bluuebunny/crossref_metadata_2025 huggingface dataset:
Fiber Optic Vibration Sensors
Authors: Kishore Putha , Dinakar Dantala , Padmavathi Manchineellu
Published: June 2021

The sensors presented in this chapter are fiber optic intensity modulated vibrations sensors which are non-contact (extrinsic sensor) to the vibrating object. Three sensors presented make use of non-contact vibration measurement method with plastic fiber using distinct designs, improvement of the sensor response and advantages of one sensor over the other for diverse applications. First discussed about dual plastic optical fiber vibration sensor design and its response. Secondly, discussed about 1x2 fused coupler plastic optical fiber vibration sensor design with advantages over the first one. Finally, discussed about the 2x2 fused coupler plastic optical fiber vibration sensor design along with advantages than other two methods. At the end reported the final results with comparison.
Monospecific and Polyreactive Monoclonal Antibodies against Human Leukocyte Antigen-E: Diagnostic and Therapeutic Relevance
Authors: H. Ravindranath Mepur , E.L. Hilali Fatiha
Published: June 2021

A monoclonal antibody (mAb) binds to an antigen recognizing an epitope (a sequence of amino acids). A protein antigen may carry amino acid sequence unique to that antigen as well as sequences found in other proteins. Human leukocyte antigens (HLA), a family of proteins expressed by the Major Histocompatibility Complex gene family represent a special case, in that it displays a high degree of polymorphism. Every HLA molecule possesses both specific (private) epitopes and epitopes shared (public) with other HLA class Ia and class Ib molecules. HLA-E is overexpressed in cancer cells more than any other HLA Class I molecules. Therefore specific localization of HLA-E with mAbs is pivotal for developing targeted therapy against cancer. However, the commercially available mAbs for immunodiagnosis are polyreactive. We have developed anti-HLA-E mAbs and distinguished monospecific from polyreactive mAbs using Luminex multiplex single antigen bead (SAB) assay. HLA-E-binding of monospecific-mAbs was also inhibited by E-restricted epitopes. The amino acid sequences in the region of the epitopes bind to CD94/NKG2A receptors on CD8+ T cells and NK cells and block their antitumor functions. Monospecific-HLA-E mAbs recognizing the epitopes sequences can interfere with the binding to restore the anti-tumor efficacy of NK cells. Also, monospecific-mAbs augment the proliferation of CD4-/CD+ cytotoxic T-lymphocytes. Therefore, anti-HLA-E monospecific-mAb can serve as a double-edged sword for eliminating tumor cells.
Optical Properties of Single Crystals
Authors: Chandran Senthilkumar , Manikam Srinivasan
Published: June 2021

Nonlinear optical crystals plays important role in the field of photo electronics, optical communication, optical modulators, laser spectroscopy, frequency conversion and so on. Semi-organic crystals exhibit high NLO response, thermal stability, laser damage threshold, mechanical stability, wide optical window transmittance and structural diversity. Combinations of inorganic and organic molecules yield the semi-organic crystals. Based on its structural diversity it’s classified into three categories. In this chapter explains various kinds of semi-organic crystals and their optical, thermal, mechanical, laser damage threshold value and NLO properties and also explains the importance of these crystals in the field of optoelectronics, frequency conversion and other optical applications.
Regenerative Endodontic Procedure in Immature Permanent Teeth
Authors: G. Al-shammari Meshal
Published: June 2021

This literature review will aim to recapitulate the different factors involved in the endodontic regenerative procedure, with a focus on different bacterial disinfecting techniques, intra-canal dressings and expected treatment outcomes. The electronic databases searched were EMBASE, MEDLINE and PUBMED. Articles included were limited to the English language from the year 1988 to May 2019. A hand search of the literature was also performed for articles dating back to 1958. No clear guidelines were available regarding follow-up and expected treatment outcomes in terms of success, survival (acceptable) or treatment failure. However, calcium hydroxide as an intra-canal medicament was found to be the best treatment modality in comparison to antibiotic paste for intra-canal dressing.
Medical Therapy of Giant Cell Tumor of Bone
Authors: Lopes-Brás Raquel , Fernandes Isabel , Casimiro Sandra , Costa Luís
Published: June 2021

Giant cell tumor of bone (GCTB) is mostly a benign disease of the bone, although with high local recurrence rate and potential for metastatic spread, namely to the lungs. It is also a locally aggressive tumor, associated with severe morbidity and functional impairment due to bone destruction. Treatment is therefore required and should be offered at an early stage to allow complete resection, minimizing functional sequelae and local recurrence. Surgical resection is the mainstay of treatment, often followed by intralesional adjuvant therapy. GCTB has a particular biology, in which RANKL represents a key factor in tumor pathogenesis, thus making this molecule a valuable therapeutic target. Monthly administration of denosumab, a fully human monoclonal antibody directed against RANKL, has been studied in several clinical trials and shown a high rate of local control with favorable safety profile. In this chapter, current medical management, ongoing studies, and future directions in GCTB will be discussed.
Personalized Digital Phenotype Score, Healthcare Management and Intervention Strategies Using Knowledge Enabled Digital Health Framework for Pediatric Asthma
Authors: Jaimini Utkarshani , Sheth Amit
Published: June 2021

