bluuebunny/crossref_metadata_2025 huggingface dataset:
LSTM DSS Automatism and Dataset Optimization for Diabetes Prediction
Authors: Massaro Alessandro , Maritati Vincenzo , Giannone Daniele , Convertini Daniele , Galiano Angelo
Published: August 2019

The paper is focused on the application of Long Short-Term Memory (LSTM) neural network enabling patient health status prediction focusing the attention on diabetes. The proposed topic is an upgrade of a Multi-Layer Perceptron (MLP) algorithm that can be fully embedded into an Enterprise Resource Planning (ERP) platform. The LSTM approach is applied for multi-attribute data processing and it is integrated into an information system based on patient management. To validate the proposed model, we have adopted a typical dataset used in the literature for data mining model testing. The study is focused on the procedure to follow for a correct LSTM data analysis by using artificial records (LSTM-AR-), improving the training dataset stability and test accuracy if compared with traditional MLP and LSTM approaches. The increase of the artificial data is important for all cases where only a few data of the training dataset are available, as for more practical cases. The paper represents a practical application about the LSTM approach into the decision support systems (DSSs) suitable for homecare assistance and for de-hospitalization processes. The paper goal is mainly to provide guidelines for the application of LSTM neural network in type I and II diabetes prediction adopting automatic procedures. A percentage improvement of test set accuracy of 6.5% has been observed by applying the LSTM-AR- approach, comparing results with up-to-date MLP works. The LSTM-AR- neural network can be applied as an alternative approach for all homecare platforms where not enough training sequential dataset is available.
A Dedicated Design Strategy for Active Boring Bar
Authors: Grossi Niccolò , Croppi Lisa , Scippa Antonio , Campatelli Gianni
Published: August 2019

Unstable vibrations (i.e., chatter) onset is one of the main limits to productivity in deep boring bar processes. Active damping systems allow to increase machining stability in different configurations (i.e., tool setup), without requiring cutting system dynamic characterization. Design of an active boring bar involves the development of monitoring system (sensors), actuation system and control logic. While several control logics were evaluated and discussed, few design solutions were presented in the literature, focusing only on building prototypes to demonstrate control logic effectiveness. In the presented work, a deep analysis of the main issues and requirements related to active boring design was carried out and a systematic approach to tackle all the critical aspects was developed. The results of the proposed method are: (i) optimal actuators positioning able to damp vibration along two directions; (ii) preload system design guaranteeing the correct actuator preloading for the operating conditions; (iii) covers design to protect actuators and ensure the dynamic and static equivalence between active and standard boring bar. Following this approach, an active boring bar was designed, realized and tested. The results prove the required equivalence between active and original boring bar and assess the damping effect.
A Brief Review about the Role of Nanomaterials, Mineral-Organic Nanoparticles, and Extra-Bone Calcification in Promoting Carcinogenesis and Tumor Progression
Authors: Senchukova Marina
Published: August 2019

People come in contact with a huge number of nanoparticles (NPs) throughout their lives, which can be of both natural and anthropogenic origin and are capable of entering the body through swallowing, skin penetration, or inhalation. In connection with the expanding use of nanomaterials in various industrial processes, the question of whether there is a need to study the potentially adverse effects of NPs on human health becomes increasingly important. Despite the fact that the nature and the extent of damage caused depends on the chemical and the physical characteristics of individual NPs, there are also general mechanisms related to their toxicity. These mechanisms include the ability of NPs to translocate to various organs through endocytosis, as well as their ability to stimulate the production of reactive oxygen species (ROS), leading to oxidative stress, inflammation, genotoxicity, metabolic changes, and potentially carcinogenesis. In this review, we discuss the main characteristics of NPs and the effects they cause at both cellular and tissue levels. We also focus on possible mechanisms that underlie the relationship of NPs with carcinogenesis. We briefly summarize the main concepts related to the role of endogenous mineral organic NPs in the development of various human diseases and their participation in extra-bone calcification. Considering data from both our studies and those published in scientific literature, we propose the revision of some ideas concerning extra-bone calcification, since it may be one of the factors associated with the initiation of the mechanisms of immunological tolerance.
Does Leadership Style Differ between a Post-Disaster and Non-Disaster Response Project? A Study of Three Major Projects in New Zealand
Authors: Witton Frederick , Rasheed Eziaku Onyeizu , Rotimi James Olabode Bamidele
Published: August 2019

Purpose–The leadership styles of three major infrastructure projects within New Zealand were determined and comparatively analysed to ascertain whether the leadership style employed in a post-disaster recovery project would differ significantly from a normal infrastructure project. A multifactor leadership questionnaire was administered to project leaders and personnel of the three infrastructure projects. The statistically significant differences (p < 0.05) in leadership styles were determined using one-way ANOVA analytical tool in STATISTICA 13. Results showed all three projects have strong transformational and transactional leadership traits. There were similarities in leadership style amongst the projects. None of the projects had a significant laissez-faire leadership style. Hence there is no significant difference in leadership style between a disaster recovery project and a normal project. Plausible reasons and implications are provided to support these findings. This study provides insight into leadership styles employed in projects in New Zealand, which could assist in the decision-making process for new and existing projects. Future studies could investigate the effect a combination of leadership styles will have on project success and staff retention. More studies are required across New Zealand to verify the generalizability of the current study findings.
Three-Dimensional Couette Flow of a Second-Grade Fluid Along Periodic Injection/Suction
Authors: Afzal Rana Muhammad , Ali Yasar , Ahmad Babar , Afzal Rana Muhammad Touseef
Published: August 2019

