bluuebunny/crossref_metadata_2025 huggingface dataset:
Large-Scale Data Mining of Rapid Residue Detection Assay Data From HTML and PDF Documents: Improving Data Access and Visualization for Veterinarians
Authors: Jaberi-Douraki Majid , Taghian Dinani Soudabeh , Millagaha Gedara Nuwan Indika , Xu Xuan , Richards Emily , Maunsell Fiona , Zad Nader , Tell Lisa A.
Published: July 2021

Extra-label drug use in food animal medicine is authorized by the US Animal Medicinal Drug Use Clarification Act (AMDUCA), and estimated withdrawal intervals are based on published scientific pharmacokinetic data. Occasionally there is a paucity of scientific data on which to base a withdrawal interval or a large number of animals being treated, driving the need to test for drug residues. Rapid assay commercial farm-side tests are essential for monitoring drug residues in animal products to protect human health. Active ingredients, sensitivity, matrices, and species that have been evaluated for commercial rapid assay tests are typically reported on manufacturers' websites or in PDF documents that are available to consumers but may require a special access request. Additionally, this information is not always correlated with FDA-approved tolerances. Furthermore, parameter changes for these tests can be very challenging to regularly identify, especially those listed on websites or in documents that are not publicly available. Therefore, artificial intelligence plays a critical role in efficiently extracting the data and ensure current information. Extracting tables from PDF and HTML documents has been investigated both by academia and commercial tool builders. Research in text mining of such documents has become a widespread yet challenging arena in implementing natural language programming. However, techniques of extracting tables are still in their infancy and being investigated and improved by researchers. In this study, we developed and evaluated a data-mining method for automatically extracting rapid assay data from electronic documents. Our automatic electronic data extraction method includes a software package module, a developed pattern recognition tool, and a data mining engine. Assay details were provided by several commercial entities that produce these rapid drug residue assay tests. During this study, we developed a real-time conversion system and method for reflowing contents in these files for accessibility practice and research data mining. Embedded information was extracted using an AI technology for text extraction and text mining to convert to structured formats. These data were then made available to veterinarians and producers via an online interface, allowing interactive searching and also presenting the commercial test assay parameters in reference to FDA-approved tolerances.
Genome-Wide Association Studies Reveal Neurological Genes for Dog Herding, Predation, Temperament, and Trainability Traits
Authors: Shan Shuwen , Xu Fangzheng , Brenig Bertram
Published: July 2021

Genome-wide association study (GWAS) using dog breed standard values as phenotypic measurements is an efficient way to identify genes associated with morphological and behavioral traits. As a result of strong human purposeful selections, several specialized behavioral traits such as herding and hunting have been formed in different modern dog breeds. However, genetic analyses on this topic are rather limited due to the accurate phenotyping difficulty for these complex behavioral traits. Here, 268 dog whole-genome sequences from 130 modern breeds were used to investigate candidate genes underlying dog herding, predation, temperament, and trainability by GWAS. Behavioral phenotypes were obtained from the American Kennel Club based on dog breed standard descriptions or groups (conventional categorization of dog historical roles). The GWAS results of herding behavior (without body size as a covariate) revealed 44 significantly associated sites within five chromosomes. Significantly associated sites on CFA7, 9, 10, and 20 were located either in or near neuropathological or neuronal genes including THOC1, ASIC2, MSRB3, LLPH, RFX8, and CHL1. MSRB3 and CHL1 genes were reported to be associated with dog fear. Since herding is a restricted hunting behavior by removing killing instinct, 36 hounds and 55 herding dogs were used to analyze predation behavior. Three neuronal-related genes (JAK2, MEIS1, and LRRTM4) were revealed as candidates for predation behavior. The significantly associated variant of temperament GWAS was located within ACSS3 gene. The highest associated variant in trainability GWAS is located on CFA22, with no variants detected above the Bonferroni threshold. Since dog behaviors are correlated with body size, we next incorporate body mass as covariates into GWAS; and significant signals around THOC1, MSRB3, LLPH, RFX8, CHL1, LRRTM4, and ACSS3 genes were still detected for dog herding, predation, and temperament behaviors. In humans, these candidate genes are either involved in nervous system development or associated with mental disorders. In conclusion, our results imply that these neuronal or psychiatric genes might be involved in biological processes underlying dog herding, predation, and temperament behavioral traits.
Performance Evaluation of Electrically Driven Agricultural Implements Powered by an External Generator
Authors: Varani Massimiliano , Mattetti Michele , Molari Giovanni
Published: July 2021