Asthma is a personalized, and multi-trigger respiratory condition which requires continuous monitoring and management of symptoms and medication adherence. We developed kHealth: Knowledge-enabled Digital Healthcare Framework to monitor and manage the asthma symptoms, medication adherence, lung function, daily activity, sleep quality, indoor, and outdoor environmental triggers of pediatric asthma patients. The kHealth framework collects up to 1852 data points per patient per day. It is practically impossible for the clinicians, parents, and the patient to analyze this vast amount of multimodal data collected from the kHealth framework. In this chapter, we describe the personalized scores, clinically relevant asthma categorization using digital phenotype score, actionable insights, and potential intervention strategies for better pediatric asthma management.
Bone Lesions in Children with Neurofibromatosis
Authors: Laliotis Nikolaos
Published: June 2021

Neurofibromatosis is often related with severe orthopaedic disorders in children. Bone lesions are rare but pose severe difficulties in management. It affects the spine and long bones. Lesions are associated either from enlargement of neurofibromas that affect the normal growth or from primary neurofibromatosis of long bones. Dystrophic scoliosis appears with short curves, with kyphosis and rotation of the apical vertebrae. Usually affect the thoracic spine, with penciling of the ribs. Surgical treatment is challenging in cases of rapid progression. Scoliosis may appear with curvatures similar to those in idiopathic scoliosis, without dysplastic changes of the vertebrae. Anterior bowing of the tibia is manifestation of NF and is distinguished from the benign posterolateral bowing. Evaluation of the medullary canal and presence of cystic lesions in the tibia is essential. Progression to pseudoarthrosis or pathologic fracture is common. Surgical management of tibial pseudoarthrosis remains a difficult procedure. Pseudoarthrosis may appear in fibula, radius or ulna but are extremely rare. Irregular eccentric bone cysts in long bones that are commonly diagnosed after a pathologic fracture, must be differentiated for NF. Malignant transformation of neurofibromas must be considered when there is rapid progression of the lesion.
The Viability of Outsourcing in Organisational Performance: Benefits and Risks
Authors: Franco Mário , Rodrigues Margarida , Silva Rui
Published: June 2021

Outsourcing is part of a system, as it includes products and services integrated in a value chain and which are performed by an external (contracted) firm, aiming to establish an interdependent, collaborative and trusting relationship between the contracting and contracted firms. Like any dimension of business in organisations, changes in organisational structures and in how the service is produced/provided, outsourcing brings benefits and risks. Therefore, from literature review method, this chapter aims to explore the concept of outsourcing as a differentiating tool in organisations’ performance, emphasising the benefits and risks. The results showed the dimensions to consider in the decision to implement outsourcing, which are: (1) transaction costs, (2) use of resources, and (3) collaboration between the parties. The contribution of the study is to present a synopsis of the outsourcing topic, specifically the theories that support it, its benefits and risks. Additionally, a decision-making model is presented, in the certainty of its usefulness for the organizations’ managers.
Syzygium cumini Mediated Green Synthesis of Silver Nanoparticles for Reduction of 4-Nitrophenol and Assessment of Its Antibacterial Activity
Authors: R. Waghmode Samadhan , A. Dudhane Amol , P. Mhaindarkar Vaibhav
Published: June 2021

The biosynthesis of silver nanoparticles (AgNPs) has become more significant in the recent years owing to its applications in catalysis, imaging, drug delivery, nano-device fabrication and in medicine. We propose the synthesis of silver nanoparticles from the plant extract of Syzygium cumini and evaluation of its antibacterial and chemocatalytic potential. Synthesis of AgNPs carried out by using aqueous silver nitrate. The UV–Vis absorption spectrum of the synthesized AgNPs showed a broad absorption peak at 470 nm. TEM analysis shows the morphology of AgNPs as a hexagonal matrix with average particle size is about 50 nm. XRD analysis displays the crystalline structure of AgNPs. The presence of elemental silver was confirmed with EDX analysis. FTIR analysis shows that amide groups present in proteins are dominant reducing agents and play an important role in the bioreduction of Ag+ ions to Ag0. The bioreduced AgNPs demonstrated significant catalytic properties in a reduction reaction of 4-nitrophenol to 4-aminophenol using NaBH4 in an aqueous condition. The biosynthesized AgNPs have potent antibacterial activity against common clinical pathogens. Considering the remarkable antibacterial activity against common pathogenic microorganisms, AgNPs can be used in the pharmaceutical industries.
Visiting Potato from a Breeding Perspective: Accomplishments and Prospects
Authors: Singh Brar Navjot , Pal Sharma Sat , Kaushik Prashant
Published: June 2021

Several enhancements to the conventional potato breeding are possible though they have encouragement as well as limitations. I n this direction, the marker-assisted selection may be utilized to stack major genes as well as QTLs. Whereas the genetic transformation and genome editing methods accelerate the process of ricking of genes/transgenes. Moreover, these methodologies supplemented with the next-generation sequencing (NGS) platforms and pipelines further aid in reaching the potato ideotype. Here, we overviewed the critical topics that are related to potatoes, from general background, breeding behavior, breeding approaches employed to the potato improvement. Overall, this information complied might serve as background information that is important for potato breeders.
Soil Compaction Due to Increased Machinery Intensity in Agricultural Production: Its Main Causes, Effects and Management
Authors: Gürsoy Songül
Published: June 2021