This work explores the three-dimensional laminar flow of an incompressible second-grade fluid between two parallel infinite plates. The assumed suction velocity comprises a basic steady dispersal with a superimposed weak transversally fluctuating distribution. Because of variation of suction velocity in transverse direction on the wall, the problem turns out to be three-dimensional. Analytic solutions for velocity field, pressure and skin friction are presented and effects of dimensionless parameters emerging in the model are discussed. It is observed that the non-Newtonian parameter plays dynamic part to rheostat the velocity component along main flow direction.
An Intelligent Computer-Aided Scheme for Classifying Multiple Skin Lesions
Authors: Hameed Nazia , Hameed Fozia , Shabut Antesar , Khan Sehresh , Cirstea Silvia , Hossain Alamgir
Published: August 2019

Skin diseases cases are increasing on a daily basis and are difficult to handle due to the global imbalance between skin disease patients and dermatologists. Skin diseases are among the top 5 leading cause of the worldwide disease burden. To reduce this burden, computer-aided diagnosis systems (CAD) are highly demanded. Single disease classification is the major shortcoming in the existing work. Due to the similar characteristics of skin diseases, classification of multiple skin lesions is very challenging. This research work is an extension of our existing work where a novel classification scheme is proposed for multi-class classification. The proposed classification framework can classify an input skin image into one of the six non-overlapping classes i.e., healthy, acne, eczema, psoriasis, benign and malignant melanoma. The proposed classification framework constitutes four steps, i.e., pre-processing, segmentation, feature extraction and classification. Different image processing and machine learning techniques are used to accomplish each step. 10-fold cross-validation is utilized, and experiments are performed on 1800 images. An accuracy of 94.74% was achieved using Quadratic Support Vector Machine. The proposed classification scheme can help patients in the early classification of skin lesions.
Teaching Using Digital Technologies: Transmission or Participation?
Authors: Cutajar Maria
Published: August 2019

Digital technologies are becoming seamlessly incorporated in all we do, no less in teaching and learning. As technological developments and interdependent social change steer us deeper into a postdigital existence, higher education institutions are observed increasing the availability of learning technologies and related academic development initiatives. Alongside these developments, models of teaching as transmission are popularly criticized and set in contrast to models of teaching as participation, which are commended and avowed as more suited for the present day digital university. This paper presents the research findings of a qualitative study, which was specifically taken up in response to observed developments. The findings derive from phenomenographic analysis mapping variation in the accounts of 27 academics describing their experiences using digital technologies for teaching. These results represent a wide-ranging description confirming previous research findings and add new detail. They reaffirm teaching orientations of transmission and participation as important and significant facets of teaching moreover existing claims based on logical argumentation. These research results potentially serve professional development constructively supporting academics seeking to incorporate contemporary digital technologies in their teaching practices.
Machine Learning-Based Relay Selection for Secure Transmission in Multi-Hop DF Relay Networks
Authors: Nguyen Tien-Tung , Lee Jong-Ho , Nguyen Minh-Tuan , Kim Yong-Hwa
Published: August 2019

A relay selection method is proposed for physical-layer security in multi-hop decode-and-forward (DF) relaying systems. In the proposed method, cooperative relays are selected to maximize the achievable secrecy rates under DF-relaying constraints by the classification method. Artificial neural networks (ANNs), which are used for machine learning, are applied to classify the set of cooperative relays based on the channel state information of all nodes. Simulation results show that the proposed method can achieve near-optimal performance for an exhaustive search method for all combinations of relay selection, while computation time are reduced significantly. Furthermore, the proposed method outperforms the best relay selection method, in which the best relay in terms of secrecy performance is selected among active ones.
Short-Term Load Forecasting for CCHP Systems Considering the Correlation between Heating, Gas and Electrical Loads Based on Deep Learning
Authors: Zhu Ruijin , Guo Weilin , Gong Xuejiao
Published: August 2019

Combined cooling, heating, and power (CCHP) systems is a distributed energy system that uses the power station or heat engine to generate electricity and useful heat simultaneously. Due to its wide range of advantages including efficiency, ecological, and financial, the CCHP will be the main direction of the integrated system. The accurate prediction of heating, gas, and electrical loads plays an essential role in energy management in CCHP systems. This paper combined long short-term memory (LSTM) network and convolutional neural network (CNN) to design a novel hybrid neural network for short-term loads forecasting considering their correlation. Pearson correlation coefficient will be utilized to measure the temporal correlation between current load and historical loads, and analyze the coupling between heating, gas and electrical loads. The dropout technique is proposed to solve the over-fitting of the network due to the lack of data diversity and network parameter redundancy. The case study shows that considering the coupling between heating, gas and electrical loads can effectively improve the forecasting accuracy, the performance of the proposed approach is better than that of the traditional methods.
Electricity Theft Detection in Smart Grid Systems: A CNN-LSTM Based Approach
Authors: Hasan Md. Nazmul , Toma Rafia Nishat , Nahid Abdullah-Al , Islam M M Manjurul , Kim Jong-Myon
Published: August 2019

