bluuebunny/crossref_metadata_2025 huggingface dataset:
Precipitation and Temperature in Costa Rica at the End of the Century Based on NEX-GDDP Projected Scenarios
Authors: Castillo Rodrigo , Amador Jorge A.
Published: December 2020

The evaluation of intraseasonal, seasonal, and annual variability of rainfall and temperature extremes, while using climate change scenarios data, is extremely important for socio-economic activities, such as water resources management. Costa Rica, a climate change hotspot, is largely dependent on rainfall for socioeconomic activities; hence, the relevance of this study. Based on the NEX-GDDP, rainfall and temperature range were analyzed for Costa Rica at the end of the century (2070–2099), while using 1970–1999 as a baseline for six available meteorological stations. Differences between the multimodel ensembles of two prospective scenarios (RCP 4.5 and 8.5) and the historical information were computed. This study highlights Costa Rica as an inflexion region for climate change impacts in Central America, for which projected scenarios suggest an early onset of the rainy season, and a decline in the mid-summer drought (MSD) minimum. The assessment of model data in some regions of Costa Rica, for which historical data were available, suggests that the latter does not capture a well-known regional climate feature, the MSD, in both precipitation and temperature range well. The availability of observed past data sources is a major limitation of this research; however, with the station data used, it is still possible to draw some conclusions regarding future climate in some regions of Costa Rica, especially in the northwest side of the country, where past data are consistent with model information, providing a more reliable picture of changes in climate there that has potential implications for socioeconomic sectors.
Collimated Microbeam Reveals that the Proportion of Non-Damaged Cells in Irradiated Blastoderm Determines the Success of Development in Medaka (Oryzias latipes) Embryos
Authors: Yasuda Takako , Funayama Tomoo , Nagata Kento , Li Duolin , Endo Takuya , Jia Qihui , Suzuki Michiyo , Ishikawa Yuji , Mitani Hiroshi , Oda Shoji
Published: December 2020

It has been widely accepted that prenatal exposure to ionizing radiation (IR) can affect embryonic and fetal development in mammals, depending on dose and gestational age of the exposure, however, the precise machinery underlying the IR-induced disturbance of embryonic development is still remained elusive. In this study, we examined the effects of gamma-ray irradiation on blastula embryos of medaka and found transient delay of brain development even when they hatched normally with low dose irradiation (2 and 5 Gy). In contrast, irradiation of higher dose of gamma-rays (10 Gy) killed the embryos with malformations before hatching. We then conducted targeted irradiation of blastoderm with a collimated carbon-ion microbeam. When a part (about 4, 10 and 25%) of blastoderm cells were injured by lethal dose (50 Gy) of carbon-ion microbeam irradiation, loss of about 10% or less of blastoderm cells induced only the transient delay of brain development and the embryos hatched normally, whereas embryos with about 25% of their blastoderm cells were irradiated stopped development at neurula stage and died. These findings strongly suggest that the developmental disturbance in the IR irradiated embryos is determined by the proportion of severely injured cells in the blastoderm.
Identification and Spatiotemporal Expression of Adenosine Deaminases Acting on RNA (ADAR) during Earthworm Regeneration: Its Possible Implication in Muscle Redifferentiation
Authors: Yoon Yoo Bin , Yu Yun-Sang , Park Beom Jun , Cho Sung-Jin , Park Soon Cheol
Published: December 2020

Adenosine deaminases acting on RNA (ADAR) catalyze the hydrolytic deamination of adenosine (A) to produce inosine (I) in double-stranded RNA substrates. A-to-I RNA editing has increasingly broad physiological significance in development, carcinogenesis, and environmental adaptation. Perionyx excavatus is an earthworm with potent regenerative potential; it can regenerate the head and tail and is an advantageous model system to investigate the molecular mechanisms of regeneration. During RNA sequencing analysis of P. excavatus regenerates, we identified an ADAR homolog (Pex-ADAR), which led us to examine its spatial and temporal expression to comprehend how Pex-ADAR is linked to regeneration. At first, in domain analysis, we discovered that Pex-ADAR only has one double-stranded RNA-binding domain (dsRBD) and a deaminase domain without a Z-DNA-binding domain (ZBD). In addition, a comparison of the core deaminase domains of Pex-ADAR with those of other ADAR family members indicated that Pex-ADAR comprises the conserved three active-site motifs and a glutamate residue for catalytic activity. Pex-ADAR also shares 11 conserved residues, a characteristic of ADAR1, supporting that Pex-ADAR is a member of ADAR1 class. Its temporal expression was remarkably low in the early stages of regeneration before suddenly increasing at 10 days post amputation (dpa) when diverse cell types and tissues were being regenerated. In situ hybridization of Pex-ADAR messenger RNA (mRNA) indicated that the main expression was observed in regenerating muscle layers and related connective tissues. Taken together, the present results demonstrate that an RNA-editing enzyme, Pex-ADAR, is implicated in muscle redifferentiation during earthworm regeneration.
Olive Mill Wastes: A Source of Bioactive Molecules for Plant Growth and Protection against Pathogens
Authors: Sciubba Fabio , Chronopoulou Laura , Pizzichini Daniele , Lionetti Vincenzo , Fontana Claudia , Aromolo Rita , Socciarelli Silvia , Gambelli Loretta , Bartolacci Barbara , Finotti Enrico , Benedetti Anna , Miccheli Alfredo , Neri Ulderico , Palocci Cleofe , Bellincampi Daniela
Published: December 2020

