this reason, the control of Unmanned Aerial Vehicles (UAVs) is one of the most important challenges in mobile robotics. These kinds of robots are commonly controlled with Proportional-Integral-Derivative (PID) controllers; however, traditional linear controllers have limitations when controlling highly nonlinear and uncertain systems such as UAVs. In this paper, a control scheme for the pose of a quadrotor is presented. The scheme presented has the behavior of a PD controller and it is based on a Multilayer Perceptron trained with an Extended Kalman Filter. The Neural Network is trained online in order to ensure adaptation to changes in the presence of dynamics and uncertainties. The control scheme is tested in real time experiments in order to show its effectiveness.
Computer Modeling of Barrel-Vaulted Sanctuary Exhibiting Flutter Echo with Comparison to Measurements
Authors: Lai Heather , Hamilton Brian
Published: February 2020

Computer modeling in acoustics allows for the prediction of acoustical defects and the evaluation of potential remediations. In this article, computer modeling is applied to the case of a barrel-vaulted sanctuary whose architectural design and construction led to severe flutter echoes along the main aisle, which was later mitigated through acoustical remediations. State-of-the-art geometrical acoustics and wave-based simulations are carried out to analyze the acoustics of this space, with a particular focus on the flutter echoes along the main aisle, before and after remediations. Multi-resolution wavelet and spectrogram analyses are carried out to isolate and characterize flutter echoes within measurements and computer-simulated room impulse responses. Comparisons of simulated responses to measurements are also made in terms of decay times and curves. Simulated room impulse responses from both geometrical acoustics and wave-based methods show evidence of flutter echoes matching measurements, to varying degrees. Time-frequency analyses isolating flutter echoes demonstrate better matches to measurements from wave-based simulated responses, at the cost of longer simulation times than geometrical acoustics simulations. This case study highlights the importance of computer modeling of acoustics in early design phases of architectural planning of worship spaces.
Adoption of ICT-Based Information Sources and Market Participation among Smallholder Livestock Farmers in South Africa
Authors: Nwafor Christopher Ugochukwu , Ogundeji Abiodun A. , van der Westhuizen Carlu
Published: February 2020

The study explored the contribution of information and communication technology (ICT)-based information sources to market participation among smallholder livestock farmers. Use of ICTs is considered paramount for providing smallholder farmers with required market information, and also to reduce market asymmetries. A double hurdle regression was utilized to analyze data collected from 150 smallholder livestock farmers in the study area. The results show that while use of ICT-based market information sources significantly influenced market participation, the effect of using ICT-based information sources on the intensity of market participation was not significant. Other variables shown to influence both market participation and the intensity of market participation were age, additional income and membership of farmer cooperatives. This suggests the need to consider other associated factors in the application and design of interventions that utilize ICT-based information sources to achieve market engagement among smallholders.
Antimicrobial Usage and Resistance in Companion Animals: A Cross-Sectional Study in Three European Countries
Authors: Joosten Philip , Ceccarelli Daniela , Odent Evelien , Sarrazin Steven , Graveland Haitske , Van Gompel Liese , Battisti Antonio , Caprioli Andrea , Franco Alessia , Wagenaar Jaap A. , Mevius Dik , Dewulf Jeroen
Published: February 2020

Companion animals have been described as potential reservoirs of antimicrobial resistance (AMR), however data remain scarce. Therefore, the objectives were to describe antimicrobial usage (AMU) in dogs and cats in three European countries (Belgium, Italy, and The Netherlands) and to investigate phenotypic AMR. A questionnaire and one fecal sample per animal (n = 303) were collected over one year and AMU was quantified using treatment incidence (TI). Phenotypic resistance profiles of 282 Escherichia coli isolates were determined. Nineteen percent of the animals received at least one antimicrobial treatment six months preceding sampling. On average, cats and dogs were treated with a standard daily dose of antimicrobials for 1.8 and 3.3 days over one year, respectively. The most frequently used antimicrobial was amoxicillin-clavulanate (27%). Broad-spectrum antimicrobials and critically important antimicrobials for human medicine represented 83% and 71% of the total number of treatments, respectively. Resistance of E. coli to at least one antimicrobial agent was found in 27% of the isolates. The most common resistance was to ampicillin (18%). Thirteen percent was identified as multidrug resistant isolates. No association between AMU and AMR was found in the investigated samples. The issue to address, regarding AMU in companion animal, lies within the quality of use, not the quantity. Especially from a One-Health perspective, companion animals might be a source of transmission of resistance genes and/or resistant bacteria to humans.
Concerted Efforts Are Needed to Control and Mitigate Antibiotic Pollution in Coastal Waters of China
Authors: Xie Huaijun , Du Jing , Chen Jingwen
Published: February 2020

