bluuebunny/crossref_metadata_2025 huggingface dataset:
Are Different Types of Learning Disorder Associated With Distinct Cognitive Functioning Profiles?
Authors: Brandenburg Janin , Huschka Sina S. , Visser Linda , Hasselhorn Marcus
Published: October 2021

Introduction: DSM-5 presented a revised conceptualization of specific learning disorders (LD). Contrary to former versions, the various types of LD—i.e., mathematics disorder, reading disorder, and writing disorder—are not treated as distinct diagnostic entities but are integrated into one single LD category. In support of this new classification, it has been argued that the various types of LD overlap to a great extent in their cognitive functioning profiles and therefore do not exhibit a distinct set of cognitive causes. In contrast, ICD-11 still adheres to the idea of discrete categories and thus follows the specificity hypothesis of LD. Using latent profile analysis (LPA), we therefore tested the specificity of cognitive strengths and weaknesses in children with different types of LD. Secondly, we aimed at examining the extent to which observed LD characteristics (type and severity of LD as well as IQ-achievement discrepancy) were consistent with the membership of a given latent profile.

Method: 302 German third-graders (134 girls; IQ ≥ 85; Mage = 111.05 months; SD = 5.76) with single or comorbid types of LD in the domains of mathematics, reading, and spelling completed a wide range of domain-specific and domain-general cognitive functioning measures.

Results: Five qualitative distinct profiles of cognitive strengths and weaknesses were identified. Profile 1 (23% of the sample) showed Comprehensive Cognitive Deficits, performing low in all measures except for naming speed, language, and inhibition. Profile 2 (21%) included children with a Double Deficit in Phonological Awareness and Phonological Short-term Memory. Profile 3 (20%) was characterized by a Double Deficit of Phonological Awareness and Naming Speed. Profile 4 (19%) included children with a Single Deficit in Attention, and profile 5 (17%) consisted of children without any cognitive deficits. Moreover, type and severity of LD as well as IQ-achievement discrepancy discriminated between the profiles, which is in line with the specificity hypothesis of LD.

Discussion: Overall, the finding of specific associations between the LD types and the identified cognitive profiles supports the ICD-11 classification of LD. Yet, those inferences may not be valid for an individual child but need to be examined through comprehensive diagnostic.
Clinical Predictors of Abnormal Head Computed Tomography Findings in Non-trauma Patients Presenting to a South African Emergency Department
Authors: Simwatachela Ekin , Ozoh John O. , Mabuza Langalibalele H. , Kalinda Chester
Published: October 2021

Background: Head computed tomography (head CT) examinations conducted at emergency departments (EDs) for non-trauma patients are expensive and expose patients to ionizing radiation. Identification of symptoms likely to yield abnormal head CT scans can reduce costs and prevent unnecessary patient irradiation. There is limited comprehensive data in the literature concerning the utilization of head CT in low- and middle-income countries (LMICs) EDs.

Methods: A retrospective study of successive non-contrasted head CT scans from February 2017 through January 2018 performed on non-trauma ED patients aged 18 years and above without known pre-existing intracranial pathology was conducted. Univariate and multivariate logistic models were used to determine which presenting clinical features were likely to yield abnormal head CT findings. Clinical information was obtained from the history and physical examination findings entered on the requisition form by the ED clinicians and from previous head CT reports if present on the picture archiving and communication system (PACS).

Results: A total of 396 consecutive patients who received head CT examinations had a median age of 49 years (IQR: 36–53), and 53.3% were male (n = 211/396). Of the head CT scans included, 73.5% of head CTs included were abnormal (n = 291/396). Age >61 years (aOR:1.54; 95%CI: 1.12–2.10), focal neurologic deficit (aOR: 2.46; 95%CI: 1.42–4.26), and loss of consciousness (aOR 2.82; 95%CI: 1.21–6.57) were the predictors of abnormal head CT findings.

Conclusion: A head CT scan in a non-trauma patient presenting to an emergency department in a low–middle income country like South Africa is likely to yield abnormal findings if a patient presented with age above 61 years, loss of consciousness, or focal neurological deficit.
Analytic Form Fitting in Poor Triangular Meshes
Authors: Rendon-Cardona Cristian , Correa Jorge , Acosta Diego A. , Ruiz-Salguero Oscar
Published: October 2021

Fitting of analytic forms to point or triangle sets is central to computer-aided design, manufacturing, reverse engineering, dimensional control, etc. The existing approaches for this fitting assume an input of statistically strong point or triangle sets. In contrast, this manuscript reports the design (and industrial application) of fitting algorithms whose inputs are specifically poor triangular meshes. The analytic forms currently addressed are planes, cones, cylinders and spheres. Our algorithm also extracts the support submesh responsible for the analytic primitive. We implement spatial hashing and boundary representation for a preprocessing sequence. When the submesh supporting the analytic form holds strict C0-continuity at its border, submesh extraction is independent of fitting, and our algorithm is a real-time one. Otherwise, segmentation and fitting are codependent and our algorithm, albeit correct in the analytic form identification, cannot perform in real-time.
Influence of Baltic Agro-Environmental Conditions on Yield and Quality of Fava Bean Crops in Conventional Systems
Authors: Lepse Liga , Vågen Ingunn M. , Zeipina Solvita , Torp Torfinn , Olle Margit , Rosa Eduardo , Domínguez-Perles Raul
Published: October 2021