Olive oil production generates high amounts of liquid and solid wastes. For a long time, such complex matrices were considered only as an environmental issue, due to their polluting properties. On the other hand, olive mill wastes (OMWs) exert a positive effect on plant growth when applied to soil due to the high content of organic matter and mineral nutrients. Moreover, OMWs also exhibit antimicrobial activity and protective properties against plant pathogens possibly due to the presence of bioactive molecules including phenols and polysaccharides. This review covers the recent advances made in the identification, isolation, and characterization of OMW-derived bioactive molecules able to influence important plant processes such as plant growth and defend against pathogens. Such studies are relevant from different points of view. First, basic research in plant biology may benefit from the isolation and characterization of new biomolecules to be potentially applied in crop growth and protection against diseases. Moreover, the valorization of waste materials is necessary for the development of a circular economy, which is foreseen to drive the future development of a more sustainable agriculture.
Analgesic Tolerance Development during Repetitive Electric Stimulations Is Associated with Changes in the Expression of Activated Microglia in Rats with Osteoarthritis
Authors: Hahm Suk-Chan , Lee Jin Seung , Yoon Young Wook , Kim Junesun
Published: December 2020

Electric stimulation is used for managing osteoarthritic (OA) pain; however, little is known about the development of analgesic tolerance during repeated stimulations and the relation of spinal microglia with OA pain. We investigated the changes in the analgesic effects of repeated electric stimulations and the relation between the development of analgesic tolerance and spinal microglial expression in rats with OA. To induce OA, monosodium iodoacetate was injected into the synovial space of the right knee joint of the rats (n = 185). Repeated high frequency, low frequency, or sham transcutaneous electric nerve stimulation (TENS) was performed to the ipsilateral knee joint for 20 min in rats with OA (n = 45). Minocycline or minocycline plus TENS (HF, LF, or sham) was treated in OA rats with repeated TENS-induced tolerance (n = 135). Immunohistochemistry of the microglia in the L3–L5 spinal segments was performed. Knee joint pain during passive movement of the knee joint were quantified using the knee-bend score and the proportion of activated microglia was calculated as primary variables. Paw withdrawal threshold (hypersensitivity to mechanical stimuli) was assessed and the resting and activated microglia were counted as secondary variables. Repeated applications decreased the analgesic effect of TENS on OA pain and failed to reduce the expression of activated microglia in the spinal cord. However, spinal microglial inhibition by minocycline restored the analgesic effect of TENS on OA pain in TENS-tolerant OA rats. TENS combined with minocycline treatment improved knee joint pain and mechanical hypersensitivity in TENS-tolerant OA rats, and inhibited the expression of activated microglia in the spinal cord. These results suggest a possible relationship between repetitive electric stimulation-induced analgesic tolerance for OA pain control and changes in microglia activation.
Constant Light in Critical Postnatal Days Affects Circadian Rhythms in Locomotion and Gene Expression in the Suprachiasmatic Nucleus, Retina, and Pineal Gland Later in Life
Authors: Kubištová Aneta , Spišská Veronika , Petrželková Lucie , Hrubcová Leona , Moravcová Simona , Maierová Lenka , Bendová Zdeňka
Published: December 2020

The circadian clock regulates bodily rhythms by time cues that result from the integration of genetically encoded endogenous rhythms with external cycles, most potently with the light/dark cycle. Chronic exposure to constant light in adulthood disrupts circadian system function and can induce behavioral and physiological arrhythmicity with potential clinical consequences. Since the developing nervous system is particularly vulnerable to experiences during the critical period, we hypothesized that early-life circadian disruption would negatively impact the development of the circadian clock and its adult function. Newborn rats were subjected to a constant light of 16 lux from the day of birth through until postnatal day 20, and then they were housed in conditions of L12 h (16 lux): D12 h (darkness). The circadian period was measured by locomotor activity rhythm at postnatal day 60, and the rhythmic expressions of clock genes and tissue-specific genes were detected in the suprachiasmatic nuclei, retinas, and pineal glands at postnatal days 30 and 90. Our data show that early postnatal exposure to constant light leads to a prolonged endogenous period of locomotor activity rhythm and affects the rhythmic gene expression in all studied brain structures later in life.
A Review and a Framework of Variables for Defining and Characterizing Tinnitus Subphenotypes
Authors: Genitsaridi Eleni , Hoare Derek J. , Kypraios Theodore , Hall Deborah A.
Published: December 2020