Antibiotics have been applied for decades and antibiotic pollution is of great concern due to the risk for promoting resistant genes. Human activities such as mariculture and land-based discharge can lead to the antibiotic pollution in coastal area and it is of importance to assess the pollution and risks of antibiotics in this area. In this mini-review, the pollution status of antibiotics in Chinese coastal waters is summarized and some perspectives are put forward for future efforts to mitigate the pollution.
Free Radical Research in Cancer
Authors: Čipak Gašparović Ana
Published: February 2020

It can be challenging to find efficient therapy for cancer due to its biological diversity [...]
Liposomal Resveratrol and/or Carvedilol Attenuate Doxorubicin-Induced Cardiotoxicity by Modulating Inflammation, Oxidative Stress and S100A1 in Rats
Authors: Alanazi Abeer M. , Fadda Laila , Alhusaini Ahlam , Ahmad Rehab , Hasan Iman H. , Mahmoud Ayman M.
Published: February 2020

Doxorubicin (DOX) is a cytotoxic anthracycline antibiotic and one of the important chemotherapeutic agents for different types of cancers. DOX treatment is associated with adverse effects, particularly cardiac dysfunction. This study examined the cardioprotective effects of carvedilol (CAR) and/or resveratrol (RES) and liposomal RES (LIPO-RES) against DOX-induced cardiomyopathy, pointing to their modulatory effect on oxidative stress, inflammation, S100A1 and sarco/endoplasmic reticulum calcium ATPase2a (SERCA2a). Rats received CAR (30 mg/kg) and/or RES (20 mg/kg) or LIPO-RES (20 mg/kg) for 6 weeks and were challenged with DOX (2 mg/kg) twice per week from week 2 to week 6. DOX-administered rats exhibited a significant increase in serum creatine kinase-MB (CK-MB), troponin-I and lactate dehydrogenase (LDH) along with histological alterations, reflecting cardiac cell injury. Cardiac toll-like receptor 4 (TLR-4), inducible nitric oxide synthase (iNOS), tumor necrosis factor (TNF)-α and interleukin (IL)-6 protein expression were up-regulated, and lipid peroxidation was increased in DOX-administered rats. Treatment with CAR, RES or LIPO-RES as well as their alternative combinations ameliorated all observed biochemical and histological alterations with the most potent effect exerted by CAR/LIPO-RES. All treatments increased cardiac antioxidants, and the expression of S100A1 and SERCA2a. In conclusion, the present study conferred new evidence on the protective effects of CAR and its combination with either RES or LIPO-RES on DOX-induced inflammation, oxidative stress and calcium dysregulation.
Prediction of Fracture Damage of Sandstone Using Digital Image Correlation
Authors: Chen Fanxiu , Wang Endong , Zhang Bin , Zhang Liming , Meng Fanzhen
Published: February 2020

Investigation on the deformation mechanism of sandstone is crucial to understanding the life cycle patterns of pertinent infrastructure systems considering the extensive adoption of sandstone in infrastructure construction of various engineering systems, e.g., agricultural engineering systems. In this study, the state-of-the-art digital image correlation (DIC) method, which uses classical digital photography, is employed to explore the detailed failure course of sandstone with physical uniaxial compression tests. Four typical points are specifically selected to characterize the global strain field by plotting their corresponding strain–time relationship curves. Thus, the targeted failure thresholds are identified. The Hill–Tsai failure criterion and finite element simulation are then used for the cross-check process of DIC predictions. The results show that, though errors exist between the experimental and the theoretical values, overall, they are sufficiently low to be ignored, indicating good agreement. From the results, near-linear relationships between strain and time are detected before failure at the four chosen points and the failure strain thresholds are almost the same; as low as 0.004. Failure thresholds of sandstone are reliably determined according to the strain variation curve, to forecast sandstone damage and failure. Consequently, the proposed technology and associated information generated from this study could be of assistance in the safety and health monitoring processes of relevant infrastructure system applications.
Networking Historic Environmental Standards to Address Modern Challenges for Sustainable Conservation in HBIM
Authors: Prizeman Oriel , Pezzica Camilla , Taher Ahmed , Boughanmi Mahdi
Published: February 2020