In modern agriculture, most of the field operations from sowing to harvesting are done mechanically by using heavy agriculture machines. However, the loads from these heavy machines may induce stresses exceeding soil strength causing soil compaction. Nowadays, soil compaction is considered as a serious form of soil degradation, which may have serious economics and environmental consequences in world agriculture because of its effects on soil structure, plant growth and environmental events. Vehicle load, inflation pressure, number of passes, stress on the soil, and soil properties (e.g. soil water content, soil texture, soil strength, soil bulk density) play an important role on soil compaction. This chapter reviews the works related to soil compaction in agricultural areas. Also, it discusses the nature and causes of soil compaction, the effects of the compaction on soil properties, environment and plant growth, and the possible solutions suggested in the literature.
Antioxidants: Pharmacothearapeutic Boon for Diabetes
Authors: Suresh Varuna , Reddy Amala , Muthukumar Pavithra , Selvam Thendarl
Published: June 2021

Glucose-induced oxidative stress can be found related to “glucose variability” and “glucose memory”. The irregular low and elevated glucose conditions cause damage to endothelial cell function than a steady, constant rise in level of glucose. Activation of PKC, NADPH oxidases, and mitochondrial oxidants are some of the pathways exhibited as a result of this aggravated cellular response. Regarding glucose memory, long after the normalization elevated level of glucose in the endothelial cells of diabetic rats and culture, a existance or ‘memory’ of induced basement membrane mRNA is expressed. This demonstrates that glucose causes dangerous long-term effects beyond the hyperglycemia period. Oxidative stress give rise to glucotoxicity and lipotoxicity which are phenomena’s related to diabetes. Following the pathogenesis of diabetes, hyperglycemia and hyperlipidemia exerts a supplementary toxic effect on the beta-cells. So, hyperglycemia can be considered as a requirement for the destructive effects of lipotoxicity. Thus glucolipotoxicity can be considered as a substitute for lipotoxicity which relates the detrimental correlation between lipids and beta-cell function. Generally, the antioxidant pharmacotherapy can be coupled with drugs to boost the natural cellular defense mechanisms as the naturally existing antioxidant components, which neutralizes free radical damage. This considers antioxidant a boon tool for pharmacotherapeutic agent.
Nanomagnetic Polymeric Absorbent Based on Alginate and Gamma-Maghemite Synthesized In Situ for Wastewater Treatment from Metallurgical Industry
Authors: Lourenço de Mello Ferreira Ivana , Ferreira Bittencourt Rodrigo , Sousa Júnior Clenilson
Published: June 2021

A nanomagnetic absorbent based on calcium alginate was produced successfully with the maghemite nanoparticles synthesized in situ, i.e., together with the polysaccharide crosslinking reaction. Physicochemical properties of the absorbent were analyzed and its ability to remove Ni(II) and Mn(II) ions from a real metallurgical industry wastewater was evaluated. Kinetic studies of the adsorption of these heavy metals were realized. To ascertain the most suitable quantity of absorbent to remove Ni(II) and Mn(II) from the wastewater, the absorbent mass was varied and adsorption kinetics was also evaluated. The competitiveness between the metals was evaluated to understand the adsorption mechanism. The samples were characterized by transmission electron microscopy, vibrating sample magnetometry, X-ray diffractometry and Mössbauer spectroscopy. The absorbent prepared, in this work, can be classified as a hydrogel. It presented predominant spherical morphology and micrometric dimension, containing atoms of iron and calcium dispersed uniformly in their internal and external surfaces. The synthesized maghemite nanoparticles presented superparamagnetic behavior. Results showed that the adsorption equilibrium time for both ions was about 60 min. The removal percentages from wastewater were 60.5% for nickel and 56.6% for manganese, using 300 mg of hydrogel. Results revealed that the adsorption mechanism is by ionic change between calcium and heavy metals.
Novel Certification Method for Quantum Random Number Generators
Authors:   Caucasus University/CST/Tbilisi, Georgia, 0102, Iavich Maksim , Kuchukhidze Tamari , Gnatyuk Sergiy , Fesenko Andriy
Published: June 2021

Random numbers have many uses, but finding true randomness is incredibly difficult. Therefore, quantum mechanics is used, using the essentially unpredictable behavior of a photon, to generate truly random numbers that form the basis of many modern cryptographic protocols. It is essential to trust cryptographic random number generators to generate only true random numbers. This is why certification methods are needed which will check both the performance of our device and the quality of the random bits generated. Self-testing as well as device independent quantum random number generation methods are analyzed in the paper. The advantages and disadvantages of both methods are identified. The model of a novel semi self-testing certification method for quantum random number generators is offered in the paper. This method combines different types of certification approaches and is rather secure and efficient. The method is very important for computer science, because it combines the best features from selftesting and device independent methods. It can be used, when the random numbers’ entropy depends on the device and when it does not. In the related researches, these approaches are offered to be used separately, depending on the random number generator. The offered novel certification technology can be properly used, when the device is compromised or spoiled. The technology can successfully detect unintended irregularities, operational problems, abnormalities and problems in the randomization process. The offered mythology assists to eliminate problems related to physical devices. The offered system has the higher certification randomness security and is faster than self-testing approaches. The method is rather efficient because it implements the different certification approaches in the parallel threads. The offered techniques make the offered research must more efficient than the other existing approaches. The corresponding programming simulation is implemented by means of the simulation techniques.
Design, Analysis, and Implementation of a Twofactor Authentication Scheme using Graphical Password
Authors:   Research Scholar JNTUK, Andhra Pradesh, India, Quadry Khaja Mizbahuddin , Govardhan A , Misbahuddin Mohammed
Published: June 2021