In the last decade, many studies have been conducted on tractor and agricultural machinery electrification. In particular, the electrification of power take-off (PTO)-powered implements could support many benefits, such as improved comfort and safety during implement connection, less noisiness, accurate control of the implement rotational speed, and fuel consumption reduction. However, commercially available tractors do not generate sufficient electric power to run electrified implements. A solution to this issue is powering eventual electrified implements with an external electric generator powered by the PTO and mounted with the front three-point linkage. This study aimed to evaluate the potential benefits of using this combination with respect to PTO powered implements. The types of implements analyzed in detail in this study were a sprayer and a mulcher. Field tests were performed acquiring performance, operational, and environmental parameters. Results show that on the electrified implements, the absence of the cardan shaft and hydraulic remotes shortened the time required for the hitching phase and reduced the in-work noisiness. Field tests demonstrated that the electrified implements permitted an improvement of the fuel consumption per hectare, up to 33.3% and 29.8% lower than their PTO-powered homologue for the sprayer and the mulcher, respectively.
Diagnostic Ability of Methods Depicting Distress of Tumor-Bearing Mice
Authors: Xie Wentao , Kordt Marcel , Palme Rupert , Grambow Eberhard , Vollmar Brigitte , Zechner Dietmar
Published: July 2021

Subcutaneous tumor models in mice are the most commonly used experimental animal models in cancer research. To improve animal welfare and the quality of scientific studies, the distress of experimental animals needs to be minimized. For this purpose, one must assess the diagnostic ability of readout parameters to evaluate distress. In this study, we evaluated different noninvasive readout parameters such as body weight change, adjusted body weight change, faecal corticosterone metabolites concentration, burrowing activity and a distress score by utilising receiver operating characteristic curves. Eighteen immunocompromised NOD.Cg-Prkdcscid Il2rgtm1Wjl/SzJ mice were used for this study; half were subcutaneously injected with A-375 cells (human malignant melanoma cells) that resulted in large tumors. The remaining mice were inoculated with SCL-2 cells (cutaneous squamous cell carcinoma cells), which resulted in small tumors. The adjusted body weight and faecal corticosterone metabolites concentration had a high diagnostic ability in distinguishing between mice before cancer cell injection and mice bearing large tumors. All other readout parameters had a low diagnostic ability. These results suggest that adjusted body weight and faecal corticosterone metabolites are useful to depict the distress of mice bearing large subcutaneous tumors.
Free-Floating Aggregate and Single-Cell-Initiated Biofilms of Staphylococcus aureus
Authors: Gupta Tripti Thapa , Gupta Niraj K. , Burback Peter , Stoodley Paul
Published: July 2021