Fava bean (Vicia faba L.) yields are featured by high variability, influenced by the agro-environmental conditions during the growing seasons. These legume crops are sensitive to hydric and heat stresses. The adaptation depends on the efficiency of specific cultivars to use the available resources to produce biomass. This capacity is determined by the genotype and agronomical management practices. The present work aimed to uncover the influence of Baltic agro-environmental conditions (fava bean cultivar, plant density, climate, and soil features) on yield and protein content. For this, field trials were set under Baltic agro-climatic conditions, in Latvia and Estonia with five commercially available fava bean cultivars, representing broad genetic variation (‘Gloria’, ‘Julia’, ‘Jogeva’, ‘Lielplatones’, and ‘Bauska’). The results evidenced ‘Bauska’, ‘Julia’, and ‘Lielplatones’, as the most productive cultivars in terms of seed yield (4.5, 3.7, and 4.6 t ha−1, respectively) and protein yield (1.39, 1.22, and 1.36 t ha−1, respectively) under Estonian and Latvian agro-climatic conditions. Sowing these specific cultivars at densities of 30–40 seeds m−2 constitutes sustainable management for fava bean production in conventional cropping systems in the Baltic region.
Molnupiravir—A Novel Oral Anti-SARS-CoV-2 Agent
Authors: Lee Ching-Chi , Hsieh Chih-Chia , Ko Wen-Chien
Published: October 2021

Since December 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has rapidly resulted in a global pandemic with approximately 4 million deaths. Effective oral antiviral agents are urgently needed to treat coronavirus disease-2019 (COVID-19), block SARS-CoV-2 transmission, and prevent progression to severe illness. Molnupiravir (formerly EIDD-2801), a prodrug of beta-d-N4-hydroxycytidine (EIDD-1931) and an inhibitor of RNA-dependent RNA polymerase, possesses significant activity against SARS-CoV-2. Its prophylactic efficacy has been evidenced in a ferret model. Two phase-I trials (NCT04392219 and NCT04746183) have demonstrated that oral molnupiravir is safe and well-tolerated at therapeutic doses. After five-days of oral molnupiravir therapy, satisfactory efficacies, assessed by eliminating nasopharyngeal virus in patients with early and mild COVID-19, were disclosed in two phase-II trials (NCT04405739 and NCT 04405570). Two phase-II/III trials, NCT04575597 and NCT04575584, with estimated enrollments of 1850 and 304 cases, respectively, are ongoing. The NCT04575597 recently released that molnupiravir significantly reduced the risk of hospitalization or death in adults experiencing mild or moderate COVID-19. To benefit individual and public health, clinical applications of molnupiravir to promptly treat COVID-19 patients and prevent SARS-CoV-2 transmission may be expected.
Comparative Analysis of Dalbavancin versus Other Antimicrobial Options for Gram-Positive Cocci Infections: Effectiveness, Hospital Stay and Mortality
Authors: de Pablo-Miró Mar , Pujol-Ruiz Sergi , Iftimie Simona , Arenas-Miras María del Mar , López-Montesinos Inmaculada , Duran-Jordà Xavier , Anglès Albert , Grau Santiago , Horcajada Juan P.
Published: October 2021

Dalbavancin is a new antibiotic that is effective against Gram-positive microorganisms, including methicillin-resistant Staphylococci, and offers the possibility of administering intravenous therapy once weekly in an ambulatory setting. We conducted a multicenter observational case-control study, comparing all patients who received dalbavancin (cases) with hospitalized patients who were treated instead with daptomycin, linezolid or vancomycin (controls), based on clinical diagnosis, main microorganism involved, and age. The primary outcome was the length of hospital stay after starting the study antimicrobial. Secondary outcomes were 7-day and 30-day efficacy, 30-day mortality, 90-day recurrence, 90-day and 6-month hospitalization, presence of adverse events and healthcare-associated infections; 161 patients (44 cases and 117 controls) were included. Bivariate analysis showed that dalbavancin reduced the total length of hospital stay (p < 0.001), with fewer 90-day recurrences (p = 0.005), 6-month hospitalizations related to the same infection (p = 0.004) and non-related hospitalizations (p = 0.035). Multivariate analyses showed that length of hospital stay was significantly shorter in patients treated with dalbavancin (−12.05 days 95% CI [−17.00, −7.11], p < 0.001), and 30-day efficacy was higher in the dalbavancin group (OR 2.62 95% CI [1.07, 6.37], p = 0.034). Although sample size of the study may be a limitation, we can conclude that Dalbavancin is a useful antimicrobial drug against Gram-positive infections, including multidrug-resistant pathogens, and allows for a remarkable reduction in length of hospital stay with greater 30-day efficacy.
Oxidative Stress in Preterm Newborns
Authors: Lembo Chiara , Buonocore Giuseppe , Perrone Serafina
Published: October 2021