With the increase in the number of e-services, there is a sharp increase in online financial transactions these days. These services require a strong authentication scheme to validate the users of these services and allow access to the resources for strong security. Since two-factor authentication ensures the required security strength, various organizations employ biometric-based or Smart Card or Cryptographic Token-based methods to ensure the safety of user accounts. But most of these methods require a verifier table for validating users at a server. This poses a security threat of stolen-verifier attack. To address this issue, there is a strong need for authentication schemes for e-services that do not require a verifier table at the server. Therefore, this paper proposes the design of an authentication scheme for eservices which should be resistant to various attacks including a stolen verifier attack. The paper will also discuss: 1) The proposed scheme analyzed for security provided against the known authentication attacks 2) The concept mplementation of the proposed scheme.
Credibility Detection on Twitter News Using Machine Learning Approach
Authors:   Modern Academy for Computer Science and Management Technology, Computer Science Department, Cairo, 11434, Egypt, Azer Marina , Taha Mohamed , Zayed Hala H. , Gadallah Mahmoud
Published: June 2021

Social media presence is a crucial portion of our life. It is considered one of the most important sources of information than traditional sources. Twitter has become one of the prevalent social sites for exchanging viewpoints and feelings. This work proposes a supervised machine learning system for discovering false news. One of the credibility detection problems is finding new features that are most predictive to better performance classifiers. Both features depending on new content, and features based on the user are used. The features' importance is examined, and their impact on the performance. The reasons for choosing the final feature set using the k-best method are explained. Seven supervised machine learning classifiers are used. They are Naïve Bayes (NB), Support vector machine (SVM), Knearest neighbors (KNN), Logistic Regression (LR), Random Forest (RF), Maximum entropy (ME), and conditional random forest (CRF). Training and testing models were conducted using the Pheme dataset. The feature's analysis is introduced and compared to the features depending on the content, as the decisive factors in determining the validity. Random forest shows the highest performance while using user-based features only and using a mixture of both types of features; features depending on content and the features based on the user, accuracy (82.2 %) in using user-based features only. We achieved the highest results by using both types of features, utilizing random forest classifier accuracy(83.4%). In contrast, logistic regression was the best as to using features that are based on contents. Performance is measured by different measurements accuracy, precision, recall, and F1_score. We compared our feature set with other studies' features and the impact of our new features. We found that our conclusions exhibit high enhancement concerning discovering and verifying the false news regarding the discovery and verification of false news, comparing it to the current results of how it is developed.
Point Based Forecasting Model of Vehicle Queue with Extreme Learning Machine Method and Correlation Analysis
Authors:   Master of Computer Science, Universitas Gadjah Mada, Yogyakarta, Indonesia, Kasliono  , Suprapto  , Makhrus Faizal
Published: June 2021

Traffic is a medium to move from one point to another. Therefore, the role of traffic is very important to support vehicle mobility. If congestion occurs, mobility will be hampered so that it gives influence to other sectors such as financial, air pollution and traffic violations. This study aims to create a model to predict vehicle queue at the traffic lights when its status is red. The prediction is conducted by using Neural Network with Extreme Learning Machine method to predict the length of the vehicle queue, and Correlation Analysis was used to measure the correlation between the connected roads. The conducted experiments use data of the length of the vehicle queue at the traffic lights which was obtained from DISHUB (Transportation Bureau) DI Yogyakarta. Several experiments were carried out to determine the optimum prediction model of vehicle queue length. The experiments found that the optimum model had an average MAPE value of 15.5882% and an average Running Time of 5.2226 seconds.
Influence of GUJarati STEmmeR in Supervised Learning of Web Page Categorization
Authors:   Research Scholar, Hemchandracharya North Gujarat University, Patan, Gujarat, India., D. Patel Chandrakant , Patel Jayesh M.
Published: June 2021

With the large quantity of information offered on-line, it's equally essential to retrieve correct information for a user query. A large amount of data is available in digital form in multiple languages. The various approaches want to increase the effectiveness of on-line information retrieval but the standard approach tries to retrieve information for a user query is to go looking at the documents within the corpus as a word by word for the given query. This approach is incredibly time intensive and it's going to miss several connected documents that are equally important. So, to avoid these issues, stemming has been extensively utilized in numerous Information Retrieval Systems (IRS) to extend the retrieval accuracy of all languages. These papers go through the problem of stemming with Web Page Categorization on Gujarati language which basically derived the stem words using GUJSTER algorithms [1]. The GUJSTER algorithm is based on morphological rules which is used to derived root or stem word from inflected words of the same class. In particular, we consider the influence of extracted a stem or root word, to check the integrity of the web page classification using supervised machine learning algorithms. This research work is intended to focus on the analysis of Web Page Categorization (WPC) of Gujarati language and concentrate on a research problem to do verify the influence of a stemming algorithm in a WPC application for the Gujarati language with improved accuracy between from 63% to 98% through Machine Learning supervised models with standard ratio 80% as training and 20% as testing.
IoT Bus Navigation System with Optimized Routing using Machine Learning
Authors:   October University for Modern Sciences and Arts (MSA), Mohamed Samer I. , Abdelhadi Muhamed
Published: June 2021