Tinnitus patients can present with various characteristics, such as those related to the tinnitus perception, symptom severity, and pattern of comorbidities. It is speculated that this phenotypic heterogeneity is associated with differences in the underlying pathophysiology and personal reaction to the condition. However, there is as yet no established protocol for tinnitus profiling or subtyping, hindering progress in treatment development. This review summarizes data on variables that have been used in studies investigating phenotypic differences in subgroups of tinnitus, including variables used to both define and compare subgroups. A PubMed search led to the identification of 64 eligible articles. In most studies, variables for subgrouping were chosen by the researchers (hypothesis-driven approach). Other approaches included application of unsupervised machine-learning techniques for the definition of subgroups (data-driven), and subgroup definition based on the response to a tinnitus treatment (treatment response). A framework of 94 variable concepts was created to summarize variables used across all studies. Frequency statistics for the use of each variable concept are presented, demonstrating those most and least commonly assessed. This review highlights the high dimensionality of tinnitus heterogeneity. The framework of variables can contribute to the design of future studies, helping to decide on tinnitus assessment and subgrouping.
Inner versus Overt Speech Production: Does This Make a Difference in the Developing Brain?
Authors: Stephan Franziska , Saalbach Henrik , Rossi Sonja
Published: December 2020

Studies in adults showed differential neural processing between overt and inner speech. So far, it is unclear whether inner and overt speech are processed differentially in children. The present study examines the pre-activation of the speech network in order to disentangle domain-general executive control from linguistic control of inner and overt speech production in 6- to 7-year-olds by simultaneously applying electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). Children underwent a picture-naming task in which the pure preparation of a subsequent speech production and the actual execution of speech can be differentiated. The preparation phase does not represent speech per se but it resembles the setting up of the language production network. Only the fNIRS revealed a larger activation for overt, compared to inner, speech over bilateral prefrontal to parietal regions during the preparation phase. Findings suggest that the children’s brain can prepare the subsequent speech production. The preparation for overt and inner speech requires different domain-general executive control. In contrast to adults, the children’s brain did not show differences between inner and overt speech when a concrete linguistic content occurs and a concrete execution is required. This might indicate that domain-specific executive control processes are still under development.
In Vitro and In Vivo Study of the Short-Term Vasomotor Response during Epileptic Seizures
Authors: Volnova Anna , Tsytsarev Vassiliy , Ptukha Maria , Inyushin Mikhail
Published: December 2020

Epilepsy remains one of the most common brain disorders, and the different types of epilepsy encompass a wide variety of physiological manifestations. Clinical and preclinical findings indicate that cerebral blood flow is usually focally increased at seizure onset, shortly after the beginning of ictal events. Nevertheless, many questions remain about the relationship between vasomotor changes in the epileptic foci and the epileptic behavior of neurons and astrocytes. To study this relationship, we performed a series of in vitro and in vivo experiments using the 4-aminopyridine model of epileptic seizures. It was found that in vitro pathological synchronization of neurons and the depolarization of astrocytes is accompanied by rapid short-term vasoconstriction, while in vivo vasodilation during the seizure prevails. We suggest that vasomotor activity during epileptic seizures is a correlate of the complex, self-sustained response that includes neuronal and astrocytic oscillations, and that underlies the clinical presentation of epilepsy.
Spanish Validation for Olfactory Function Testing Using the Sniffin’ Sticks Olfactory Test: Threshold, Discrimination, and Identification
Authors: Delgado-Losada María Luisa , Delgado-Lima Alice Helena , Bouhaben Jaime
Published: December 2020

The assessment of olfactory function is becoming increasingly relevant, especially in cases of cognitive decline (i.e., neurodegenerative diseases), where olfactory alterations may be relevant as potential early biomarkers. The Sniffin’ Sticks Olfactory Test, developed in Germany and validated in several countries, is an objective measure of olfactory performance. This study aims to validate this test in a Spanish sample. This study included 209 healthy normosmic volunteers (154 females and 55 males) aged between 20 to 79 years (mean age = 50.11 ± 15.18 years) as the normative sample. From this group, 22 participants were retested in order to obtain test–retest reliability evidence. Odor familiarity for descriptors in the olfactory identification test was also studied on an independent healthy sample (n = 69), and required cultural modifications were applied. Results indicate that men and women, as well as smokers and non-smokers, performed equally in every test. However, significant differences were found between age groups in every score. The general trend is that olfactory function progressively decreases as a function of age, the elderly group (+60 years) being the one with the lowest scores. In conclusion, this normative data, in addition to the test’s cultural modifications, allows the Sniffin’ Sticks Olfactory Test to be administered on a Spanish population.
A Review of Machine Learning Methods of Feature Selection and Classification for Autism Spectrum Disorder
Authors: Rahman Md. Mokhlesur , Usman Opeyemi Lateef , Muniyandi Ravie Chandren , Sahran Shahnorbanun , Mohamed Suziyani , Razak Rogayah A
Published: December 2020