Awareness of the logic and context of original (and subsequent) design priorities is critical to informing decisions relating to valorisation, repair, refurbishment, energy retrofit or re-use of built heritage. A key benefit of collating data through Historic Building Information Modelling (HBIM) should be to assist others facing similar challenges. Here, examples for sharing understanding of how components belong to a system are outlined in the context of a newly completed dataset of public library buildings in the UK funded by Andrew Carnegie, predominantly built between 1900 and 1914. Demands for the functionality and economy of public library buildings, coupled with the emergent standardisation of building components at the time, provide a specific condition with potential for further iteration to other buildings of the period or related typologies. The work highlights the urgency of providing cost-efficient knowledge sharing structures in an era of altered priorities with respect to energy use for modern heritage. We propose the means for mapping common features to network knowledge amongst stakeholders through relevant open source pathways. The results demonstrate that integrating geographic approaches to knowledge sharing in HBIM with environmental considerations also supports wider questions of risk management related to the stewardship of historic buildings in the context of climate change.
Confirmation of Initial Stable Adsorption Structures of Leucine and Tyrosine Adsorbed on a Cu(110) Surface
Authors: Lee Hangil , Kim Hyun Sung
Published: February 2020

The structures and stability levels of leucine (Leu) and tyrosine (Tyr) adsorbed on a Cu(110) surface, at initial levels of coverage (less than 0.25 monolayer), were investigated using reflection–absorption infrared spectroscopy and high-resolution photoemission spectroscopy (HRPES), as well as by performing density functional theory calculations. At an initial coverage, the O–H dissociation bonded structure was indicated from the spectral results to be the most favorable structure for Leu adsorbed on the Cu(110) surface, whereas the O–H dissociated-N dative bonded structure was most favorable for adsorbed Tyr. These models were further supported by the results of experiments, in which the systems were exposed to other molecules and HRPES was used to monitor whether the amine or carboxylic groups of the adsorbed amino acids became reactive.
Cybersecurity Threats Based on Machine Learning-Based Offensive Technique for Password Authentication
Authors: Lee Kyungroul , Yim Kangbin
Published: February 2020

Due to the emergence of online society, a representative user authentication method that is password authentication has been a key topic. However, in this authentication method, various attack techniques have emerged to steal passwords input from the keyboard, hence, the keyboard data does not ensure security. To detect and prevent such an attack, a keyboard data protection technique using random keyboard data generation has been presented. This technique protects keyboard data by generating dummy keyboard data while the attacker obtains the keyboard data. In this study, we demonstrate the feasibility of keyboard data exposure under the keyboard data protection technique. To prove the proposed attack technique, we gathered all the dummy keyboard data generated by the defense tool, and the real keyboard data input by the user, and evaluated the cybersecurity threat of keyboard data based on the machine learning-based offensive technique. We verified that an adversary obtains the keyboard data with 96.2% accuracy even if the attack technique that makes it impossible to attack keyboard data exposure is used. Namely, the proposed method in this study obviously differentiates the keyboard data input by the user from dummy keyboard data. Therefore, the contributions of this paper are that we derived and verified a new security threat and a new vulnerability of password authentication. Furthermore, a new cybersecurity threat derived from this study will have advantages over the security assessment of password authentication and all types of authentication technology and application services input from the keyboard.
Posture Recognition Using Ensemble Deep Models under Various Home Environments
Authors: Byeon Yeong-Hyeon , Lee Jae-Yeon , Kim Do-Hyung , Kwak Keun-Chang
Published: February 2020

This paper is concerned with posture recognition using ensemble convolutional neural networks (CNNs) in home environments. With the increasing number of elderly people living alone at home, posture recognition is very important for helping elderly people cope with sudden danger. Traditionally, to recognize posture, it was necessary to obtain the coordinates of the body points, depth, frame information of video, and so on. In conventional machine learning, there is a limitation in recognizing posture directly using only an image. However, with advancements in the latest deep learning, it is possible to achieve good performance in posture recognition using only an image. Thus, we performed experiments based on VGGNet, ResNet, DenseNet, InceptionResNet, and Xception as pre-trained CNNs using five types of preprocessing. On the basis of these deep learning methods, we finally present the ensemble deep model combined by majority and average methods. The experiments were performed by a posture database constructed at the Electronics and Telecommunications Research Institute (ETRI), Korea. This database consists of 51,000 images with 10 postures from 51 home environments. The experimental results reveal that the ensemble system by InceptionResNetV2s with five types of preprocessing shows good performance in comparison to other combination methods and the pre-trained CNN itself.
Railway Wheel Flat Recognition and Precise Positioning Method Based on Multisensor Arrays
Authors: Zhou Chenyi , Gao Liang , Xiao Hong , Hou Bowen
Published: February 2020