Preterm babies are highly susceptible to oxidative stress (OS) due to an imbalance between the oxidant and antioxidant systems. The generation of free radicals (FR) induces oxidative damage to multiple body organs and systems. OS is the main factor responsible for the development of typical premature infant diseases, such as bronchopulmonary dysplasia, retinopathy of prematurity, necrotizing enterocolitis, intraventricular hemorrhage, periventricular leukomalacia, kidney damage, eryptosis, and also respiratory distress syndrome and patent ductus arteriosus. Many biomarkers have been detected to early identify newborns at risk of developing a free radical-mediated disease and to investigate new antioxidant strategies. This review reports the current knowledge on OS in the preterm newborns and the newest findings concerning the use of OS biomarkers as diagnostic tools, as well as in implementing antioxidant therapeutic strategies for the prevention and treatment of these diseases and their sequelae.
Inhibition of Peroxiredoxin 6 PLA2 Activity Decreases Oxidative Stress and the Severity of Acute Lung Injury in the Mouse Cecal Ligation and Puncture Model
Authors: Fisher Aron B. , Dodia Chandra , Tao Jian-Qin , Feinstein Sheldon I. , Chatterjee Shampa
Published: October 2021

The use of agents to inhibit the production of reactive oxygen species (ROS) has been proposed for the treatment of Acute Lung Injury (ALI). However, this approach also inhibits the bactericidal activity of polymorphonuclear leucocytes (PMN) and other cells, raising the possibility of aggravating lung injury in ALI associated with bacterial infection. We used the cecal ligation and puncture (CLP) model of ALI associated with sepsis to investigate the effect of inhibiting NADPH oxidase 2 (NOX2)-derived ROS production, the main source of ROS in lungs. A phospholipase A2 inhibitor called peroxiredoxin 6 inhibitory peptide-2 (PIP-2) was used to inhibit NOX2 activation; the peptide prevents liberation of Rac, a necessary NOX2 co-factor. At 18 h after intravenous treatment with 2 µg PIP-2 /gram body weight (wt), the number of colony-forming bacteria in lungs and peritoneal fluid of mice with CLP was approximately doubled as compared to untreated mice. Treatment with 10 µg PIP-2/g body wt resulted in 100% mortality within 18 h. Antibiotic treatment abolished both the increase in lung bacteria with low dose PIP-2 and the increased mortality with high dose PIP-2. Treatment with PIP-2 plus antibiotics resulted in significantly improved lung histology, decreased PMN infiltration, decreased lung fluid accumulation, and decreased oxidative lung injury compared to antibiotics alone. We conclude that the administration of PIP-2 provides partial protection against lung injury in a model of ALI due to bacterial infection, while concurrent antibiotic treatment abolishes the deleterious effects of PIP-2 on lung bacterial clearance. These results suggest that addition of PIP-2 to the antibiotic regimen is beneficial for treatment of ALI associated with bacterial infection.
Experimentally Viable Techniques for Accessing Coexisting Attractors Correlated with Lyapunov Exponents
Authors: Hall Joshua Ray , Burton Erikk Kenneth Tilus , Chapman Dylan Michael , Bandy Donna Kay
Published: October 2021

Universal, predictive attractor patterns configured by Lyapunov exponents (LEs) as a function of the control parameter are shown to characterize periodic windows in chaos just as in attractors, using a coherent model of the laser with injected signal. One such predictive pattern, the symmetric-like bubble, foretells of an imminent bifurcation. With a slight decrease in the gain parameter, we find the symmetric-like bubble changes to a curved trajectory of two equal LEs in one attractor, while an increase in the gain reverses this process in another attractor. We generalize the power-shift method for accessing coexisting attractors or periodic windows by augmenting the technique with an interim parameter shift that optimizes attractor retrieval. We choose the gain as our parameter to interim shift. When interim gain-shift results are compared with LE patterns for a specific gain, we find critical points on the LE spectra where the attractor is unlikely to survive the gain shift. Noise and lag effects obscure the power shift minimally for large domain attractors. Small domain attractors are less accessible. The power-shift method in conjunction with the interim parameter shift is attractive because it can be experimentally applied without significant or long-lasting modifications to the experimental system.
Sub-Rectangular Tunnel Behavior under Seismic Loading
Authors: Pham Van Vi , Do Ngoc Anh , Dias Daniel
Published: October 2021

Circular and rectangular tunnel shapes are usually chosen when excavating at shallow depths in urban areas. However, special-shaped tunnels such as sub-rectangular tunnels have recently been used to overcome some drawbacks of circular and rectangular tunnels in terms of low space utilization efficiency and stress concentration, respectively. In the literature, experimental studies as well as analytical and numerical models have been developed for the seismic analysis and vulnerability assessment of circular and rectangular tunnels since the early 1990s. However, knowledge gaps regarding the behavior of sub-rectangular tunnels under seismic loading remain and still need to be bridged. The present paper focuses on introducing a numerical analysis of sub-rectangular tunnels under seismic loading. The numerical model of sub-rectangular tunnels is developed based on the numerical analyses of circular tunnels validated by comparing well-known, analytical solutions. This paper aims to highlight the differences between the behavior of sub-rectangular tunnels compared with circular tunnels when subjected to seismic loadings. Special attention is paid to the soil–lining interface conditions. The influence of parameters, such as soil deformations, maximum horizontal acceleration, and lining thickness, on sub-rectangular tunnel behavior under seismic loading is also investigated. The results indicate a significant behavior difference between sub-rectangular and circular tunnels. The absolute extreme incremental bending moments for a circular tunnel (no-slip condition) are smaller than that for the corresponding full-slip condition. The absolute extreme incremental bending moments of sub-rectangular tunnels (no-slip condition) are, however, greater than the corresponding full-slip conditions.
The Impact of Ski Geometry Data and Standing Height on the Risk of Falling in Recreational Alpine Skiers
Authors: Ruedl Gerhard , Posch Markus , Greier Klaus , Faulhaber Martin , Burtscher Martin
Published: October 2021