Periprosthetic joint infection (PJI) occurring after artificial joint replacement is a major clinical issue requiring multiple surgeries and antibiotic interventions. Staphylococcus aureus is the common bacteria responsible for PJI. Recent in vitro research has shown that staphylococcal strains rapidly form free-floating aggregates in the presence of synovial fluid (SF) with biofilm-like resistance to antimicrobial agents. However, the development of biofilms formed from these aggregates under shear have not been widely investigated. Thus, in this study, we examined the progression of attached biofilms from free-floating aggregates. Biofilms were grown for 24 h in flow cells on titanium discs after inoculation with either pre-aggregated or single planktonic cells. Image analysis showed no significant difference between the biofilm formed from aggregates vs. the planktonic cells in terms of biomass, surface area, and thickness. Regarding antibiotic susceptibility, there were 1 and 2 log reductions in biofilms formed from single cells and aggregates, respectively, when treated with vancomycin for 24 h. Thus, this study demonstrates the formation of biofilm from free-floating aggregates and follows a similar developmental time period and shows similar antibiotic tolerance to more traditionally inoculated in vitro flow cell biofilms.
A Combined Drug Treatment That Reduces Mitochondrial Iron and Reactive Oxygen Levels Recovers Insulin Secretion in NAF-1-Deficient Pancreatic Cells
Authors: Karmi Ola , Sohn Yang-Sung , Marjault Henri-Baptiste , Israeli Tal , Leibowitz Gil , Ioannidis Konstantinos , Nahmias Yaakov , Mittler Ron , Cabantchik Ioav Z. , Nechushtai Rachel
Published: July 2021

Decreased insulin secretion, associated with pancreatic β-cell failure, plays a critical role in many human diseases including diabetes, obesity, and cancer. While numerous studies linked β-cell failure with enhanced levels of reactive oxygen species (ROS), the development of diabetes associated with hereditary conditions that result in iron overload, e.g., hemochromatosis, Friedreich’s ataxia, and Wolfram syndrome type 2 (WFS-T2; a mutation in CISD2, encoding the [2Fe-2S] protein NAF-1), underscores an additional link between iron metabolism and β-cell failure. Here, using NAF-1-repressed INS-1E pancreatic cells, we observed that NAF-1 repression inhibited insulin secretion, as well as impaired mitochondrial and ER structure and function. Importantly, we found that a combined treatment with the cell permeant iron chelator deferiprone and the glutathione precursor N-acetyl cysteine promoted the structural repair of mitochondria and ER, decreased mitochondrial labile iron and ROS levels, and restored glucose-stimulated insulin secretion. Additionally, treatment with the ferroptosis inhibitor ferrostatin-1 decreased cellular ROS formation and improved cellular growth of NAF-1 repressed pancreatic cells. Our findings reveal that suppressed expression of NAF-1 is associated with the development of ferroptosis-like features in pancreatic cells, and that reducing the levels of mitochondrial iron and ROS levels could be used as a therapeutic avenue for WFS-T2 patients.
Atmospheric Wind Field Modelling with OpenFOAM for Near-Ground Gas Dispersion
Authors: Schalau Sebastian , Habib Abdelkarim , Michel Simon
Published: July 2021

CFD simulations of near-ground gas dispersion depend significantly on the accuracy of the wind field. When simulating wind fields with conventional RANS turbulence models, the velocity and turbulence profiles specified as inlet boundary conditions change rapidly in the approach flow region. As a result, when hazardous materials are released, the extent of hazardous areas is calculated based on an approach flow that differs significantly from the boundary conditions defined. To solve this problem, a turbulence model with consistent boundary conditions was developed to ensure a horizontally homogeneous approach flow. Instead of the logarithmic vertical velocity profile, a power law is used to overcome the problem that with the logarithmic profile, negative velocities would be calculated for heights within the roughness length. With this, the problem that the distance of the wall-adjacent cell midpoint has to be higher than the roughness length is solved, so that a high grid resolution can be ensured even in the near-ground region which is required to simulate gas dispersion. The evaluation of the developed CFD model using the German guideline VDI 3783/9 and wind tunnel experiments with realistic obstacle configurations showed a good agreement between the calculated and the measured values and the ability to achieve a horizontally homogenous approach flow.
Assessments of Solar, Thermal and Net Irradiance from Simple Solar Geometry and Routine Meteorological Measurements in the Pannonian Basin
Authors: Popov Zlatica , Nagy Zoltán , Baranka Györgyi , Weidinger Tamás
Published: July 2021