Wheel flats have become a major problem affecting the long-term service of railway systems. Wheels with flats create intermittent impact loads to trains and rails. This not only accelerates the deterioration of vehicle and track components but also leads to abnormal wheel-rail contact conditions. An effective method for detecting wheel conditions is urgently needed to ensure the operation of the railway and provide guidance for the repair of wheels. However, most previous researches have used qualitative detection methods, and hence have been unable to achieve accurate positioning of the wheel flats. In addition, the theoretical basis for the layout scheme for wheel flat detection sensors is lacking, making it impossible to meet the needs of field applications. In this study, we simulated the spatial distribution characteristics of rail strain, under different wheel flat conditions, and based on this, a layout scheme of multisensor arrays was proposed which more effectively captured the responses of the wheel flats. A wheel flat recognition and precise positioning method based on multisensor fusion was designed. The algorithm was validated through the combination of experimental and simulation methods. The result shows that the algorithm can ideally detect and locate the wheel flats under complex conditions.
Emulation Strategies and Economic Dispatch for Inverter-Based Renewable Generation under VSG Control Participating in Multiple Temporal Frequency Control
Authors: Zhang Weichao , Yan Xiangwu , Huang Hanyan
Published: February 2020

As the increasing penetration of inverter-based generation (IBG) and the consequent displacement of traditional synchronous generators (SGs), the system stability and reliability deteriorate for two reasons: first, the overall inertia decreases since the power electronic interfaces (PEIs) are almost inertia-less; second, renewable generation profiles are largely influenced by stochastic meteorological conditions. To strengthen power systems, the concept of the virtual synchronous generator (VSG) has been proposed, which controls the external characteristics of PEIs to emulate those of SGs. Currently, PEIs could perform short-term inertial and primary frequency responses through the VSG algorithm. For renewable energy sources (RES), deloading strategies enable the generation units to possess active power reserves for system frequency responses. Additionally, the deloading strategies could provide the potential for renewable generation to possess long-term frequency regulation abilities. This paper focuses on emulation strategies and economic dispatch for IBG units to perform multiple temporal frequency control. By referring to the well-established knowledge systems of generation and operation in conventional power systems, the current VSG algorithm is extended and complemented by the emulation of secondary and tertiary regulations. The reliability criteria are proposed, considering the loss of load probability (LOLP) and renewable spillage probability (RSP). The reliability criteria are presented in two scenarios, including the renewable units operated in maximum power point tracking (MPPT) and VSG modes. A LOLP-based economic dispatch (ED) approach is solved to acquire the generation and reserve schemes. The emulation strategies and the proposed approach are verified by simulation.
Special Issue on Mobile Robots Navigation
Authors: Reinoso Oscar , Payá Luis
Published: February 2020

In recent years, the presence of mobile robots in diverse scenarios has considerably increased, to solve a variety of tasks [...]
Degradable and Dissolvable Thin-Film Materials for the Applications of New-Generation Environmental-Friendly Electronic Devices
Authors: Liu Xiaoyan , Shi Mingmin , Luo Yuhao , Zhou Lvyang , Loh Zhi Rong , Oon Zhi Jian , Lian Xiaojuan , Wan Xiang , Chong Fred Beng Leng , Tong Yi
Published: February 2020

The environmental pollution generated by electronic waste (e-waste), waste-gas, and wastewater restricts the sustainable development of society. Environmental-friendly electronics made of degradable, resorbable, and compatible thin-film materials were utilized and explored, which was beneficial for e-waste dissolution and sustainable development. In this paper, we present a literature review about the development of various degradable and disposable thin-films for electronic applications. The corresponding preparation methods were simply reviewed and one of the most exciting and promising methods was discussed: Printing electronics technology. After a short introduction, detailed applications in the environment sensors and eco-friendly devices based on these degradable and compatible thin-films were mainly reviewed, finalizing with the main conclusions and promising perspectives. Furthermore, the future on these upcoming environmental-friendly electronic devices are proposed and prospected, especially on resistive switching devices, showing great potential applications in artificial intelligence (AI) and the Internet of Thing (IoT). These resistive switching devices combine the functions of storage and computations, which can complement the off-shelf computing based on the von Neumann architecture and advance the development of the AI.
Failure Type Prediction Using Physical Indices and Data Features for Solenoid Valve
Authors: Peng Jun , Tang Xuanheng , Chen Bin , Jiang Fu , Yang Yingze , Zhang Rui , Gao Dianzhu , Zhang Xiaoyong , Huang Zhiwu
Published: February 2020