The aim of this study was to evaluate the impact of individual, equipment-related and environmental factors associated with falls among adult recreational skiers. Individual, equipment-related (ski geometry data) and environmental data were collected by questionnaire among uninjured skiers with and without reported falls during the skiing day. Ski length, side cut radius, and width of the waist were directly recorded from the ski and standing height was measured using a digital sliding caliper. Absolute ski length was relativized to body height. A total of 1174 recreational skiers participated in this study, of whom 13.5% (n = 158) reported at least one fall during the skiing day. Results of the multiple logistic regression analysis found that a lower age, a very good/good fitness level, a moderate skiing speed, a lower relativized ski length, and fresh and grippy snow conditions decreased, while a lower skill level, a larger sidecut radius and an easy slope difficulty increased risk of falling on ski slopes. Besides individual and environmental factors, a lower relativized ski length and a lower sidecut radius decreased the risk of falling. Considering these ski geometry parameters when buying new skis could potentially decrease the risk of falling and thus prevent injuries in recreational skiers.
BIM Information Standard Framework for Model Integration and Utilization Based on openBIM
Authors: Jo Chanwon , Choi Jungsik
Published: October 2021

The use of Building Information Modeling (BIM) is becoming more common in the construction process, and the demand for the integrated use of BIM data is expected to continue increasing. BIM is a technology that can maximize various efficiencies by sharing facility information in an integrated manner; however, the information generated in the life cycle of the construction industry is broad, diverse, and complex. Accordingly, because BIM information is difficult to share and is often duplicated, it is not easy to obtain the effects of various BIMs. The solution to this is to create a systematic standard so that one item of information can be used in various ways, and everyone shares and uses it together. To this end, various standards (guides, classification systems, information standards, etc.) are being created; however, the interrelationships between standard elements are complex, so there is confusion and overlap between standards. This paper proposes an information standard framework for BIM to identify a systematic standard and method to effectively develop various guidelines for the standard.
Network Analysis for Learners’ Concept Maps While Using Mobile Augmented Reality Gaming
Authors: Sdravopoulou Konstantina , Muñoz González Juan Manuel , Hidalgo-Ariza María Dolores
Published: October 2021

Using mobile augmented reality games in education combines situated and active learning with pleasure. The aim of this research is to analyze the responses expressed by young, middle-aged, and elderly adults about the location-based mobile augmented reality (MAR) games using methods of content analysis, concept maps, and social network analysis (SNA). The responses to questions related to MAR game Ingress were collected from 36 adult players, aged 20–60, from Greece, and subsequently analyzed by means of content analysis, concept maps, and social network analysis. Our findings show that for question 1 (How do you feel when you endow the geographical space with personal preferences?), there was a differentiation of the answers between age groups with age groups agreeing in pairs, the first two and the last two, while for question 2 (Do you think that the game offers opportunities for learning and teaching geography, building on your previous geographical knowledge?), there was an overlap in responses of participants among age groups. It was also revealed that the MAR games foster a constructivism approach of learning, as their use learning becomes an active, socially supported process of knowledge construction.
A Parallel Robot with Torque Monitoring for Brachial Monoparesis Rehabilitation Tasks
Authors: Pisla Doina , Tarnita Daniela , Tucan Paul , Tohanean Nicoleta , Vaida Calin , Geonea Ionut Daniel , Bogdan Gherman , Abrudan Cristian , Carbone Giuseppe , Plitea Nicolae
Published: October 2021

Robots for rehabilitation tasks require a high degree of safety for the interaction with both the patients and for the operators. In particular, high safety is a stable and intuitive control of the moving elements of the system combined with an external system of sensors able to monitor the position of every aspect of the rehabilitation system (operator, robot, and patient) and overcome in a certain measure all the events that may occur during the robotic rehabilitation procedure. This paper presents the development of an internal torque monitoring system for ASPIRE. This is a parallel robot designed for shoulder rehabilitation, which enables the use of strategies towards developing a HRI (human–robot interaction) system for the therapy. A complete analysis regarding the components of the robotic system is carried out with the purpose of determining the dynamic behavior of the system. Next, the proposed torque monitoring system is developed with respect to the previously obtained data. Several experimental tests are performed using healthy subjects being equipped with a series of biomedical sensors with the purpose of validating the proposed torque monitoring strategy and, at the same time, to satisfy the degree of safety that is requested by the medical procedure.
A Non-Stationary Heat Spell Frequency, Intensity, and Duration Model for France, Integrating Teleconnection Patterns and Climate Change
Authors: Hamdi Yasser , Charron Christian , Ouarda Taha B. M. J.
Published: October 2021