As the population in Egypt is ever expanding, it is reflected in the increase of the number of vehicles on the road. Public transportation is the solution and the number of available buses can cover a significant amount of the population demand. However, the outdated state of the transportation infrastructure, the static nature of the lines and indistinct schedules create a confounding and unappealing user experience which prompts the users to stray to cars for their needs. So, an Intelligent Urban Transportation System (IUTS) is a must. IUTS is a multi-layered system which provides the solution for most of these problems. It operates on different layers starting from a real time vehicle tracking for transparent and efficient management of assets, cash-less ticketing done through RFID cards, vehicle health and diagnostic data for creation of automated maintenance schedules and a friendly interactive driver interface. In this paper an approach based on combining all these technologies is discussed where the hardware component is implemented based on System-on-Chip technology with custom hardware to interface with the vehicle. The data collected from the on-board unit is sent to the cloud, and with the help of machine learning algorithms the dynamic responsiveness of the system is guaranteed. The proposed system outperforms other existing ones through the dynamic and optimized routing feature for the bus navigation to optimize the operating cost but still satisfy the passengers’demand.
Bug Severity Prediction using Keywords in Imbalanced Learning Environment
Authors:   Dept. of Computer Science and Informatics, Faculty of Applied Sciences, Uva Wellassa University, Badulla, 90000, Sri Lanka, Ekanayake Jayalath
Published: June 2021

Reported bugs of software systems are classified into different severity levels before fixing them. The number of bug reports may not be equally distributed according to the severity levels of bugs. However, most of the severity prediction models developed in the literature assumed that the underlying data distribution is evenly distributed, which may not correct at all instances and hence, the aim of this study is to develop bug classification models from unevenly distributed datasets and tested them accordingly. To that end first, the topics or keywords of developer descriptions of bug reports are extracted using Rapid Keyword Extraction (RAKE) algorithm and then transferred them into numerical attributes, which combined with severity levels constructs datasets. These datasets are used to build classification models; Naïve Bayes, Logistic Regression, and Decision Tree Learner algorithms. The models’ prediction quality is measured using Area Under Recursive Operative Characteristics Curves (AUC) as the models learnt from more skewed environments. According to the results, the prediction quality of the Logistics Regression model is 0.65 AUC whereas the other two models recorded maximum 0.60 AUC. Though the datasets contain comparatively less number of instances from the high severity classes; Blocking and High, the Logistic Regression models predict the two classes with a decent AUC value of 0.65 AUC. Hence, this projects shows that the models can be trained from highly skewed datasets so that the models prediction quality is equally well over all the classes regardless of number of instances representing the class. Further, this project emphasizes that the models should be evaluated using the appropriate metrics when the models are trained from imbalance learning environments. Also, this work uncovers that the Logistic Regression model is also capable of classifying documents as Naïve Bayes, which is well known for this task.
Is there a Human Right to Subsistence Goods?
Authors: Rettig Cristián ,   Philosophy Documentation Center
Published: June 2021

The much-discussed “claimability objection” holds that it is unjustified to believe that all individuals have a human right to subsistence because the bearers of the correlative duties are not sufficiently determined. This argument is based on the so-called “claimability-condition”: S has a right to P if and only if the duty-bearer is sufficiently determined. Practice-based theorists defend the human right to subsistence by arguing that if we take the existing human rights practice seriously, there is no indeterminacy about the allocation of duties. In this paper, I challenge this (apparently compelling) defense of the human right to subsistence with a dilemma. If the claimability condition is true, the practice-based defense fails to undermine the claimability objection because the duty-bearer is determined in some, but not all, cases. If practice-based theorists reject the claimability condition, they generate an account of human rights that is problematic from the practical perspective because it may contain duties that are unable to guide action.
Mennesker og medier i samspil
Authors: Sandbye Mette
Published: June 2021

Anmeldelse af:

Jacob Lund og Ulrik Schmidt (red.)

Medieæstetik – en introduktion

Forlaget Samfundslitteratur, Frederiksberg, 2020
Views from the boundaries
Authors: Nordgård Daniel
Published: June 2021

This article explores how Norwegian record label managers understand their current positions and future possibilities in a market that is increasingly driven by on-demand subscription-based streaming. It adds to a growing body of research by adopting a qualitative approach, seeking to describe issues at a personal or company level, and provide nuance and dynamics in a discourse that is often described in dichotomies and on aggregate levels. The article argues that stakeholders have more varied attitudes than simply being for or against the innovation, the new economic models and their eff ects on their own business, and the market in general. It also demonstrates that perceptions change as markets develop, and stakeholders and their businesses adjust. The article uses four in-depth interviews to assess a 2013 government-initiated project, and provides insights into differing positions and changes over time.
Multivariate analysis of the adoption of cacao productive technologies: Evidence from a case study in Colombia
Authors: Martínez José María , Martínez Pachón Eliana
Published: June 2021