Autism Spectrum Disorder (ASD), according to DSM-5 in the American Psychiatric Association, is a neurodevelopmental disorder that includes deficits of social communication and social interaction with the presence of restricted and repetitive behaviors. Children with ASD have difficulties in joint attention and social reciprocity, using non-verbal and verbal behavior for communication. Due to these deficits, children with autism are often socially isolated. Researchers have emphasized the importance of early identification and early intervention to improve the level of functioning in language, communication, and well-being of children with autism. However, due to limited local assessment tools to diagnose these children, limited speech-language therapy services in rural areas, etc., these children do not get the rehabilitation they need until they get into compulsory schooling at the age of seven years old. Hence, efficient approaches towards early identification and intervention through speedy diagnostic procedures for ASD are required. In recent years, advanced technologies like machine learning have been used to analyze and investigate ASD to improve diagnostic accuracy, time, and quality without complexity. These machine learning methods include artificial neural networks, support vector machines, a priori algorithms, and decision trees, most of which have been applied to datasets connected with autism to construct predictive models. Meanwhile, the selection of features remains an essential task before developing a predictive model for ASD classification. This review mainly investigates and analyzes up-to-date studies on machine learning methods for feature selection and classification of ASD. We recommend methods to enhance machine learning’s speedy execution for processing complex data for conceptualization and implementation in ASD diagnostic research. This study can significantly benefit future research in autism using a machine learning approach for feature selection, classification, and processing imbalanced data.
AHP-Systems Thinking Analyses for Kaizen Costing Implementation in the Construction Industry
Authors: Omotayo Temitope , Awuzie Bankole , Egbelakin Temitope , Obi Lovelin , Ogunnusi Mercy
Published: December 2020

The incessant reportage of cost overruns and abandoned projects in contemporary literature have accentuated the need for a re-examination of the nature of the cost management strategies deployed to these projects. This study explores the potential of kaizen costing strategy to engender effective cost management within construction project delivery systems in developing countries. Data collected during this study were analysed using the analytic hierarchy process (AHP) and systems thinking approaches to determine the criticality of the factors influencing the effective implementation of kaizen costing. Seven (7) archetypes leading to final causal loop diagram identified the incorporation of the plan–do–check–act approach to project and cost planning, the budgeting system of the construction companies, overhead cost reduction during construction and the overall procurement process. Executing these archetypes will potentially reduce high overhead costs, project cost and time overruns, as well as enhance construction industry sector growth policies and construction organisation corporate governance.
Additive Manufacturing Applications for Industry 4.0: A Systematic Critical Review
Authors: Sepasgozar Samad M. E. , Shi Anqi , Yang Liming , Shirowzhan Sara , Edwards David J.
Published: December 2020

Additive manufacturing, including 3D printing (3DP), is one of the critical pillars of Industry 4.0 and the next construction revolution. Several countries, including China, have utilized 3DP on larger scales or real projects. However, reviews of the lessons learned from previous large-sized practices of 3DP utilization are scarce. This paper presents a few practical applications of implementing 3DP over the past decade and suggests a direction for future research work. Recent publications on 3DP practices are systematically reviewed using an interpretivist philosophical lens, and more specifically, the nozzle characteristics are focused upon. The Scopus and China National Knowledge Infrastructure (CNKI) journal databases are utilized, resulting in the examination of 54 English and 62 Chinese papers. The selected practices from Mainland China, Hong Kong, Taiwan and Macao are considered for this review. A content critical review approach is adopted, and the identified papers are critically reviewed. These papers reported key challenges and advantages from their reported practices, such as limitations in aggregate sizes, nozzle sizes, standards, post-occupancy satisfaction, final product quality, productivity challenges and other associated risks. The paper reports upon prominent limitations and signposts directions for future investigations.
One-Step Catalytic or Photocatalytic Oxidation of Benzene to Phenol: Possible Alternative Routes for Phenol Synthesis?
Authors: Mancuso Antonietta , Sacco Olga , Sannino Diana , Venditto Vincenzo , Vaiano Vincenzo
Published: December 2020

Phenol is an important chemical compound since it is a precursor of the industrial production of many materials and useful compounds. Nowadays, phenol is industrially produced from benzene by the multi-step “cumene process”, which is energy consuming due to high temperature and high pressure. Moreover, in the “cumene process”, the highly explosive cumene hydroperoxide is produced as an intermediate. To overcome these disadvantages, it would be useful to develop green alternatives for the synthesis of phenol that are more efficient and environmentally benign. In this regard, great interest is devoted to processes in which the one-step oxidation of benzene to phenol is achieved, thanks to the use of suitable catalysts and oxidant species. This review article discusses the direct oxidation of benzene to phenol in the liquid phase using different catalyst formulations, including homogeneous and heterogeneous catalysts and photocatalysts, and focuses on the reaction mechanisms involved in the selective conversion of benzene to phenol in the liquid phase.
Membrane Protein Modified Electrodes in Bioelectrocatalysis
Authors: Zhang Huijie , Catania Rosa , Jeuken Lars J. C.
Published: December 2020