Among an electricity provider’s non-technical losses, electricity theft has the most severe and dangerous effects. Fraudulent electricity consumption decreases the supply quality, increases generation load, causes legitimate consumers to pay excessive electricity bills, and affects the overall economy. The adaptation of smart grids can significantly reduce this loss through data analysis techniques. The smart grid infrastructure generates a massive amount of data, including the power consumption of individual users. Utilizing this data, machine learning and deep learning techniques can accurately identify electricity theft users. In this paper, an electricity theft detection system is proposed based on a combination of a convolutional neural network (CNN) and a long short-term memory (LSTM) architecture. CNN is a widely used technique that automates feature extraction and the classification process. Since the power consumption signature is time-series data, we were led to build a CNN-based LSTM (CNN-LSTM) model for smart grid data classification. In this work, a novel data pre-processing algorithm was also implemented to compute the missing instances in the dataset, based on the local values relative to the missing data point. Furthermore, in this dataset, the count of electricity theft users was relatively low, which could have made the model inefficient at identifying theft users. This class imbalance scenario was addressed through synthetic data generation. Finally, the results obtained indicate the proposed scheme can classify both the majority class (normal users) and the minority class (electricity theft users) with good accuracy.
Fast Torque Computation of Hysteresis Motors and Clutches Using Magneto-static Finite Element Simulation
Authors: Gallicchio Gianvito , Palmieri Marco , Di Nardo Mauro , Cupertino Francesco
Published: August 2019

Hysteresis motor and clutches have several advantages, such as constant torque from zero to synchronous speed, low torque ripple, and low fabrication cost. Low efficiency and power factor are the main features that have limited the application of this type of electrical machine to few applications. Being a niche argument, little literature has addressed the problem of analytical and finite element (FE) modelling of hysteresis electrical machines. This paper first describes the most important contributions of the literature on the analytical and FE modelling of hysteresis motors and clutches and then proposes a method for the fast computation of its performance. The proposed procedure consists of two steps: first, a magneto-static FE simulation is performed considering the normal magnetization curve of the hysteresis material; then, the average torque is computed by a post-processing analysis. The proposed method is used to analyze a hysteresis clutch and the obtained results are compared with those achieved using a commercial finite element software that implements a vector hysteresis model.
Modeling a Large-Scale Battery Energy Storage System for Power Grid Application Analysis
Authors: Rancilio Giuliano , Lucas Alexandre , Kotsakis Evangelos , Fulli Gianluca , Merlo Marco , Delfanti Maurizio , Masera Marcelo
Published: August 2019

The interest in modeling the operation of large-scale battery energy storage systems (BESS) for analyzing power grid applications is rising. This is due to the increasing storage capacity installed in power systems for providing ancillary services and supporting nonprogrammable renewable energy sources (RES). BESS numerical models suitable for grid-connected applications must offer a trade-off, keeping a high accuracy even with limited computational effort. Moreover, they are asked to be viable in modeling for real-life equipment, and not just accurate in the simulation of the electrochemical section. The aim of this study is to develop a numerical model for the analysis of the grid-connected BESS operation; the main goal of the proposal is to have a test protocol based on standard equipment and just based on charge/discharge tests, i.e., a procedure viable for a BESS owner without theoretical skills in electrochemistry or lab procedures, and not requiring the ability to disassemble the BESS in order to test each individual component. The BESS model developed is characterized by an experimental campaign. The test procedure itself is framed in the context of this study and adopted for the experimental campaign on a commercial large-scale BESS. Once the model is characterized by the experimental parameters, it undergoes the verification and validation process by testing its accuracy in simulating the provision of frequency regulation. A case study is presented for the sake of presenting a potential application of the model. The procedure developed and validated is replicable in any other facility, due to the low complexity of the proposed experimental set. This could help stakeholders to accurately simulate several layouts of network services.
Modelling of Combustion Characteristics of a Single Curved-Cylinder Spark-Ignition Crank-Rocker Engine
Authors: Mohammed Salah E. , Baharom M. B. , A. Aziz A. Rashid , Zainal A. Ezrann Z.
Published: August 2019