In this paper, we discussed several different procedures for calculating irradiation from routine weather measurements and observations. There are between four and eight frequently used parameterizations of radiation balance components in meteorological preprocessors, and we investigated them. First of all, the estimated and measured solar and net irradiance were compared. Afterwards, the estimated and measured longwave irradiance were investigated. Then, we recalculated the net irradiance from the sum of global solar irradiance, longwave downwelling irradiance, reflect solar irradiance and upwelling longwave irradiance. Statistical estimates of the described methods were also recalculated compared with each shortwave and longwave radiation budget component measured separately with WMO first-class radiation instruments (Kipp&Zonen CMP6 and CMP11 and CGR3 and CGR4) in the Agrometeorological Observatory Debrecen, Hungary during one-year time period. Finally, we compared the calculated and measured values for longer periods (2008–2010 and 2008–2017) through statistical errors. The suggested parameterizations of the net radiation based on the separately parameterized all radiation balance components were: Foken’s calculation for clear sky solar global irradiance, Beljaars and Bosveld parameterization for albedo, Dilley and O’Brien methodology for the clear sky incoming longwave (LW) irradiance and Holstlag and Van Ulden cloudiness correction for all sky incoming LW and for the LW outgoing irradiance.
Detection of Red Wine Faults over Time with Flash Profiling and the Electronic Tongue
Authors: Paup Victoria D. , Cook-Barton Tara , Diako Charles , Edwards Charles G. , Ross Carolyn F.
Published: July 2021

Wine faults, often caused by spoilage microorganisms, are considered negative sensory attributes, and may result in substantial economic losses. The objective of this study was to use the electronic tongue (e-tongue) and flash sensory profiling (FP) to evaluate changes in red wine over time due to the presence of different spoilage microorganisms. Merlot wine was inoculated with one of the following microorganisms: Brettanomyces bruxellensis, Lactobacillus brevis, Pediococcus parvulus, or Acetobacter pasteurianus. These wines were analyzed weekly until Day 42 using the e-tongue and FP, with microbial plate counts. Over time, both FP and e-tongue differentiated the wines. The e-tongue showed a low discrimination among microorganisms up to Day 14 of storage. However, at Day 21 and continuing to Day 42, the e-tongue discriminated among the samples with a discrimination index of 91. From the sensory FP data, assessors discriminated among the wines starting at Day 28. Non-spoilage terms were used to describe the wines at significantly higher frequency for all time points until Day 42, at which point the use of spoilage terms was significantly higher (p < 0.05). These results suggest that application of these novel techniques may be the key to detecting and limiting financial losses associated with wine faults.
A Modified Brewing Procedure Informed by the Enzymatic Profiles of Gluten-Free Malts Significantly Improves Fermentable Sugar Generation in Gluten-Free Brewing
Authors: Ledley Andrew J. , Elias Ryan J. , Hopfer Helene , Cockburn Darrell W.
Published: July 2021

The mashing step underpins the brewing process, during which the endogenous amylolytic enzymes in the malt, chiefly β-amylase, α-amylase, and limit dextrinase, act concurrently to rapidly hydrolyze malt starch to fermentable sugars. With barley malts, the mashing step is relatively straightforward, due in part to malted barley’s high enzyme activity, enzyme thermostabilities, and gelatinization properties. However, barley beers also contain gluten and individuals with celiac disease or other gluten intolerances should avoid consuming these beers. Producing gluten-free beer from gluten-free malts is difficult, generally because gluten-free malts have lower enzyme activities. Strategies to produce gluten-free beers commonly rely on exogenous enzymes to perform the hydrolysis. In this study, it was determined that the pH optima of the enzymes from gluten-free malts correspond to regions already typically targeted for barley mashes, but that a lower mashing temperature was required as the enzymes exhibited low thermostability at common mashing temperatures. The ExGM decoction mashing procedure was developed to retain enzyme activity, but ensure starch gelatinization, and demonstrates a modified brewing procedure using gluten-free malts, or a combination of malts with sub-optimal enzyme profiles, that produces high fermentable sugar concentrations. This study demonstrates that gluten-free malts can produce high fermentable sugar concentrations without requiring enzyme supplementation.
Numerical Models Can Assist Choice of an Aortic Phantom for In Vitro Testing
Authors: Comunale Giulia , Di Micco Luigi , Boso Daniela Paola , Susin Francesca Maria , Peruzzo Paolo
Published: July 2021