Multivariate and ordered Probit models were used to study the determinants of the adoption and extent of adoption of agronomic practices among cacao farmers in Nariño, Colombia, with data from 353 farmers in the mountain region. Results suggest that farmers’ adoption decisions are made on a joint basis, further validating the use of a multivariate approach. The presence of illegal crops creates strong disincentives that affect the possibility of more significant technological improvements. Adequate access to agricultural technical assistance strongly increases rates of adoption. Evidence suggests that efforts are necessary to better target resource-poor farmers.
Gerçek Zamanlı Enerji İzleme ve Tüketici Farkındalığı için LabVIEW ™ Programı ile Otomatik Sayaç Okuma
Authors: KARAMAN Bilal , TAŞKIN Sezai , TOKAY Mert
Published: June 2021

Akıllı sayaçlar; kayıp-kaçak oranını azaltma, uzaktan okuma, kontrol etme (açma-kesme) ve faturalandırmanın yanı sıra farklı zaman dilimleri için enerji tüketimi hesaplaması ile yük öteleme teşviki gibi birtakım özellikleri sayesinde akıllı şebekelerin önemli birer bileşenidir. Bu çalışmada, RS-485 haberleşmesi ve TCP/IP protokolü üzerinden erişim sağlanan akıllı sayaç verileri NI LabVIEW™ programında tasarlanan bir arayüz üzerine aktarılmıştır. Böylece, her bir sayaca ait anlık akım, gerilim, aktif-reaktif güç değerleri, aktif - reaktif tüketim ile güç katsayısı değerlerinin hem nümerik hem de grafiksel olarak görüntülenmesi, tüketiciye raporlanması ve enerji tarif dilimlerine göre fiyatlandırılması yapılmıştır. Geliştirilen arayüze uzaktan erişim sağlanarak sayaca ait tüketim verilerinin ilgili elektrik dağıtım şirketi ve tüketici tarafından anlık izlenmesi sağlanmıştır. Çalışmada sunulan yöntem, mevcut akıllı sayaç sistemlerine yeni bir ilave maliyet getirmediğinden akıllı şebeke çözümlerine bir katkı sunmaktadır. Ayrıca, çalışmada sunulan sistem tüketicilerin tüketim verilerini sadece fatura döneminde değil sürekli olarak izlemelerine olanak verdiğinden hem enerji tasarrufu hem de şebeke üzerindeki yayılı yük dengelemesine de katkı sağlamaktadır.
Propozycja usługi autobilansowania (UAB)
Authors: Cetnarski Ryszard , Penksyy Serhiy , Wawrzyniak Karol
Published: June 2021

Energetyka rozproszona rozwija się w szybkim tempie i potrzebuje rozwiązań legislacyjnych, które wesprą jej działanie i jednocześnie nie obciążą kosztowo reszty społeczeństwa. Niniejszy artykuł przedstawia i opisuje rozwiązanie, które pozwoli osiągnąć te cele. Usługa autobilansowania promuje pożądane zjawiska sieciowe w obszarze przesyłu i dystrybucji energii. Zjawiska te wynikają z jednoczesności występowania popytu i podaży na energię w określonym, lokalnym obrębie sieci nazwanym obszarem autobilansowania. Proponuje się, by rekompensata za usługę autobilansowania była uznana za koszt uzasadniony ponoszony przez OSD, ponieważ jej realizacja prowadzi do wykonania zadań ustawowych OSD. Usługa autobilansowania składa się z dwóch niezależnych elementów: autokonsumpcja godzinowa generuje pożądane efekty w obszarze energii, redukując starty przesyłowe, zaś bilansowanie fizyczne prowadzi do redukcji mocy szczytowych, co przekłada się na oszczędności w obszarze inwestycji sieciowych. Usługa autobilansowania zachęca do inwestycji w elastyczne źródła energii oraz sterowania elastycznymi jednostkami w sposób najbardziej korzystny z punktu widzenia sieci, czyli poprzez niwelację szczytów własnego zapotrzebowania. Przeprowadzono badanie symulacyjne, na podstawie szczegółowego modelu klastra energii, wskazujące na efekty ekonomiczne i technologiczne wprowadzenia proponowanej regulacji. Wyniki badania pokazują, że w przypadku wprowadzenia usługi klastry uzyskają istotną zachętę do inwestycji w magazyny energii i inne źródła elastyczności.
Klastry energii – szanse i bariery rozwoju. Podsumowanie badania ankietowego. Część 3: Instytucje zainteresowane rozwojem energetyki rozproszonej w Polsce
Authors: Piech Krzysztof , Hanzelka Zbigniew , Dybowski Paweł
Published: June 2021

W trzeciej ankiecie przeprowadzonej w ramach projektu KlastER (www.er.agh.edu.pl) poproszono przedstawicieli instytucji, organizacji, stowarzyszeń, fundacji itp. aktywnie działających na rzecz rozwoju energetyki rozproszonej w Polsce o wyrażenie opinii i oczekiwań dotyczących klastrów energii, jak również szeroko rozumianej energetyki rozproszonej (ER). W artykule przedstawiono podsumowanie wyników ankiety.
Identification and expression pattern analysis of miRNAs in pectoral muscle during pigeon (Columba livia) development
Authors: Wang Xun , Yan Peiqi , Feng Siyuan , Luo Yi , Liang Jiyuan , Zhao Ling , Liu Haifeng , Tang Qianzi , Long Keren , Jin Long , Ma Jideng , Jiang Anan , Shuai Surong , Li Mingzhou
Published: June 2021