Transmembrane proteins involved in metabolic redox reactions and photosynthesis catalyse a plethora of key energy-conversion processes and are thus of great interest for bioelectrocatalysis-based applications. The development of membrane protein modified electrodes has made it possible to efficiently exchange electrons between proteins and electrodes, allowing mechanistic studies and potentially applications in biofuels generation and energy conversion. Here, we summarise the most common electrode modification and their characterisation techniques for membrane proteins involved in biofuels conversion and semi-artificial photosynthesis. We discuss the challenges of applications of membrane protein modified electrodes for bioelectrocatalysis and comment on emerging methods and future directions, including recent advances in membrane protein reconstitution strategies and the development of microbial electrosynthesis and whole-cell semi-artificial photosynthesis.
Catalyzed Steam Gasification of Cistus Ladanifer Biochar
Authors: Encinar José María , González Juan Félix , Nogales-Delgado Sergio
Published: December 2020

Gasification processes require the use of cheap and sustainable raw materials, as well as the optimization of the process, for a suitable commercial use. Cistus Ladanifer (rockrose) could be a suitable raw material for this purpose, as it grows spontaneously in Mediterranean regions, and might contribute to the economic development of these areas. In this research, a study about catalyzed gasification of Cistus Ladanifer biochar was carried out. The aim was to characterize the gaseous phase and to carry out a kinetic study. The experiments were carried out in a thermobalance connected to a gas chromatograph to quantify the exhaust gas. The operating variables studied were the initial carbon mass, temperature, steam partial pressure, the kind of catalyst (ionic or cationic), catalyst concentration and the method to incorporate the catalyst (impregnation or mixture). As a result, impregnation was the most effective way to mix the raw material and the catalyst, with K+ and CO32− as the most active cations and anions used in this experience, respectively. Temperature and steam partial vapor showed a positive effect on conversion and gas yield. The use of ideal models for gas-solid reactions showed acceptable results for the kinetic study.
BLE-GSpeed: A New BLE-Based Dataset to Estimate User Gait Speed
Authors: Sansano-Sansano Emilio , Aranda Fernando J. , Montoliu Raúl , Álvarez Fernando J.
Published: December 2020

To estimate the user gait speed can be crucial in many topics, such as health care systems, since the presence of difficulties in walking is a core indicator of health and function in aging and disease. Methods for non-invasive and continuous assessment of the gait speed may be key to enable early detection of cognitive diseases such as dementia or Alzheimer’s disease. Wearable technologies can provide innovative solutions for healthcare problems. Bluetooth Low Energy (BLE) technology is excellent for wearables because it is very energy efficient, secure, and inexpensive. In this paper, the BLE-GSpeed database is presented. The dataset is composed of several BLE RSSI measurements obtained while users were walking at a constant speed along a corridor. Moreover, a set of experiments using a baseline algorithm to estimate the gait speed are also presented to provide baseline results to the research community.
In Situ Mass Spectrometry Diagnostics of Impaired Glucose Tolerance Using Label-Free Metabolomic Signature
Authors: Lokhov Petr G. , Trifonova Oxana P. , Maslov Dmitry L. , Balashova Elena E.
Published: December 2020

In metabolomics, mass spectrometry is used to detect a large number of low-molecular substances in a single analysis. Such a capacity could have direct application in disease diagnostics. However, it is challenging because of the analysis complexity, and the search for a way to simplify it while maintaining the diagnostic capability is an urgent task. It has been proposed to use the metabolomic signature without complex data processing (mass peak detection, alignment, normalization, and identification of substances, as well as any complex statistical analysis) to make the analysis more simple and rapid. Methods: A label-free approach was implemented in the metabolomic signature, which makes the measurement of the actual or conditional concentrations unnecessary, uses only mass peak relations, and minimizes mass spectra processing. The approach was tested on the diagnosis of impaired glucose tolerance (IGT). Results: The label-free metabolic signature demonstrated a diagnostic accuracy for IGT equal to 88% (specificity 85%, sensitivity 90%, and area under receiver operating characteristic curve (AUC) of 0.91), which is considered to be a good quality for diagnostics. Conclusions: It is possible to compile label-free signatures for diseases that allow for diagnosing the disease in situ, i.e., right at the mass spectrometer without complex data processing. This achievement makes all mass spectrometers potentially versatile diagnostic devices and accelerates the introduction of metabolomics into medicine.
Students’ Perceptions of Educational Climate in a Spanish School of Dentistry Using the Dundee Ready Education Environment Measure: A Longitudinal Study
Authors: Hernández-Crespo Alba María , Fernández-Riveiro Paula , Rapado-González Óscar , Aneiros Ángela , Tomás Inmaculada , Suárez-Cunqueiro María Mercedes
Published: December 2020