The warming observed over the past summers since 2000 is unprecedented in climate records in Europe and especially in France. Extreme temperatures and heat spells were often analyzed in the literature by applying extreme value theory but rarely in a non-stationary (NS) framework and duration modeling is often excluded. For a modern risk-based approach, it is important to have knowledge of the duration, magnitude, and frequency of occurrence of heat spells in a climate variability and change context. Yet, despite their obvious importance, teleconnections and associated climate indices (CIs) have often been excluded from heat spell modelling. The notion of duration is also not easily interpretable in a frequency analysis and can even be subtle, especially in a NS context. In this study, we used time-varying statistical distributions with parameters conditional on covariates representing the time and CIs. The daily maximum temperatures (DMTs) observed at the Orange and Dijon stations in France were used as a case study. This paper highlights a possible relationship between some large-scale climate patterns and the heat spells in France. Overall, the results suggest that considering the combined effect of global warming and these patterns in NS models is useful for a more appropriate characterization of the hazard heat spells in France.
Specification of Modified Jarvis Model Parameterization for Pinus cembra
Authors: Buchholcerová Anna , Fleischer Peter , Štefánik Dušan , Bičárová Svetlana , Lukasová Veronika
Published: October 2021

The high ambient ozone concentrations cause impairing effects on vegetation leading to plant injuries. The potential ozone uptake to vegetation through open stomata can be quantified using stomatal conductance measurements under the local environmental conditions. This study compares the ozone stomatal conductance to vegetation obtained with a modified Jarvis formula adopted from the Vegetation Manual of United Nations Economic Commission for Europe, and experimental field measurements’ data. The stomatal conductance was measured by a portable photosynthesis and gas exchange analyzer system LiCOR6400. The measurements were performed in the submontane environment of the High Tatra Mountains in Slovakia on Swiss pine (Pinus cembra), as a native species of the local flora. According to previous studies, Swiss pine is considered as an ozone-sensitive species. The modified Jarvis model for the ozone stomatal conductance is compared with the field measurements. The suitable parameterization of the modified Jarvis model for Swiss pine is obtained. The parameterization of stomatal conductance for Swiss pine in the local environment would help understand its specificity and similarity to other conifer species. In the case of using parameterization for a boreal coniferous from the Vegetation Manual of the International Cooperative Programme on Effects of Air Pollution on Natural Vegetation and Crops, validation of the model with the measurements without temperature adjustment of the conifer chamber achieved a coefficient of determination of R2=0.75. This result is not in contradiction with the previous researches. With the optimal set of parameters, obtained in this paper, the Jarvis model reaches R2=0.85. The data suggest that Jarvis-type models with appropriate parameterization are applicable for stomatal conductance estimation for Pinus cembra when the measurements do not modify the temperature regime.
Satellite-Observed Effects from Ozone Pollution and Climate Change on Growing-Season Vegetation Activity over China during 1982–2020
Authors: Wang Zhaosheng
Published: October 2021

Remote sensing vegetation index data contain important information about the effects of ozone pollution, climate change and other factors on vegetation growth. However, the absence of long-term observational data on surface ozone pollution and neglected air pollution-induced effects on vegetation growth have made it difficult to conduct in-depth studies on the long-term, large-scale ozone pollution effects on vegetation health. In this study, a multiple linear regression model was developed, based on normalized difference vegetation index (NDVI) data, ozone mass mixing ratio (OMR) data at 1000 hPa, and temperature (T), precipitation (P) and surface net radiation (SSR) data during 1982–2020 to quantitatively assess the impact of ozone pollution and climate change on vegetation growth in China on growing season. The OMR data showed an increasing trend in 99.9% of regions in China over the last 39 years, and both NDVI values showed increasing trends on a spatial basis with different ozone pollution levels. Additionally, the significant correlations between NDVI and OMR, temperature and SSR indicate that vegetation activity is closely related to ozone pollution and climate change. Ozone pollution affected 12.5% of NDVI, and climate change affected 26.7% of NDVI. Furthermore, the effects from ozone pollution and climate change on forest, shrub, grass and crop vegetation were evaluated. Notably, the impact of ozone pollution on vegetation growth was 0.47 times that of climate change, indicating that the impact of ozone pollution on vegetation growth cannot be ignored. This study not only deepens the understanding of the effects of ozone pollution and climate change on vegetation growth but also provides a research framework for the large-scale monitoring of air pollution on vegetation health using remote sensing vegetation data.
Omics Strategies in Current Advancements of Infectious Fish Disease Management
Authors: Natnan Maya , Mayalvanan Yosmetha , Jazamuddin Fahmeeda , Aizat Wan , Low Chen-Fei , Goh Hoe-Han , Azizan Kamalrul , Bunawan Hamidun , Baharum Syarul
Published: October 2021