(1) Background: The realization of appropriate aortic replicas for in vitro experiments requires a suitable choice of both the material and geometry. The matching between the grade of details of the geometry and the mechanical response of the materials is an open issue that deserves attention. (2) Methods: To explore this issue, we performed a series of Fluid–Structure Interaction simulations, which compared the dynamics of three aortic models. Specifically, we reproduced a patient-specific geometry with a wall of biological tissue or silicone, and a parametric geometry based on in vivo data made in silicone. The biological tissue and the silicone were modeled with a fiber-oriented anisotropic and isotropic hyperelastic model, respectively. (3) Results: Clearly, both the aorta’s geometry and its constitutive material contribute to the determination of the aortic arch deformation; specifically, the parametric aorta exhibits a strain field similar to the patient-specific model with biological tissue. On the contrary, the local geometry affects the flow velocity distribution quite a lot, although it plays a minor role in the helicity along the arch. (4) Conclusions: The use of a patient-specific prototype in silicone does not a priori ensure a satisfactory reproducibility of the real aorta dynamics. Furthermore, the present simulations suggest that the realization of a simplified replica with the same compliance of the real aorta is able to mimic the overall behavior of the vessel.
The Emerging Importance of Tumor Genomics in Operable Non-Small Cell Lung Cancer
Authors: Lengel Harry B. , Connolly James G. , Jones Gregory D. , Caso Raul , Zhou Jian , Sanchez-Vega Francisco , Mastrogiacomo Brooke , Isbell James M. , Li Bob T. , Liu Yuan , Rekhtman Natasha , Jones David R.
Published: July 2021

During the last two decades, next-generation sequencing (NGS) has played a key role in enhancing non-small cell lung cancer treatment paradigms through the application of “targeted therapy” in advanced and metastatic disease. The use of specific tyrosine kinase inhibitors in patients with oncogenic driver alterations, such as EGFR, ALK, ROS1, BRAF V600E, MET, and NTRK mutations, among others, has changed treatment approaches and improved outcomes in patients with late-stage disease. Although NGS technology has mostly been used in the setting of systemic therapy to identify targets, response to therapy, and mechanisms of resistance, it has multiple potential applications for patients with earlier-stage disease, as well. In this review, we discuss the emerging role of NGS technologies to better understand tumor biology in patients with non-small cell lung cancer who are undergoing surgery with curative intent. In this patient cohort, we examine tumor heterogeneity, the underlying tumor genomics associated with lung adenocarcinoma subtypes, the prediction of recurrence after complete surgical resection, the use of plasma circulating tumor DNA for detection of early cancers and monitoring for minimal residual disease, the differentiation of separate primaries from intrapulmonary metastases, and the use of NGS to guide induction and adjuvant therapies.
Current Surgical Management of Peri-Hilar and Intra-Hepatic Cholangiocarcinoma
Authors: Lauterio Andrea , De Carlis Riccardo , Centonze Leonardo , Buscemi Vincenzo , Incarbone Niccolò , Vella Ivan , De Carlis Luciano
Published: July 2021