Background: Educational Climate (EC) may determine teacher and student behaviour. Our aim was to evaluate EC longitudinally in a period of ‘curricular transition’ from traditional (teacher-centred learning) to Bologna curricula (interactive student-centred learning). Methods: The ‘Dundee Ready Education Environment Measure’ (DREEM) questionnaire was completed by 397 students from a Spanish School of Dentistry. Students’ perception was assessed in different courses and academic years. Results: The overall EC scale average was 115.70 ± 20.20 (57.85%) and all domain values showed a percentage > 52%, which were interpreted as ‘positive and acceptable’. The EC mean was: 118.02 ± 17.37 (59.01%) for 2010–2011; 116.46 ± 19.79 (58.23%) for 2013–2014; 115.60 ± 21.93 (57.80%) for 2014–2015; 112.02 ± 22.28 (56.01%) for 2015–2016, interpreted as ‘more positive than negative EC’. The worst Learning domain scores corresponded to later academic years and may reflect the Bologna curriculum’s more intensive clinical training involving greater responsibility and self-learning. Conclusions: EC and its domains were perceived more positively than negatively. The Social domain was the most positively evaluated, while the Learning domain was the worst.
Approximate Evolution for A Hybrid System—An Optomechanical Jaynes-Cummings Model
Authors: Medina-Dozal Luis , Ramos-Prieto Irán , Récamier José
Published: December 2020

In this work, we start from a phenomenological Hamiltonian built from two known systems: the Hamiltonian of a pumped optomechanical system and the Jaynes-Cummings Hamiltonian. Using algebraic techniques we construct an approximate time evolution operator U^(t) for the forced optomechanical system (as a product of exponentials) and take the JC Hamiltonian as an interaction. We transform the later with U^(t) to obtain a generalized interaction picture Hamiltonian which can be linearized and whose time evolution operator is written in a product form. The analytic results are compared with purely numerical calculations using the full Hamiltonian and the agreement between them is remarkable.
A Review of Fractional Order Entropies
Authors: Lopes António M. , Machado José A. Tenreiro
Published: December 2020

Fractional calculus (FC) is the area of calculus that generalizes the operations of differentiation and integration. FC operators are non-local and capture the history of dynamical effects present in many natural and artificial phenomena. Entropy is a measure of uncertainty, diversity and randomness often adopted for characterizing complex dynamical systems. Stemming from the synergies between the two areas, this paper reviews the concept of entropy in the framework of FC. Several new entropy definitions have been proposed in recent decades, expanding the scope of applicability of this seminal tool. However, FC is not yet well disseminated in the community of entropy. Therefore, new definitions based on FC can generalize both concepts in the theoretical and applied points of view. The time to come will prove to what extend the new formulations will be useful.
Lottery and Auction on Quantum Blockchain
Authors: Sun Xin , Kulicki Piotr , Sopek Mirek
Published: December 2020

This paper proposes a protocol for lottery and a protocol for auction on quantum Blockchain. Our protocol of lottery satisfies randomness, unpredictability, unforgeability, verifiability, decentralization and unconditional security. Our protocol of auction satisfies bid privacy, posterior privacy, bids’ binding, decentralization and unconditional security. Except quantum Blockchain, the main technique involved in both protocols is quantum bit commitment.
On the Asymptotic Optimality of a Low-Complexity Coding Strategy for WSS, MA, and AR Vector Sources
Authors: Gutiérrez-Gutiérrez Jesús , Zárraga-Rodríguez Marta , Insausti Xabier
Published: December 2020

In this paper, we study the asymptotic optimality of a low-complexity coding strategy for Gaussian vector sources. Specifically, we study the convergence speed of the rate of such a coding strategy when it is used to encode the most relevant vector sources, namely wide sense stationary (WSS), moving average (MA), and autoregressive (AR) vector sources. We also study how the coding strategy considered performs when it is used to encode perturbed versions of those relevant sources. More precisely, we give a sufficient condition for such perturbed versions so that the convergence speed of the rate remains unaltered.
Adam and the Ants: On the Influence of the Optimization Algorithm on the Detectability of DNN Watermarks
Authors: Cortiñas-Lorenzo Betty , Pérez-González Fernando
Published: December 2020

As training Deep Neural Networks (DNNs) becomes more expensive, the interest in protecting the ownership of the models with watermarking techniques increases. Uchida et al. proposed a digital watermarking algorithm that embeds the secret message into the model coefficients. However, despite its appeal, in this paper, we show that its efficacy can be compromised by the optimization algorithm being used. In particular, we found through a theoretical analysis that, as opposed to Stochastic Gradient Descent (SGD), the update direction given by Adam optimization strongly depends on the sign of a combination of columns of the projection matrix used for watermarking. Consequently, as observed in the empirical results, this makes the coefficients move in unison giving rise to heavily spiked weight distributions that can be easily detected by adversaries. As a way to solve this problem, we propose a new method called Block-Orthonormal Projections (BOP) that allows one to combine watermarking with Adam optimization with a minor impact on the detectability of the watermark and an increased robustness.
Working Memory Decline in Alzheimer’s Disease Is Detected by Complexity Analysis of Multimodal EEG-fNIRS
Authors: Perpetuini David , Chiarelli Antonio Maria , Filippini Chiara , Cardone Daniela , Croce Pierpaolo , Rotunno Ludovica , Anzoletti Nelson , Zito Michele , Zappasodi Filippo , Merla Arcangelo
Published: December 2020