Aquaculture is an important industry globally as it remains one of the significant alternatives of animal protein source supplies for humankind. Yet, the progression of this industry is being dampened by the increasing rate of fish mortality, mainly the outbreak of infectious diseases. Consequently, the regress in aquaculture ultimately results in the economy of multiple countries being affected due to the decline of product yields and marketability. By 2025, aquaculture is expected to contribute approximately 57% of fish consumption worldwide. Without a strategic approach to curb infectious diseases, the increasing demands of the aquaculture industry may not be sustainable and hence contributing to the over-fishing of wild fish. Recently, a new holistic approach that utilizes multi-omics platforms including transcriptomics, proteomics, and metabolomics is unraveling the intricate molecular mechanisms of host-pathogen interaction. This approach aims to provide a better understanding of how to improve the resistance of host species. However, no comprehensive review has been published on multi-omics strategies in deciphering fish disease etiology and molecular regulation. Most publications have only covered particular omics and no constructive reviews on various omics findings across fish species, particularly on their immune systems, have been described elsewhere. Our previous publication reviewed the integration of omics application for understanding the mechanism of fish immune response due to microbial infection. Hence, this review provides a thorough compilation of current advancements in omics strategies for fish disease management in the aquaculture industry. The discovery of biomarkers in various fish diseases and their potential advancement to complement the recent progress in combatting fish disease is also discussed in this review.
Cadmium-Induced Kidney Injury: Oxidative Damage as a Unifying Mechanism
Authors: Yan Liang-Jun , Allen Daniel C.
Published: October 2021

Cadmium is a nonessential metal that has heavily polluted the environment due to human activities. It can be absorbed into the human body via the gastrointestinal tract, respiratory tract, and the skin, and can cause chronic damage to the kidneys. The main site where cadmium accumulates and causes damage within the nephrons is the proximal tubule. This accumulation can induce dysfunction of the mitochondrial electron transport chain, leading to electron leakage and production of reactive oxygen species (ROS). Cadmium may also impair the function of NADPH oxidase, resulting in another source of ROS. These ROS together can cause oxidative damage to DNA, proteins, and lipids, triggering epithelial cell death and a decline in kidney function. In this article, we also reviewed evidence that the antioxidant power of plant extracts, herbal medicines, and pharmacological agents could ameliorate cadmium-induced kidney injury. Finally, a model of cadmium-induced kidney injury, centering on the notion that oxidative damage is a unifying mechanism of cadmium renal toxicity, is also presented. Given that cadmium exposure is inevitable, further studies using animal models are warranted for a detailed understanding of the mechanism underlying cadmium induced ROS production, and for the identification of more therapeutic targets.
TSMG: A Deep Learning Framework for Recognizing Human Learning Style Using EEG Signals
Authors: Zhang Bingxue , Shi Yang , Hou Longfeng , Yin Zhong , Chai Chengliang
Published: October 2021

Educational theory claims that integrating learning style into learning-related activities can improve academic performance. Traditional methods to recognize learning styles are mostly based on questionnaires and online behavior analyses. These methods are highly subjective and inaccurate in terms of recognition. Electroencephalography (EEG) signals have significant potential for use in the measurement of learning style. This study uses EEG signals to design a deep-learning-based model of recognition to recognize people’s learning styles with EEG features by using a non-overlapping sliding window, one-dimensional spatio-temporal convolutions, multi-scale feature extraction, global average pooling, and the group voting mechanism; this model is named the TSMG model (Temporal-Spatial-Multiscale-Global model). It solves the problem of processing EEG data of variable length, and improves the accuracy of recognition of the learning style by nearly 5% compared with prevalent methods, while reducing the cost of calculation by 41.93%. The proposed TSMG model can also recognize variable-length data in other fields. The authors also formulated a dataset of EEG signals (called the LSEEG dataset) containing features of the learning style processing dimension that can be used to test and compare models of recognition. This dataset is also conducive to the application and further development of EEG technology to recognize people’s learning styles.
An Agent-Based Model of Combination Oncolytic Viral Therapy and Anti-PD-1 Immunotherapy Reveals the Importance of Spatial Location When Treating Glioblastoma
Authors: Storey Kathleen M. , Jackson Trachette L.
Published: October 2021

Oncolytic viral therapies and immunotherapies are of growing clinical interest due to their selectivity for tumor cells over healthy cells and their immunostimulatory properties. These treatment modalities provide promising alternatives to the standard of care, particularly for cancers with poor prognoses, such as the lethal brain tumor glioblastoma (GBM). However, uncertainty remains regarding optimal dosing strategies, including how the spatial location of viral doses impacts therapeutic efficacy and tumor landscape characteristics that are most conducive to producing an effective immune response. We develop a three-dimensional agent-based model (ABM) of GBM undergoing treatment with a combination of an oncolytic Herpes Simplex Virus and an anti-PD-1 immunotherapy. We use a mechanistic approach to model the interactions between distinct populations of immune cells, incorporating both innate and adaptive immune responses to oncolytic viral therapy and including a mechanism of adaptive immune suppression via the PD-1/PD-L1 checkpoint pathway. We utilize the spatially explicit nature of the ABM to determine optimal viral dosing in both the temporal and spatial contexts. After proposing an adaptive viral dosing strategy that chooses to dose sites at the location of highest tumor cell density, we find that, in most cases, this adaptive strategy produces a more effective treatment outcome than repeatedly dosing in the center of the tumor.
Predict Early Recurrence of Resectable Hepatocellular Carcinoma Using Multi-Dimensional Artificial Intelligence Analysis of Liver Fibrosis
Authors: Liu I-Ting , Yen Chia-Sheng , Wang Wen-Lung , Tsai Hung-Wen , Chu Chang-Yao , Chang Ming-Yu , Hou Ya-Fu , Yen Chia-Jui
Published: October 2021