A high-speed solenoid valve is a key component of the braking system. Accurately predicting the failure type of the solenoid valve is an important guarantee for safe operation of the braking system. However, electrical, magnetic, and mechanical coupling aging mechanism; individual differences; and uncertainty of aging processes have remained major challenges. To address this problem, a method combining physical indices and data features is proposed to predict the failure type of solenoid valve. Firstly, the mechanism model of the solenoid valve is established and five physical indices are extracted from the driven current curve. Then, the frequency band energy characteristics are obtained from the current change rate curve of the solenoid valve by wavelet packet decomposition. Combining physical indices and frequency band energy characteristics into a comprehensive feature vector, we applied random forest to both predict and classify the failure type. We generate a data set consisting of 60 high-speed solenoid valves periodically switched under accelerated aging test conditions, including driven current, final failure type, and switching cycles. The prediction result shows that the proposed method achieves 95.95% and 94.68% precision for the two failures using the driven current data of the 3000th cycle and has better prediction performance than other algorithms.
Prediction System for Prostate Cancer Recurrence Using Machine Learning
Authors: Lee Sun Jung , Yu Sung Hye , Kim Yejin , Kim Jae Kwon , Hong Jun Hyuk , Kim Choung-Soo , Seo Seong Il , Byun Seok-Soo , Jeong Chang Wook , Lee Ji Youl , Choi In Young
Published: February 2020

Prostate cancer is the fourth most common cancer affecting South Korean males, and the biochemical recurrence (BCR) of prostate cancer occurs in approximately 25% of patients five years after radical prostatectomy. The ability to predict BCR would help clinicians and patients to make better treatment decisions. Therefore, in this study, we have proposed a web-based clinical decision support system that predicts the BCR of prostate cancer in Korean patients. The data were obtained from the Korean Prostate Cancer Registry (KPCR) database, which contained information about 7394 patients with prostate cancer who were treated at one of the six major medical institutions in South Korea between May 2001 and December 2014. We tested 13 prediction models and selected the gradient boosting classifier because it demonstrated excellent prediction performance. Using this model, we were able to create a web application and once clinical data from patients were entered, the three- and five-year post-surgery BCR predictions could be extracted. We developed a clinical decision support system to provide a prostate cancer BCR predictive function to facilitate postoperative follow-up and clinical management. This system will help clinicians develop a strategic approach for prostate cancer treatment by predicting the likelihood of prostate cancer recurrence.
An SVM-Based Neural Adaptive Variable Structure Observer for Fault Diagnosis and Fault-Tolerant Control of a Robot Manipulator
Authors: Piltan Farzin , Prosvirin Alexander E. , Sohaib Muhammad , Saldivar Belem , Kim Jong-Myon
Published: February 2020

A robot manipulator is a multi-degree-of-freedom and nonlinear system that is used in various applications, including the medical area and automotive industries. Uncertain conditions in which a robot manipulator operates, as well as its nonlinearities, represent challenges for fault diagnosis and fault-tolerant control (FDC) that are addressed through the proposed FDC technique. A machine-learning-based neural adaptive, high-order, variable structure observer for fault diagnosis (FD) and adaptive, modern, fuzzy, backstepping, variable structure control for use in a fault-tolerant control (FC) algorithm, are proposed in this paper. In the first stage, a variable structure observer is proposed as an FD technique for the robot manipulator. The chattering phenomenon associated with the variable structure observer(VSO) is solved using a high-order variable structure observer. Then, the dynamic behavior estimation performance in the high-order variable structure observer is improved by incorporating a neural network algorithm in the FD pipeline. This adaptive technique is also effective in improving the robustness of the fault signal estimation. Moreover, support vector machines (SVMs) that can derive adaptive threshold values are used to categorize faults. To design an effective fault-tolerant controller (FC), an adaptive modern fuzzy backstepping variable structure controller is used in this study. First, a new variable structure controller is designed. Next, to increase robustness and reduce high-frequency oscillations in uncertain conditions, a backstepping algorithm is used in parallel with the variable structure controller to design the backstepping variable structure controller. To design an effective hybrid controller, a fuzzy algorithm is integrated into the backstepping variable structure controller to create a fuzzy backstepping variable structure controller. Then, to improve the robustness and reliability of the FC, a neural adaptive. high-order. variable structure observer is applied to the fuzzy backstepping variable structure controller to design a modern fuzzy backstepping variable structure controller. An adaptive algorithm is used to fine-tune the variable structure coefficients and reduce the effect of faults on the robot manipulator. The effectiveness of the selected algorithm is validated using a PUMA robot manipulator. The neural adaptive. high-order variable structure observer improves the average performance for the identification of various faults by about 27% and 29.2%, compared with the neural high-order variable structure observer and variable structure observer, respectively.