Cholangiocarcinoma accounts for approximately 10% of all hepatobiliary tumors and represents 3% of all new-diagnosed malignancies worldwide. Intrahepatic cholangiocarcinoma (i-CCA) accounts for 10% of all cases, perihilar (h-CCA) cholangiocarcinoma represents two-thirds of the cases, while distal cholangiocarcinoma accounts for the remaining quarter. Originally described by Klatskin in 1965, h-CCA represents one of the most challenging tumors for hepatobiliary surgeons, mainly because of the anatomical vascular relationships of the biliary confluence at the hepatic hilum. Surgery is the only curative option, with the goal of a radical, margin-negative (R0) tumor resection. Continuous efforts have been made by hepatobiliary surgeons in order to achieve R0 resections, leading to the progressive development of aggressive approaches that include extended hepatectomies, associating liver partition, and portal vein ligation for staged hepatectomy, pre-operative portal vein embolization, and vascular resections. i-CCA is an aggressive biliary cancer that arises from the biliary epithelium proximal to the second-degree bile ducts. The incidence of i-CCA is dramatically increasing worldwide, and surgical resection is the only potentially curative therapy. An aggressive surgical approach, including extended liver resection and vascular reconstruction, and a greater application of systemic therapy and locoregional treatments could lead to an increase in the resection rate and the overall survival in selected i-CCA patients. Improvements achieved over the last two decades and the encouraging results recently reported have led to liver transplantation now being considered an appropriate indication for CCA patients.
Diagnosis of Helicobacter pylori Infection and Recent Advances
Authors: Yang Hang , Hu Bing
Published: July 2021

Background: Helicobacter pylori (H. pylori) infects approximately 50% of the world population. Its infection is associated with gastropathies, extra-gastric digestive diseases, and diseases of other systems. There is a canonical process from acute-on-chronic inflammation, chronic atrophic gastritis (CAG), intestinal metaplasia (IM), dysplasia, and intraepithelial neoplasia, eventually to gastric cancer (GC). H. pylori eradication abolishes the inflammatory response and early treatment prevents the progression to preneoplastic lesions. Methods: the test-and-treat strategy, endoscopy-based strategy, and screen-and-treat strategy are recommended to prevent GC based on risk stratification, prevalence, and patients’ clinical manifestations and conditions. Challenges contain false-negative results, increasing antibiotic resistance, decreasing eradication rate, and poor retesting rate. Present diagnosis methods are mainly based on invasive endoscopy and noninvasive laboratory testing. Results: to improve the accuracy and effectiveness and reduce the missed diagnosis, some advances were achieved including newer imaging techniques (such as image-enhanced endoscopy (IEE), artificial intelligence (AI) technology, and quantitative real-time polymerase chain reaction (qPCR) and digital PCR (dPCR). Conclusion: in the article, we summarized the diagnosis methods of H. pylori infection and recent advances, further finding out the opportunities in challenges.
Forecasting COVID-19 Severity by Intelligent Optical Fingerprinting of Blood Samples
Authors: Faria Simão P. , Carpinteiro Cristiana , Pinto Vanessa , Rodrigues Sandra M. , Alves José , Marques Filipe , Lourenço Marta , Santos Paulo H. , Ramos Angélica , Cardoso Maria J. , Guimarães João T. , Rocha Sara , Sampaio Paula , Clifton David A. , Mumtaz Mehak , Paiva Joana S.
Published: July 2021

Forecasting COVID-19 disease severity is key to supporting clinical decision making and assisting resource allocation, particularly in intensive care units (ICUs). Here, we investigated the utility of time- and frequency-related features of the backscattered signal of serum patient samples to predict COVID-19 disease severity immediately after diagnosis. ICU admission was the primary outcome used to define disease severity. We developed a stacking ensemble machine learning model including the backscattered signal features (optical fingerprint), patient comorbidities, and age (AUROC = 0.80), which significantly outperformed the predictive value of clinical and laboratory variables available at hospital admission (AUROC = 0.71). The information derived from patient optical fingerprints was not strongly correlated with any clinical/laboratory variable, suggesting that optical fingerprinting brings unique information for COVID-19 severity risk assessment. Optical fingerprinting is a label-free, real-time, and low-cost technology that can be easily integrated as a front-line tool to facilitate the triage and clinical management of COVID-19 patients.
Sinus Mucosa Thickness Changes and Ostium Involvement after Maxillary Sinus Floor Elevation in Sinus with Septa. A Cone Beam Computed Tomography Study
Authors: Kato Shingo , Omori Yuki , Kanayama Masatsugu , Hirota Atsuya , Ferri Mauro , Apaza Alccayhuaman Karol Alí , Botticelli Daniele
Published: July 2021