MicroRNAs (miRNAs) are a group of crucial regulators in the process of animal growth and development. However, little is known about the expression and function of miRNAs in pigeon muscles. To identify the miRNAs participating in the rapid development of pigeon pectoral muscles and quantitate their expression levels of pectoral muscles in different age stages, we performed miRNA transcriptome analysis in pigeon pectoral muscles by sequencing small RNAs over three different age stages (1-day old, 28 days old, and 2 years old). Dual-luciferase reporter assay was applied to validate the interaction between miRNA and its target gene. We identified 304 known miRNAs, 201 conserved miRNAs, and 86 novel miRNAs in pigeon pectoral muscles. 189 differentially expressed (DE) miRNAs were screened out during pigeon development. A short time-series expression miner (STEM) analysis indicated 89 DE miRNAs were significantly clustered in a progressively decreasing expression profile, and mainly enriched in biosynthesis-related GO categories and signaling pathways for MAPK and TGF-β. Dual-luciferase reporter assay indicated that a progressively down-regulated miRNA (miR-20b-5p) could directly target Krüppel-like factor 3 (KLF3) gene. To sum-up, our data expand the repertoire of pigeon miRNAs and enhance understanding of the mechanisms underlying rapid development in squabs.
The characteristics of host lipid body biogenesis during coral-dinoflagellate endosymbiosis
Authors: Chen Hung-Kai , Rosset Sabrina L. , Wang Li-Hsueh , Chen Chii-Shiarng
Published: June 2021

Intracellular lipid body (LB) biogenesis depends on the symbiosis between coral hosts and their Symbiodinaceae. Therefore, understanding the mechanism(s) behind LB biosynthesis in corals can portentially elucide the drivers of cellular regulation during endosymbiosis. This study assessed LB formation in the gastrodermal tissue layer of the hermatypic coral Euphyllia glabrescens. Diel rhythmicity in LB size and distribution was observed; solar irradiation onset at sunrise initiated an increase in LB formation, which continued throughout the day and peaked after sunset at 18:00. The LBs migrated from the area near the mesoglea to the gastrodermal cell border near the coelenteron. Micro-LB biogenesis occurred in the endoplasmic reticulum (ER) of the host gastrodermal cells. A transcriptomic analysis of genes related to lipogenesis indicated that binding immunoglobulin protein (BiP) plays a key role in metabolic signaling pathways. The diel rhythmicity of LB biogenesis was correlated with ER-localized BiP expression. BiP expression peaked during the period with the largest increase in LB formation, thereby indicating that the chaperoning reaction of abnormal protein folding inside the host ER is likely involved in LB biosynthesis. These findings suggest that the host ER, central to LB formation, potentially facilitates the regulation of endosymbiosis between coral hosts and Symbiodiniaceae.
Digital mapping of soil texture in ecoforest polygons in Quebec, Canada
Authors: Duchesne Louis , Ouimet Rock
Published: June 2021

Texture strongly influences the soil’s fundamental functions in forest ecosystems. In response to the growing demand for information on soil properties for environmental modeling, more and more studies have been conducted over the past decade to assess the spatial variability of soil properties on a regional to global scale. These investigations rely on the acquisition and compilation of numerous soil field records and on the development of statistical methods and technology. Here, we used random forest machine learning algorithms to model and map particle size composition in ecoforest polygons for the entire area of managed forests in the province of Quebec, Canada. We compiled archived laboratory analyses of 29,570 mineral soil samples (17,901 sites) and a set of 33 covariates, including 22 variables related to climate, five related to soil characteristics, three to spatial position or spatial context, two to relief and topography, and one to vegetation. After five repeats of 5-fold cross-validation, results show that models that include two functionally independent values regarding particle size composition explain 60%, 34%, and 78% of the variance in sand, silt and clay fractions, respectively, with mean absolute errors ranging from 4.0% for the clay fraction to 9.5% for the sand fraction. The most important model variables are those observed in the field and those interpreted from aerial photography regarding soil characteristics, followed by those regarding elevation and climate. Our results compare favorably with those of previous soil texture mapping studies for the same territory, in which particle size composition was modeled mainly from rasterized climatic and topographic covariates. The map we provide should meet the needs of provincial forest managers, as it is compatible with the ecoforest map that constitutes the basis of information for forest management in Quebec, Canada.
Transitional Employment Programs within Clubhouses as a Means of Promoting Recovery for Individuals Living with Mental Illness: Reviewing the Case for Québec
Authors: Reidel Kristen , Abriel Shelagh , Tavares Rachel , Roark Mollie , McLellan Ruth , Kehayia Eva
Published: June 2021

Transitional employment (TE) within the Clubhouse model has been adopted across Canada and the world for its effectiveness in promoting work and recovery for persons living with mental illness. However, attempts to establish a TE program in the province of Québec have been met with numerous roadblocks. Using a qualitative phenomenological approach, this study aimed to synthesize knowledge that could inform local implementation of TE. Experiences of Montréal Clubhouse members and Canadian Clubhouse directors were examined. Member narratives identified employment-program and systemic shortcomings, while directors provided key strategies for overcoming barriers to TE implementation.
Meta-analysis of Technical Efficiency in Selected Agricultural Sub-sectors: Implications for Policy Making in Developing Countries like Sri Lanka
Authors: Senevirathne S. M. P. , Hettiarachchi M. H. S. M. , Dilrukshi R. P. W. A. , Kumara G.D. Kapila , Ampitiyawatta A. D. , Beneragama C. K.
Published: June 2021

Aims: To evaluate the technical efficiency (TE) in selected agricultural sub-sectors and to propose possible policy interventions to the government with the aim of reducing the poverty of farmers in the developing world.