Background: Liver fibrosis is thought to be associated with early recurrence of hepatocellular carcinoma (HCC) after resection. To recognize HCC patients with higher risk of early recurrence, we used a second harmonic generation and two-photon excitation fluorescence (SHG/TPEF) microscopy to create a fully quantitative fibrosis score which is able to predict early recurrence. Methods: The study included 81 HCC patients receiving curative intent hepatectomy. Detailed fibrotic features of resected hepatic tissues were obtained by SHG/TPEF microscopy, and we used multi-dimensional artificial intelligence analysis to create a recurrence prediction model “combined index” according to the morphological collagen features of each patient’s non-tumor hepatic tissues. Results: Our results showed that the “combined index” can better predict early recurrence (area under the curve = 0.917, sensitivity = 81.8%, specificity = 90.5%), compared to alpha fetoprotein level (area under the curve = 0.595, sensitivity = 68.2%, specificity = 47.6%). Using a Cox proportional hazards analysis, a higher “combined index” is also a poor prognostic factor of disease-free survival and overall survival. Conclusions: By integrating multi-dimensional artificial intelligence and SHG/TPEF microscopy, we may locate patients with a higher risk of recurrence, follow these patients more carefully, and conduct further management if needed.
Neutrophils Extracellular Traps Inhibition Improves PD-1 Blockade Immunotherapy in Colorectal Cancer
Authors: Zhang Hongji , Wang Yu , Onuma Amblessed , He Jiayi , Wang Han , Xia Yujia , Lal Rhea , Cheng Xiang , Kasumova Gyulnara , Hu Zhiwei , Deng Meihong , Beane Joal D. , Kim Alex C. , Huang Hai , Tsung Allan
Published: October 2021

Immune checkpoint inhibitors can improve the prognosis of patients with advanced malignancy; however, only a small subset of advanced colorectal cancer patients in microsatellite-instability-high or mismatch-repair-deficient colorectal cancer can benefit from immunotherapy. Unfortunately, the mechanism behind this ineffectiveness is unclear. The tumor microenvironment plays a critical role in cancer immunity, and may contribute to the inhibition of immune checkpoint inhibitors and other novel immunotherapies in patients with advanced cancer. Herein, we demonstrate that the DNase I enzyme plays a pivotal role in the degradation of NETs, significantly dampening the resistance to anti-PD-1 blockade in a mouse colorectal cancer model by attenuating tumor growth. Remarkably, DNase I decreases tumor-associated neutrophils and the formation of MC38 tumor cell-induced neutrophil extracellular trap formation in vivo. Mechanistically, the inhibition of neutrophil extracellular traps with DNase I results in the reversal of anti-PD-1 blockade resistance through increasing CD8+ T cell infiltration and cytotoxicity. These findings signify a novel approach to targeting the tumor microenvironment using DNase I alone or in combination with immune checkpoint inhibitors.
Effects of Dams on Vertebrate Diversity: A Global Analysis
Authors: Bohada-Murillo Mauricio , Castaño-Villa Gabriel J. , Fontúrbel Francisco E.
Published: October 2021

Dams are crucial for water supply in human populations and are becoming more common globally for hydroelectric power generation. Dams alter natural habitats and their biodiversity; however, studies are inconclusive about their effects on them. This study aimed to examine the effects of dams on vertebrates and the determinants of changes in global biodiversity and their relationship with critical areas for conservation. We evaluated the effects of dams on vertebrate richness and abundance. We performed a meta-analysis based on 120 case studies. We evaluated the overall effect on richness and abundance and examined these effects regarding taxa, disturbance type, latitudinal zone, zoogeographic zone, biodiversity hotspots, dam size and purpose, and species extinction risk. We conducted an overall analysis that included all species, and then we conducted separate analyses for terrestrial and aquatic species. Dams had a negative effect on vertebrate richness but not on vertebrate abundance. These effects were influenced by larger dams with fragmentation and were more pronounced within hotspots and in countries with a low species extinction risk. Such negative effects were explained by terrestrial vertebrates (particularly birds and mammals) because species richness and the abundance of aquatic vertebrates (fish) were not affected by dams in any case. Our results showed that habitat fragmentation created by large dams changes vertebrate communities, negatively affecting species richness in some areas of conservation concern. We propose implementing reservoirs in areas where they would have a lower impact on biodiversity and avoiding large dams in priority areas for conservation and where endangered species inhabit.
Transcriptome Comparison of Secondary Metabolite Biosynthesis Genes Expressed in Cultured and Lichenized Conditions of Cladonia rangiferina
Authors: Sveshnikova Natalia , Piercey-Normore Michele D.
Published: October 2021