A crank-rocker engine is a new invention used to convert oscillating motion from the curve-piston into the rotary motion of the crankshaft. The configuration of this new engine is different from the normal slider-crank engine, so the existing model used to calculate the combustion characteristic is not appropriate for this new engine. A fundamental thermodynamic model of a single curved-cylinder spark-ignition crank-rocker engine is presented. The model was simulated in MATLAB to predict the combustion characteristics at different operating conditions. The friction losses, residual gas fraction and combustion efficiency were introduced into the combustion model to improve the overall accuracy of the model. The developed model was used to analyze and evaluate the in-cylinder pressure, fuel burn rate, and heat release under various crank angle positions. To validate the predictions of the model, experimental tests were conducted on a single-cylinder crank-rocker engine at an engine speed of 2000 rpm, spark timing of 8.60 CA BTDC, full load and wide-open throttle (WOT) condition. Finally, the results were plotted and compared with the simulation results. The findings obtained from the current study have shown the ability of the simulation model to predict the combustion characteristics under different operating conditions. The agreement between the results of the present model and experimental data was reasonably good. This research work proposes a new model which can predict the behavior of the crank-rocker engine. The information gained from this study will aid in the tuning process and future development of this engine.
Preparation and Characterization of Novel Plaster with Improved Thermal Energy Storage Performance
Authors: Fořt Jan , Novotný Radimír , Trník Anton , Černý Robert
Published: August 2019

Thermal energy storage systems based on latent heat utilization represent a promising way to achieve building sustainability and energy efficiency. The application of phase change materials (PCMs) can substantially improve the thermal performance of building envelopes, decrease the energy consumption, and support the thermal comfort maintenance, especially during peak periods. On this account, the newly formed form-stable PCM (FSPCM) based on diatomite impregnated by dodecanol is used as an admixture for design of interior plasters with enhanced thermal storage capability. In this study, the effect of FSPCM admixture on functional properties of plasters enriched by 8, 16 and 24 wt.% is determined. On this account, the assessment of physical, thermal, hygric, and mechanical properties is done in order to correlate obtained results with applied FSPCM dosages. Achieved results reveal only a minor influence of applied FSPCM admixture on material properties when compared to negative impacts of commercially produced PCMs. The differential scanning calorimetry discloses variations of the phase change temperature, which ranging from 20.75 °C to 21.68 °C and the effective heat capacity increased up to 15.38 J/g accordingly to the applied FSPCM dosages.
Does Inoculation with Arbuscular Mycorrhizal Fungi Reduce Trunk Disease in Grapevine Rootstocks?
Authors: Holland Taylor , Bowen Patricia , Kokkoris Vasilis , Urbez-Torres Jose Ramon , Hart Miranda
Published: August 2019

Ilyonectria is a weak pathogen known for causing black foot disease in young vines, infecting roots and vascular tissues at the basal end of the rootstock and restricting the movement of water and nutrients. This negatively impacts vine establishment during transplant into the vineyard. Arbuscular mycorrhizal (AM) fungi are symbiotic fungi that associate with most plants and have been shown to mitigate the infection and effect of pathogens. This greenhouse study was designed to determine if the mycorrhizal fungi could mitigate Ilyonectria infection and whether this was dependent on inoculation timing. ‘Riparia gloire’ grapevine rootstocks (Vitis riparia) were infected with Ilyonectria either after AM fungi, at the same time as AM fungi, or to roots that were not inoculated by AM fungi. We measured the abundance using specific markers for both the pathogen and AM fungi. Colonization by AM fungi did not suppress Ilyonectria, but instead increased the abundance of Ilyonectria. Further, mycorrhizal rootstocks did not have enhanced growth effects on physiological parameters when compared to non-mycorrhizal rootstocks. These findings stand in contrast to the general perception that AM fungi provide protection against root pathogens.
Brain–Barrier Regulation, Metal (Cu, Fe) Dyshomeostasis, and Neurodegenerative Disorders in Man and Animals
Authors: Haywood Susan
Published: August 2019

The neurodegenerative diseases (Alzheimers, Parkinsons, amyotrophic lateral sclerosis, Huntingtons) and the prion disorders, have in common a dysregulation of metalloprotein chemistry involving redox metals (Cu, Fe, Mn). The consequent oxidative stress is associated with protein plaques and neuronal cell death. An equilibrium exists between the functional requirement of the brain for Cu and Fe and their destructive potential with the production of reactive oxygen species. The importance of the brain barrier is highlighted in regulating the import of these metals. Upregulation of key transporters occurs in fetal and neonatal life when brain metal requirement is high, and is downregulated in adult life when need is minimal. North Ronaldsay sheep are introduced as an animal model in which a neonatal mode of CTR1 upregulation persists into adulthood and leads to the premise that metal regulation may return to this default setting in ageing, with implications for the neurodegenerative diseases.
The Effect of a Virtual-Reality Full-Body Illusion on Body Representation in Obesity
Authors: Scarpina Federica , Serino Silvia , Keizer Anouk , Chirico Alice , Scacchi Massimo , Castelnuovo Gianluca , Mauro Alessandro , Riva Giuseppe
Published: August 2019