Background: A thickening of the sinus mucosa is observed after sinus floor augmentation. The objective of this retrospective study was to evaluate the influence of the presence of septa in the dimensional variation and ostium involvement over time of the Schneiderian mucosa after sinus floor augmentation. Materials and Methods: Fifteen sinuses with septa (septa group) and 15 without (control group) were selected. CBCTs taken before surgery, and were analyzed after 1 week and after 9 months. Schneiderian membrane thickness changes over time and involvement of the ostium were evaluated. Results: Four perforations occurred in the septa group and none in the control group. After 1 week of healing, the sinus mucosa thickness increased in height by 5.7 mm and 7.1 mm in the septa and control groups, respectively. In this period, the patency of the ostium decreased in both groups, and three infundibula were obstructed in the septa group, and five in the control group. The mucosa was thicker and the edema was closer to the ostium in the control compared to in the septa group. After 9 months of healing, the dimensions regressed to normal pattern and no obstruction of the infundibula were observed. No statistically significant differences were found between septa and control groups. Conclusions: after one week of healing, the sinus mucosa increased in dimensions in both septa and control groups. However, the sinus mucosa presented a tendency of being thicker and closer to the ostium, resulting in a higher number of infundibula obstructions, in the control group compared to in the septa group. After 9 months, the sinus mucosa regressed to normal dimensions and no obstructions of the infundibula were observed in any group.
First-Year Life Science Students’ Understanding of the Role of Plants in the Ecosystem—A Concept Network Analysis
Authors: Södervik Ilona , Nousiainen Maija , Koponen Ismo. T.
Published: July 2021

The purpose of this study is to increase the understanding about undergraduate life science students’ conceptions concerning the role of photosynthesizing plants in the ecosystem, utilizing a network analysis method. Science learning requires the integration and linking of abstract and often counterintuitive concepts successfully into multifaceted networks. The quality of these networks, together with their abilities to communicate via the language of science, influences students’ success in academic, verbal problem-solving tasks. This study contributes to investigating students’ understanding, utilizing a modern network analysis method in exploring first-year university life science students’ written answers. In this study, a total of 150 first-year life science students answered two open-ended tasks related to the role of photosynthesizing plants in the ecosystem. A network analysis tool was used in exploring the occurrence of different-level science concepts and the interrelatedness between these concepts in students’ verbal outputs. The results showed that the richness of concept networks and students’ use of macro-concepts were remarkably varied between the tasks. Higher communicability measures were connected to the more abundant existence of macro-concepts in the task concerning the role of plants from the food-chain perspective. In the answers for the task concerning the role of plants regarding the atmosphere, the students operated mainly with single facts, and there were only minor interconnections made between the central concepts. On the basis of these results, the need for more all-encompassing biology teaching concerning complex environmental and socio-economic problems became evident. Thus, methodological and pedagogical contributions are discussed.
Active Learning: Basic Science Workshops, Clinical Science Cases, and Medical Role-Playing in an Undergraduate Biology Course
Authors: Church Frank C.
Published: July 2021

Effective undergraduate courses increasingly blend elements of active learning with a more traditional lecture format. Designing and implementing active learning sessions that engage, educate, and are challenging and workable in a group setting are essential for student learners. In addition, active learning sessions take concepts of fundamental knowledge and apply them to a more relevant and real-world environment. Thus, effective active learning lesson plans enable students to thrive in their educational experience, and this potentially enhances material retention. Presented here are examples of the critical components of active learning engagement in an undergraduate biology course. First, basic science workshops let students apply basic scientific principles to biomedical science scenarios. Second, clinical science case studies help students understand the interplay between basic and clinical sciences in a patient-based medical case format. Finally, medical role-playing allows student teams to understand the complexity of medical care, moving from the patient’s presenting symptoms to formulating a diagnosis and treatment plan. These exercises strengthen several aspects of active learning, especially those related to student-team-based collaboration, conversation, coordination, and compilation.
The Academic Impacts of 2015 Nepal Earthquake: Evidence from Two Secondary Schools in Sindhupalchok District
Authors: Sapkota Jeet Bahadur , Neupane Pramila
Published: July 2021