Lichen secondary metabolites are natural products of high medicinal and industrial value, which are produced by the fungal symbiont (mycobiont) of lichens in response to environmental changes. It has been shown that the cultured mycobiont is capable of secondary metabolite production, specifically polyketides, and polyketide production is affected by the presence or absence of the algal or cyanobacterial symbiont (photobiont). Identification of polyketide synthases encoding genes is, in turn, key for understanding the regulation of secondary metabolite synthesis. Using a previously established method of resynthesis for Cladonia rangiferina as well as the sequenced and assembled genome of that species, we compared transcriptomes of C. rangiferina cultured alone and resynthesized with the photobiont (Asterochloris glomerata) to reveal transcriptionally active genes in secondary metabolic gene clusters, as well some of the neighbouring genes, induced by the presence of the photobiont and events of lichenization. The results identify potential candidates for PKS genes in C. rangiferina, identify potential neighbouring genes in the PKS cluster, and offer insights into further research. The study provides preliminary insights into the activity of several identified biosynthetic gene clusters (BGC) as well as interactions of genes within those clusters.
Effects of Line Dancing on Mental Health in Seniors after COVID-19 Pandemic
Authors: Aliberti Sara , Raiola Gaetano
Published: October 2021

Line dancing is one of the most practiced dance styles by adults and seniors due to the ease of execution of choreography. Due to the COVID-19 pandemic prolonging the restrictions of physical and sports activities, the elderly population has been forced into increased sedentariness and social isolation, resulting in the development of symptoms of depression. The aim of this study was to investigate the effects of line dancing practice on the mental state of late second- and third-age dancers. The sample consisted of 14 Italian female dancers with an average age of 65 years old. The Geriatric Depression Scale was used to verify whether 3 months of LD classes were able to produce improvements. Paired Samples T-Test and effect size were performed to test the difference between pre- and post-training protocol. The result was statistically significant (p < 0.05). Dancers improved their state of depression; in particular, they felt a better satisfaction in their life (d = 0.6), a greater interest in activities (d = 1), less boredom (d = 0.8), a good mood most of the time (d = 0.8), greater happiness throughout the day (d = 0.7), and the perception of a wonderful life (d = 0.5). Line dancing has proven to be an effective physical activity for improving the state of depression in late second- and third-age dancers.
Model Predictive Control for Autonomous Driving Vehicles
Authors: Vu Trieu Minh , Moezzi Reza , Cyrus Jindrich , Hlava Jaroslav
Published: October 2021

The field of autonomous driving vehicles is growing and expanding rapidly. However, the control systems for autonomous driving vehicles still pose challenges, since vehicle speed and steering angle are always subject to strict constraints in vehicle dynamics. The optimal control action for vehicle speed and steering angular velocity can be obtained from the online objective function, subject to the dynamic constraints of the vehicle’s physical limitations, the environmental conditions, and the surrounding obstacles. This paper presents the design of a nonlinear model predictive controller subject to hard and softened constraints. Nonlinear model predictive control subject to softened constraints provides a higher probability of the controller finding the optimal control actions and maintaining system stability. Different parameters of the nonlinear model predictive controller are simulated and analyzed. Results show that nonlinear model predictive control with softened constraints can considerably improve the ability of autonomous driving vehicles to track exactly on different trajectories.
Design and Analysis of Asynchronous Sampling Duty Cycle Corrector
Authors: Park Gijin , Han Jaeduk , Bae Woorham
Published: October 2021

This paper presents a duty cycle correction scheme based on asynchronous sampling and associated settling analysis. The proposed duty cycle corrector circuit consumes less power and area compared to other corrector circuits due to the low-frequency operation of asynchronous sampling. However, the settling behavior of an asynchronous sampling duty cycle corrector is limited in some operation conditions, which degrades its robustness and performance. This paper, therefore, performs analysis on the settling behavior of the asynchronous sampling in various operating conditions and proposes a control scheme to avoid the lagged settling. To verify the proposed duty cycle corrector and its analysis, a prototype design is implemented in a 40-nm CMOS process and its performance is verified by post-layout simulations. The proposed duty cycle corrector achieved very small duty cycle errors (less than 0.8%) and consumed 540 uW per one DCC unit.
Performance Improvement of Reluctance Synchronous Motor Using Brain Emotional Learning Based Intelligent Controller
Authors: Ahmadi Kamarposhti Mehrdad , Shokouhandeh Hassan , Colak Ilhami , Eguchi Kei
Published: October 2021

In this paper, intelligent control of a reluctance synchronous motor by an emotional controller, considering the effect of magnetic saturation on implementation, is analyzed; the maximum torque per ampere (MTPA) strategy is provided. According to the application of the proposed control scheme, the structure adequately performs the control of speed and magnetic flux of the reluctance synchronous motor drive. Additionally, the application of intelligent control based on an emotional learning system has provided adequate results to create a proper control process. The control function of a SynRM drive based on vector control in a rotor machine was compared with another based on emotional controllers and a PI controller regulated by genetic algorithms. The result of this comparison was the improvement of control functions by the controller based on the emotional controller. In addition, the MTPA based on search algorithms was well implemented in different situations. Due to its simplicity and independence from system parameters, the emotional controller can be considered as a potential operational method in the industry.