Background. The effective illusory ownership over an artificial body in modulating body representations in healthy and eating disorders population has been repeatedly reported in recent literature. In this study, we extended this research in the field of obesity: specifically, we investigated whether ownership over a virtual body with a skinny abdomen might be successfully experienced by participants affected by obesity. Methods. Fifteen participants with obesity and fifteen healthy-weight participants took part at this study in which the VR-Full-Body Illusion was adopted. The strength of illusion was investigated through the traditional Embodiment Questionnaire, while changes in bodily experience were measured through a body size estimation task. Results. Participants with obesity as well as healthy-weight participants reported to experience the illusion. About the body size estimation task, both groups reported changes only in the estimation of the abdomen’s circumference after the experimental condition, in absence of any another difference. Discussion. Participants with obesity reported to experience the illusion over a skinny avatar, but the modulation of the bodily experience seems controversial. Future lines of research exploiting this technique for modulating body representations in obesity, specifically in terms of potential therapeutic use, were discussed.
The Hydrodynamic Dispersion Characteristics of Coral Sands
Authors: Cui Xiang , Zhu Changqi , Hu Mingjian , Wang Xinzhi , Liu Haifeng
Published: August 2019

Dispersion characteristics are important factors affecting groundwater solute transport in porous media. In marine environments, solute dispersion leads to the formation of freshwater aquifers under islands. In this study, a series of model tests were designed to explore the relationship between the dispersion characteristics of solute in calcareous sands and the particle size, degree of compactness, and gradation of porous media, with a discussion of the types of dispersion mechanisms in coral sands. It was found that the particle size of coral sands was an important parameter affecting the dispersion coefficient, with the dispersion coefficient increasing with particle size. Gradation was also an important factor affecting the dispersion coefficient of coral sands, with the dispersion coefficient increasing with increasing d10. The dispersion coefficient of coral sands decreased approximately linearly with increasing compactness. The rate of decrease was −0.7244 for single-grained coral sands of particle size 0.25–0.5 mm. When the solute concentrations and particle sizes increased, the limiting concentration gradients at equilibrium decreased. In this study, based on the relative weights of molecular diffusion versus mechanical dispersion under different flow velocity conditions, the dispersion mechanisms were classified into five types, and for each type, a corresponding flow velocity limit was derived.
Whole Genome Sequencing of the Giant Grouper (Epinephelus lanceolatus) and High-Throughput Screening of Putative Antimicrobial Peptide Genes
Authors: Wang Dengdong , Chen Xiyang , Zhang Xinhui , Li Jia , Yi Yunhai , Bian Chao , Shi Qiong , Lin Haoran , Li Shuisheng , Zhang Yong , You Xinxin
Published: August 2019

Giant groupers, the largest grouper type in the world, are of economic importance in marine aquaculture for their rapid growth. At the same time, bacterial and viral diseases have become the main threats to the grouper industry. Here, we report a high-quality genome of a giant grouper sequenced by an Illumina HiSeq X-Ten and PacBio Bioscience Sequel platform. A total of 254 putative antimicrobial peptide (AMP) genes were identified, which can be divided into 34 classes according to the annotation of the Antimicrobial Peptides Database (APD3). Their locations in pseudochromosomes were also determined. Thrombin-, lectin-, and scolopendin-derived putative AMPs were the three largest parts. In addition, expressions of putative AMPs were measured by our transcriptome data. Two putative AMP genes (gapdh1 and gapdh2) were involved in glycolysis, which had extremely high expression levels in giant grouper muscle. As it has been reported that AMPs inhibit the growth of a broad spectrum of microbes and participate in regulating innate and adaptive immune responses, genome sequencing of this study provides a comprehensive cataloging of putative AMPs of groupers, supporting antimicrobial research and aquaculture therapy. These genomic resources will be beneficial to further molecular breeding of this economically important fish.
Structure, Function, and Therapeutic Potential of Marine Bioactive Peptides
Authors: Ovchinnikova Tatiana V.
Published: August 2019

In recent years, bioactive peptides from marine organisms have gained increasing attention in the field of pharmaceutical, cosmeceutical, and nutraceutical product development owing to their interesting biological properties [...]
Calcific Myonecrosis of the Leg: A Rare Entity
Authors: Angelini Andrea , Mavrogenis Andreas F. , Pagliarini Elisa , Trovarelli Giulia , Fanelli Giuseppe Nicolò , Cappellesso Rocco , Ruggieri Pietro
Published: August 2019

Calcific myonecrosis is a rare disease that has been shown to be a late sequela of trauma. This article presents a 68-year-old man with calcific myonecrosis of the leg 40 years after a tibial fracture complicated with peroneal nerve palsy. The soft tissue mass increased in size after another injury to the leg that occurred two years before his presentation. Physical examination at presentation showed a palpable extra-osseous mass at the anterior aspect of the left leg; the mass was not adherent to adjacent soft-tissues and bone, and it was painless but tender to palpation. Radiographs of the left leg showed extensive calcification at the soft-tissue of the anterior and posterior leg. An ultrasonography-guided trocar biopsy was done; histological findings were indicative of calcific myonecrosis. Given the benign entity of the lesion and known high rate of complications, he was recommended for no further treatment except for clinical and imaging observation. Located at the site of the biopsy, he experienced infection with drainage that eventually healed after six months with antibiotics and wound dressing changes. During the last follow-up examination, two years after diagnosis, the patient was asymptomatic without progression of the mass.
Heterologous Hyaluronic Acid Production in Kluyveromyces lactis
Authors: V. Gomes Antonio M. , C. M. Netto João H. , Carvalho Lucas S. , Parachin Nádia S.
Published: August 2019