Alzheimer’s disease (AD) is characterized by working memory (WM) failures that can be assessed at early stages through administering clinical tests. Ecological neuroimaging, such as Electroencephalography (EEG) and functional Near Infrared Spectroscopy (fNIRS), may be employed during these tests to support AD early diagnosis within clinical settings. Multimodal EEG-fNIRS could measure brain activity along with neurovascular coupling (NC) and detect their modifications associated with AD. Data analysis procedures based on signal complexity are suitable to estimate electrical and hemodynamic brain activity or their mutual information (NC) during non-structured experimental paradigms. In this study, sample entropy of whole-head EEG and frontal/prefrontal cortex fNIRS was evaluated to assess brain activity in early AD and healthy controls (HC) during WM tasks (i.e., Rey–Osterrieth complex figure and Raven’s progressive matrices). Moreover, conditional entropy between EEG and fNIRS was evaluated as indicative of NC. The findings demonstrated the capability of complexity analysis of multimodal EEG-fNIRS to detect WM decline in AD. Furthermore, a multivariate data-driven analysis, performed on these entropy metrics and based on the General Linear Model, allowed classifying AD and HC with an AUC up to 0.88. EEG-fNIRS may represent a powerful tool for the clinical evaluation of WM decline in early AD.
Research on Community Detection in Complex Networks Based on Internode Attraction
Authors: Sheng Jinfang , Liu Cheng , Chen Long , Wang Bin , Zhang Junkai
Published: December 2020

With the rapid development of computer technology, the research on complex networks has attracted more and more attention. At present, the research directions of cloud computing, big data, internet of vehicles, and distributed systems with very high attention are all based on complex networks. Community structure detection is a very important and meaningful research hotspot in complex networks. It is a difficult task to quickly and accurately divide the community structure and run it on large-scale networks. In this paper, we put forward a new community detection approach based on internode attraction, named IACD. This algorithm starts from the perspective of the important nodes of the complex network and refers to the gravitational relationship between two objects in physics to represent the forces between nodes in the network dataset, and then perform community detection. Through experiments on a large number of real-world datasets and synthetic networks, it is shown that the IACD algorithm can quickly and accurately divide the community structure, and it is superior to some classic algorithms and recently proposed algorithms.
Challenges and Opportunities for Russian Higher Education amid COVID-19: Teachers’ Perspective
Authors: Almazova Nadezhda , Krylova Elena , Rubtsova Anna , Odinokaya Maria
Published: December 2020

The COVID-19 pandemic has tremendously affected higher education systems in Russia and all over the world, forcing to transform curriculum into an online format, which is a challenge for all the educational process participants. The current study discusses the implementation of online learning amid the COVID-19 pandemic in the Russian higher education context and investigates the challenges experienced by university teachers during this period to define their readiness for online education. To address the above-mentioned issues, a study was conducted in Peter the Great St. Petersburg Polytechnic University. A variety of methods of scientific and pedagogical research were used including systematic structural analysis, synthesis, work with research papers, the generalization of experience and experimental work, observation, surveys, etc., with 87 university teachers asked to respond to several sets of questions describing their online teaching experience after the launch of online education amid the COVID-19 pandemic. The analysis of the participants’ answers helped to identify the following main challenges experienced by university teachers: computer literacy level, the university electronic environment and support, academic staff readiness and students’ readiness for online learning, the last two being the most important hindering the implementation of the efficient online education process. It was also underlined by most respondents that methodological work of a teacher in a digital educational environment differs from conventional teaching methods. Thus, psychological, technological, methodological support and teachers’ professional development programs are of vital importance to minimize the negative impact of the rapid changes of the educational process and to ensure efficient online education.
Assessment of Microbiological Quality and Physicochemical Parameters of Fruhe Made by Ovine and Goat Milk: A Sardinian (Italy) Cheese
Authors: Murgia Marco A. , Deiana Pietrino , Nudda Anna , Correddu Fabio , Montanari Luigi , Mangia Nicoletta P.
Published: December 2020

Fruhe (Casu axedu) is a fresh cheese, traditionally manufactured in Sardinia (Italy) from sheep or goat milk, characterized by a compact coagulum obtained from raw or heat-treated whole milk. The objective of this study was to investigate the microbiological quality and physicochemical parameters of the sheep and goat Fruhe types of cheese at 21 days of cold storage. Chemical analyses showed that all Fruhe cheese samples were characterized by a pH below 4.4 and a variable content of total solid (22.75–21.06 g/100 g) proteins (5.4–10 g/100 g) and fat (3.9–15.7 g/100 g). The average residual lactose content was 2.6 g/100 g, while lactic acid content was 1.8 g/100 g. Microbial analyses revealed a high number of Lactic Acid Bacteria for both thermophilic and mesophilic streptococci (9 log CFU/g), and no pathogenic bacteria were found. The content of Free Amino Acids and Free Fatty acids point out that a good activity of rennet and microbial enzymes occurred, although Fruhe cheese is not subject to a ripening process. The present research reports the microbiological and nutritional characteristics of the sheep and goat Fruhe cheese that could represent the basis for further investigations, needful to improve its nutritional quality and to preserve its peculiarities.
Comparing Blockchain Standards and Recommendations
Authors: König Lukas , Korobeinikova Yuliia , Tjoa Simon , Kieseberg Peter
Published: December 2020