Study design: A meta-analysis based on empirical studies conducted by various scientists throughout the developing world.

Methodology: Research articles for the meta-analysis were selected using a thorough screening process based on the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) concept. Selected 94 articles were sub-divided in to three main agriculture sub-sectors for detailed analysis; (a) paddy, other field crops-OFC and vegetables, (b) fruits, and (c) livestock. Mean TE of each crop or livestock type was calculated by averaging the TE values for a particular crop or livestock type across different studies included in this study.

Results: TE data presented in the original articles showed a considerable dispersion within a given study. The highest mean TE was recorded in B-onion (0.83±0.15) whereas the lowest was recorded in maize (0.703±0.09) and in soybean (0.705±0.13). The TE of chili cultivation was 0.78 with the greatest variability (standard error of mean [SEM] 0.19) among the crops considered, which signifies the unpredictable nature of the chili cultivation. Mango was found to be the least technically efficient crop among the studied, with a mean TE of 0.596±0.11. Dairy, poultry and aquaculture farming operations were found to be highly technically efficient having mean TE values of 0.80±0.16, 0.89±0.02 and 0.88±0.08 respectively.

Conclusion: Findings of this study will lead to several key policy implications including, improvement of the socioeconomic characteristics of farmers, implementation of farmer field schools (FFS) and establishment of a cautious and gradual strategy for expansion of the rural financial institutions.
The potential of cord blood to replenish young immune cells against cancer
Authors: Li Xiaoyang , Cheng Lin , Li Junmin , Ren Ruibao
Published: June 2021

The immune system of elderly individuals behaves differently from young adults, leading to a general assumption that the decline of immune system function increases the susceptibility to infectious and noninfectious diseases. This age‐related internal immune function failure, termed "immune senescence," contributes to the increment of morbidity and mortality associated with diseases in elderly populations. Cord blood is considered as a source of “young” immune cells for anti‐infectious immunity and adoptive cancer immunotherapy. In this review, we describe immune aging and the application of cord blood for replenishing aging immune cells against neoplastic diseases.
Does writing enhance recall and memory consolidation? Revealing the factor of effectiveness of the self‐administered interview
Authors: Miura Hiroshi , Matsuo Kayo
Published: June 2021

The self‐administered interview (SAI©) is a booklet in which eyewitnesses write down their memories of an incident without assistance. The SAI can gather a significant amount of eyewitness information, and completing the SAI soon after witnessing an event can improve later recall. This study aimed to reveal the factor of effectiveness of the SAI and specifically focused on the method of handwriting. Participants watched a video and immediately recalled the event in the three conditions: SAI‐writing, SAI‐speaking, and free recall (speaking). One week later, participants again recalled the event via free recall. The results showed that participants in the SAI‐writing condition reported more correct information than those in the other conditions at both time points. This suggests that a factor of effectiveness of the SAI is the method of writing. Thus, initial written recall using the SAI could facilitate later recall in police investigative interviews.
Feasibility of a deep learning‐based algorithm for automated detection and classification of nasal polyps and inverted papillomas on nasal endoscopic images
Authors: Girdler Benton , Moon Hyun , Bae, Mi Rye , Ryu Sung Seok , Bae Jihye , Yu Myeong Sang
Published: June 2021

Background

Discrimination of nasal cavity mass lesions is a challenging work requiring extensive experience. A deep learning‐based automated diagnostic system may help clinicians to classify nasal cavity mass lesions. We demonstrated the feasibility of a convolutional neural network (CNN)‐based diagnosis system for automatic detection and classification of nasal polyps (NP) and inverted papillomas (IP).

Methods

We developed a CNN‐based algorithm using a transfer learning strategy and trained it on nasal endoscopic images. A total of 99 nasal endoscopic images with normal findings, 98 images with NP, and 100 images with IP were analyzed using the developed CNN. Six otolaryngologists participated in clinical visual assessment. Image‐based classification performance was measured by calculating the accuracy and area under the receiver operating characteristic curve (AUC). The diagnostic performance was compared between the CNN and clinical visual assessment by human experts.

Results

The algorithm achieved an overall accuracy of 0.742 ± 0.058 with the following class accuracies: normal, 0.81± 0.14; IP, 0.57 ± 0.07; and NP, 0.83 ± 0.21. The AUC values for normal, IP, and NP were 0.91 ± 0.06, 0.82 ± 0.09, and 0.84 ± 0.06, respectively. The overall accuracy of the CNN model was comparable with the average performance of human experts (0.742 vs. 0.749; p = 0.11).

Conclusions

The trained CNN model appears to reliably classify NP and IP of the nasal cavity from nasal endoscopic images; it also yields a reliable reference for diagnosing nasal cavity mass lesions during nasal endoscopy. However, further studies with more test data are warranted to improve the diagnostic accuracy of our CNN model.