Hyaluronic Acid (HA) is a biopolymer composed by the monomers Glucuronic Acid (GlcUA) and N-Acetyl Glucosamine (GlcNAc). It has a broad range of applications in the field of medicine, being marketed between USD 1000–5000/kg. Its primary sources include extraction of animal tissue and fermentation using pathogenic bacteria. However, in both cases, extensive purification protocols are required to prevent toxin contamination. In this study, aiming at creating a safe HA producing microorganism, the generally regarded as safe (GRAS) yeast Kluyveroymyces lactis is utilized. Initially, the hasB (UDP-Glucose dehydrogenase) gene from Xenopus laevis (xlhasB) is inserted. After that, four strains are constructed harboring different hasA (HA Synthase) genes, three of humans (hshasA1, hshasA2, and hshasA3) and one with the bacteria Pasteurella multocida (pmhasA). Transcript values analysis confirms the presence of hasA genes only in three strains. HA production is verified by scanning electron microscopy in the strain containing the pmHAS isoform. The pmHAS strain is grown in a 1.3 l bioreactor operating in a batch mode, the maximum HA levels are 1.89 g/L with a molecular weight of 2.097 MDa. This is the first study that reports HA production in K. lactis and it has the highest HA titers reported among yeast.
Elizabethkingia Infections in Humans: From Genomics to Clinics
Authors: Lin Jiun-Nong , Lai Chung-Hsu , Yang Chih-Hui , Huang Yi-Han
Published: August 2019

The genus Elizabethkingia has recently emerged as a cause of life-threatening infections in humans, particularly in immunocompromised patients. Several new species in the genus Elizabethkingia have been proposed in the last decade. Numerous studies have indicated that Elizabethkingia anophelis, rather than Elizabethkingia meningoseptica, is the most prevalent pathogen in this genus. Matrix-assisted laser desorption/ionization–time of flight mass spectrometry systems with an extended spectrum database could reliably identify E. anophelis and E. meningoseptica, but they are unable to distinguish the remaining species. Precise species identification relies on molecular techniques, such as housekeeping gene sequencing and whole-genome sequencing. These microorganisms are usually susceptible to minocycline but resistant to most β-lactams, β-lactam/β-lactam inhibitors, carbapenems, and aminoglycosides. They often exhibit variable susceptibility to piperacillin, piperacillin-tazobactam, fluoroquinolones, and trimethoprim-sulfamethoxazole. Accordingly, treatment should be guided by antimicrobial susceptibility testing. Target gene mutations are markedly associated with fluoroquinolone resistance. Knowledge on the genomic characteristics provides valuable insights into in these emerging pathogens.
Contemporary Strategies and Current Trends in Designing Antiviral Drugs against Dengue Fever via Targeting Host-Based Approaches
Authors: Ahammad Foysal , Tengku Abd Rashid Tengku Rogayah , Mohamed Maizan , Tanbin Suriyea , Ahmad Fuad Fazia Adyani
Published: August 2019

Dengue virus (DENV) is an arboviral human pathogen transmitted through mosquito bite that infects an estimated ~400 million humans (~5% of the global population) annually. To date, no specific therapeutics have been developed that can prevent or treat infections resulting from this pathogen. DENV utilizes numerous host molecules and factors for transcribing the single-stranded ~11 kb positive-sense RNA genome. For example, the glycosylation machinery of the host is required for viral particles to assemble in the endoplasmic reticulum. Since a variety of host factors seem to be utilized by the pathogens, targeting these factors may result in DENV inhibitors, and will play an important role in attenuating the rapid emergence of other flaviviruses. Many experimental studies have yielded findings indicating that host factors facilitate infection, indicating that the focus should be given to targeting the processes contributing to pathogenesis along with many other immune responses. Here, we provide an extensive literature review in order to elucidate the progress made in the development of host-based approaches for DENV viral infections, focusing on host cellular mechanisms and factors responsible for viral replication, aiming to aid the potential development of host-dependent antiviral therapeutics.
Fangchinoline, a Bisbenzylisoquinoline Alkaloid can Modulate Cytokine-Impelled Apoptosis via the Dual Regulation of NF-κB and AP-1 Pathways
Authors: Jung Young Yun , Shanmugam Muthu K. , Chinnathambi Arunachalam , Alharbi Sulaiman Ali , Shair Omar H.M. , Um Jae-Young , Sethi Gautam , Ahn Kwang Seok
Published: August 2019