Since the introduction of Bitcoin, the term “blockchain” has attracted many start-ups and companies over the years, especially in the financial sector. However, technology is evolving faster than standardization frameworks. This left the industry in the position of having to use this emerging technology, without being backed by any international standards organization regarding for neither the technology itself, nor for a blockchain specific information security framework. In times of the General Data Protection Regulation and growing international trade conflicts, protecting information is more relevant than ever. Standardization of blockchains is an appeal to raise the development of information technologies to the next level. Therefore, this paper shall provide an overview of standardization organization’s publications about blockchains/distributed ledger technologies, a set of comparison criteria for future work and a comparison of the existing standards work itself. With that information, aligning to existing standardization efforts becomes easier, and might even present the possibility to create frameworks where there are none at the moment.
Predictive Maintenance (PdM) Structure Using Internet of Things (IoT) for Mechanical Equipment Used into Hospitals in Rwanda
Authors: Niyonambaza Irene , Zennaro Marco , Uwitonze Alfred
Published: December 2020

The success of all industries relates to attaining the satisfaction to clients with a high level of services and productivity. The success main factor depends on the extent of maintaining their equipment. To date, the Rwandan hospitals that always have a long queue of patients that are waiting for service perform a repair after failure as common maintenance practice that may involve unplanned resources, cost, time, and completely or partially interrupt the remaining hospital activities. Aiming to reduce unplanned equipment downtime and increase their reliability, this paper proposes the Predictive Maintenance (PdM) structure while using Internet of Things (IoT) in order to predict early failure before it happens for mechanical equipment that is used in Rwandan hospitals. Because prediction relies on data, the structure design consists of a simplest developed real time data collector prototype with the purpose of collecting real time data for predictive model construction and equipment health status classification. The real time data in the form of time series have been collected from selected equipment components in King Faisal Hospital and then later used to build a proposed predictive time series model to be employed in proposed structure. The Long Short Term Memory (LSTM) Neural Network model is used to learn data and perform with an accuracy of 90% and 96% to different two selected components.
Smart Site Diversity for a High Throughput Satellite System with Software-Defined Networking and a Virtual Network Function
Authors: Velusamy Gandhimathi , Lent Ricardo
Published: December 2020

High Throughput Satellite (HTS) systems aim to push data rates to the order of Terabit/s, making use of Extremely High Frequencies (EHF) or free-space optical (FSO) in the feeder links. However, one challenge that needs to be addressed is that the use of such high frequencies makes the feeder links vulnerable to atmospheric conditions, which can effectively disable channels at times or temporarily increases the bit error rates. One way to cope with the problem is to introduce site diversity and to forward the data through the gateways not affected, or at least less constrained, by adverse conditions. In this paper, a virtual network function (VNF) introduced through reinforcement learning defines a smart routing service for an HTS system. Experiments were conducted on an emulated ground-satellite system in CloudLab, testing a VNF implementation of the approach with software-defined networking virtual switches, which indicate the expected performance of the proposed method.
Investigation of Flow Behavior and Porous Medium Resistance Coefficients for Metallic-Cloth Fibers
Authors: Gorgun Erdem , Dogu Yahya , Aksit Mahmut Faruk
Published: December 2020

The flow through porous metallic-cloth fibers influences the cloth seal leakage performance. Measuring the actual seal leakage proves difficult with challenging turbine operating conditions. A non-Darcian porous medium Computational Fluid Dynamics (CFD) model was employed for the flow within porous metallic-cloth fibers. CFD analyses need leakage data depending on the pressure load to calibrate flow resistance coefficients. A test rig was built to measure leakage with respect to the pressure load and weave orientation in four directions. The Sutherland-ideal gas approach was utilized to determine the flow resistance coefficients for Dutch twill metallic-cloth fibers as a function of pressure load. The results show that metallic-cloth fiber leakage is a linear function of pressure load. The best–worst order for leakage performance was the warp, diagonal, shute, and cross directions. For the best sealing performance, the flow direction in metallic-cloth fibers would be the warp direction. The flow resistance coefficients depend on the evaluation of the pressure level, which changes over the weave flow thickness. This is represented with the pressure constant (Cdown). The best match between the test and CFD leakages was obtained for the weave directions of warp (0.9), shute (0.9), diagonal (0.7), and cross (0.0). Calibrating the resistance coefficients with respect to the pressure and temperature enables performing CFD analyses in turbine conditions.