Fangchinoline (FCN) derived from Stephaniae tetrandrine S. Moore can be employed to treat fever, inflammation, rheumatism arthralgia, edema, dysuria, athlete’s foot, and swollen wet sores. FCN can exhibit a plethora of anti-neoplastic effects although its precise mode of action still remains to be deciphered. Nuclear factor-κB (NF-κB) and activator protein-1 (AP-1) can closely regulate carcinogenesis and thus we analyzed the possible action of FCN may have on these two signaling cascades in tumor cells. The effect of FCN on NF-κB and AP-1 signaling cascades and its downstream functions was deciphered using diverse assays in both human chronic myeloid leukemia (KBM5) and multiple myeloma (U266). FCN attenuated growth of both leukemic and multiple myeloma cells and repressed NF-κB, and AP-1 activation through diverse mechanisms, including attenuation of phosphorylation of IκB kinase (IKK) and p65. Furthermore, FCN could also cause significant enhancement in TNFα-driven apoptosis as studied by various molecular techniques. Thus, FCN may exhibit potent anti-neoplastic effects by affecting diverse oncogenic pathways and may be employed as pro-apoptotic agent against various malignancies.
Effects of Complex DNA and MVs with GTF Extracted from Streptococcus mutans on the Oral Biofilm
Authors: Senpuku Hidenobu , Nakamura Tomoyo , Iwabuchi Yusuke , Hirayama Satoru , Nakao Ryoma , Ohnishi Makoto
Published: August 2019

Streptococcus mutans is one of the principal pathogens for the development of dental caries. Oral biofilms formed by S. mutans are constructed of insoluble glucan formation induced by the principal enzymes, GTF-I and GTF-SI, in sucrose-containing conditions. However, as another means of biofilm formation, extracellular DNA (eDNA) and membrane vesicles (MVs) are also contributors. To explore the roles of eDNA and MVs for biofilm formation, short and whole size pure DNAs, two types of sub-purified DNAs and MVs were extracted from S. mutans by beads destruction, treatment of proteinase K, and ultracentrifugation of culture supernatant, and applied into the biofilm formation assay using the S. mutans UA159 gtfBC mutant, which lost GTF-I and GTF-SI, on a human saliva-coated 96 well microtiter plate in sucrose-containing conditions. Sub-purified DNAs after cell lysis by beads destruction for total 90 and 180 s showed a complex form of short-size DNA with various proteins and MVs associated with GTF-I and GTF-SI, and induced significantly higher biofilm formation of the S. mutans UA159.gtfBC mutant than no sample (p < 0.05). Short-size pure DNA without proteins induced biofilm formation but whole-size pure DNA did not. Moreover, the complex form of MV associated with GTFs and short-size DNA showed significantly higher biofilm formation of initial colonizers on the human tooth surface such as Streptococcus mitis than no sample (p < 0.05). The short-size DNAs associated with MVs and GTFs are important contributors to the biofilm formation and may be one of additional targets for the prevention of oral biofilm-associated diseases.
Rethinking the Future of Food Packaging: Biobased Edible Films for Powdered Food and Drinks
Authors: Puscaselu Roxana , Gutt Gheorghe , Amariei Sonia
Published: August 2019

In today’s society, packaging is essential. Without this, the materials would be messy and ineffective. Despite the importance and key role of packaging, they are considered to be useless, as consumers see it as a waste of resources and an environmental threat. Biopolymer-based edible packaging is one of the most promising solutions to these problems. Thus, inulin, biopolymers such as agar and sodium alginate, and glycerol were used to develop a single use edible material for food packaging. These biofilms were obtained and tested for three months. For inulin-based films, the results highlight improvements not only in physical properties (homogeneity, well-defined margins, light sweet taste, good optical properties, high solubility capacity or, as in the case of some samples, complete solubilization), but also superior mechanical properties (samples with high inulin content into composition had high tensile strength and extremely high elongation values). Even after three months of developing, the values of mechanical properties indicate a strong material. The optimization establishes the composition necessary to obtain a strong and completely water-soluble material. This type of packaging represents a successful alternative for the future of food packaging: they are completely edible, biodegradable, compostable, obtained from renewable resources, and produce zero waste, at low cost.
Intrinsic Thermal Shock Behavior of Common Rutile Oxides
Authors: Music Denis , Stelzer Bastian
Published: August 2019

Rutile TiO2, VO2, CrO2, MnO2, NbO2, RuO2, RhO2, TaO2, OsO2, IrO2, SnO2, PbO2, SiO2, and GeO2 (space group P42/mnm) were explored for thermal shock resistance applications using density functional theory in conjunction with acoustic phonon models. Four relevant thermomechanical properties were calculated, namely thermal conductivity, Poisson’s ratio, the linear coefficient of thermal expansion, and elastic modulus. The thermal conductivity exhibited a parabolic relationship with the linear coefficient of thermal expansion and the extremes were delineated by SiO2 (the smallest linear coefficient of thermal expansion and the largest thermal conductivity) and PbO2 (vice versa). It is suggested that stronger bonding in SiO2 than PbO2 is responsible for such behavior. This also gave rise to the largest elastic modulus of SiO2 in this group of rutile oxides. Finally, the intrinsic thermal shock resistance was the largest for SiO2, exceeding some of the competitive phases such as Al2O3 and nanolaminated Ti3SiC2.
Economic Dispatch of Multi-Energy System Considering Load Replaceability
Authors: Zheng Tao , Dai Zemei , Yao Jiahao , Yang Yufeng , Cao Jing
Published: August 2019

By integrating gas, electricity, and cooling and heat networks, multi-energy system (MES) breaks the bondage of isolated planning and operation of independent energy systems. Appropriate scheduling of MES is critical to the operational economy, and it is essential to design scheduling strategies to achieve maximum economic benefits. In addition to the emergence of energy conversion systems, the other main novelty of MES is the multivariate of load, which offers a great optimization potential by changing load replaceability (flexibly adjusting the composition of loads). In this paper, by designing load replaceability index (LRI) of composite load in MES, its interaction mechanism with scheduling optimum is systematically analyzed. Through case studies, it is proven that the optimum can be improved by elevating load replaceability.
The Impact of Equilibrium Gas Pressure and Coal Particle Size on Gas Dynamic Diffusion in Coal
Authors: Li Chengwu , Nie Yao , Tian Jianwei , Zhao Yuechao , Zhang Xiaoqian
Published: August 2019

The diffusion coefficient of gases in coal varies with time. This study aims to develop an unsteady dynamic diffusion (UDD) model based on the decay of diffusion coefficient with time and the change of integral. This study conducted a series of gas desorption and diffusion experiments with three different combinations of particle sizes and gas pressures and compared the diffusion coefficients of the three models. The UDD model exhibited good fitting results, and both the UDD and bidisperse models fitted the experimental data better than the unipore model. In addition, the dynamic diffusion coefficient (DDe) decreased rapidly in the initial stage but gradually decreased to a stable level in the later stage. All the effective diffusion coefficients of the three models negatively correlated with the particle size. In the unipore model, the diffusion coefficient of coal samples with three particle sizes increased with gas pressure. In the bidisperse and UDD models, the diffusion coefficients (Dae, Die, and DDe) of 0.25–0.5 mm and 0.5–1.0 mm coal samples increased with gas pressure. However, DDe and Dae of 1.0–1.25 mm coal samples increased first and then decreased. Furthermore, Die decreased first and then increased, with no sign of significant pressure dependence. Finally, the correlation and significance between the constant and diffusion coefficient in the UDD model was investigated.
RETRACTED: A Sugarcane-Bagasse-Based Adsorbent Employed for Mitigating Eutrophication Threats and Producing Biodiesel Simultaneously
Authors: Wan Basri Wan , Daud Hanita , Lam Man , Cheng Chin , Oh Wen , Tan Wen , Shaharun Maizatul , Yeong Yin , Paman Ujang , Kusakabe Katsuki , Abdul Kadir Evizal , Show Pau , Lim Jun
Published: August 2019

Eutrophication is an inevitable phenomenon, and it has recently become an unabated threat. As a positive, the thriving microalgal biomass in eutrophic water is conventionally perceived to be loaded with myriad valuable biochemical compounds. Therefore, a sugarcane-bagasse-based adsorbent was proposed in this study to harvest the microalgal biomass for producing biodiesel. By activating the sugarcane-bagasse-based adsorbent with 1.5 M of H2SO4, a highest adsorption capacity of 108.9 ± 0.3 mg/g was attained. This was fundamentally due to the surface potential of the 1.5 M H2SO4 acid-modified sugarcane-bagasse-based adsorbent possessing the lowest surface positivity value as calculated from its point of zero charge. The adsorption capacity was then improved to 192.9 ± 0.1 mg/g by stepwise optimizing the adsorbent size to 6.7–8.0 mm, adsorption medium pH to 2–4, and adsorbent dosage to 0.4 g per 100 mL of adsorption medium. This resulted in 91.5% microalgae removal efficiency. Excellent-quality biodiesel was also obtained as reflected by the fatty acid methyl ester (FAME) profile, showing the dominant species of C16–C18 encompassing 71% of the overall FAMEs. The sustainability of harvesting microalgal biomass via an adsorption-enhanced flocculation processes was also evidenced by the potentiality to reuse the spent acid-modified adsorbent.
Melt Conditioned Direct Chill (MC-DC) Casting of AA-6111 Aluminium Alloy Formulated from Incinerator Bottom Ash (IBA)
Authors: Al-Helal Kawther W , Lazaro-Nebreda Jaime , Patel Jayesh B , Scamans Geoff M , Fan Zhongyun
Published: August 2019

The melt conditioned direct chill (MC-DC) casting process has been used for the production of billets of AA-6111 alloy formulated from recycled aluminium derived from incinerator bottom ash (IBA). The billets were homogenised and then extruded into planks. Optical metallography of the MC-DC billets showed equiaxed refined grains in comparison to DC and grain refined (DC-GR) billets formulated from the same scrap source. Microstructure evaluation for the extruded planks showed a less extensive peripheral coarse grain (PCG) for the MC-DC sample.