How do natural disasters affect academic performance? Despite numerous studies having been conducted after the 2015 Nepal earthquake, the academic impacts of this tragic event have rarely been explored. Applying the OLS estimation on the microdata collected through a questionnaire survey among 189 secondary school students of two secondary schools in one of the hardest-hit rural villages, we found that students’ average annual test scores dropped by 7% after the earthquake. Human losses measured by the incidence of death or injury and economic losses proxied by the level of house damage in a respondent’s family were found to be significant in the decline in the annual test scores of the respondents. Because secondary schools are usually not very close for most of the students in rural mountainous communities, we controlled for time taken to reach school, which was also found to significantly increase the magnitude of the drop in the test score. However, students’ level of happiness measured using the Oxford Happiness Questionnaire (OHQ) and the mother’s level of education were found to be significant in reducing the magnitude of the drop in the test score of students. The findings suggest more support is needed for students who faced higher levels of human and economic loss in their family.
Secure Cyber Defense: An Analysis of Network Intrusion-Based Dataset CCD-IDSv1 with Machine Learning and Deep Learning Models
Authors: Thapa Niraj , Liu Zhipeng , Shaver Addison , Esterline Albert , Gokaraju Balakrishna , Roy Kaushik
Published: July 2021

Anomaly detection and multi-attack classification are major concerns for cyber defense. Several publicly available datasets have been used extensively for the evaluation of Intrusion Detection Systems (IDSs). However, most of the publicly available datasets may not contain attack scenarios based on evolving threats. The development of a robust network intrusion dataset is vital for network threat analysis and mitigation. Proactive IDSs are required to tackle ever-growing threats in cyberspace. Machine learning (ML) and deep learning (DL) models have been deployed recently to detect the various types of cyber-attacks. However, current IDSs struggle to attain both a high detection rate and a low false alarm rate. To address these issues, we first develop a Center for Cyber Defense (CCD)-IDSv1 labeled flow-based dataset in an OpenStack environment. Five different attacks with normal usage imitating real-life usage are implemented. The number of network features is increased to overcome the shortcomings of the previous network flow-based datasets such as CIDDS and CIC-IDS2017. Secondly, this paper presents a comparative analysis on the effectiveness of different ML and DL models on our CCD-IDSv1 dataset. In this study, we consider both cyber anomaly detection and multi-attack classification. To improve the performance, we developed two DL-based ensemble models: Ensemble-CNN-10 and Ensemble-CNN-LSTM. Ensemble-CNN-10 combines 10 CNN models developed from 10-fold cross-validation, whereas Ensemble-CNN-LSTM combines base CNN and LSTM models. This paper also presents feature importance for both anomaly detection and multi-attack classification. Overall, the proposed ensemble models performed well in both the 10-fold cross-validation and independent testing on our dataset. Together, these results suggest the robustness and effectiveness of the proposed IDSs based on ML and DL models on the CCD-IDSv1 intrusion detection dataset.
Image Fusion Algorithm Selection Based on Fusion Validity Distribution Combination of Difference Features
Authors: Ji Linna , Yang Fengbao , Guo Xiaoming
Published: July 2021

Aiming at addressing the problem whereby existing image fusion models cannot reflect the demand of diverse attributes (e.g., type or amplitude) of difference features on algorithms, leading to poor or invalid fusion effect, this paper puts forward the construction and combination of difference features fusion validity distribution based on intuition-possible sets to deal with the selection of algorithms with better fusion effect in dual mode infrared images. Firstly, the distances of the amplitudes of difference features between fused images and source images are calculated. The distances can be divided into three levels according to the fusion result of each algorithm, which are regarded as intuition-possible sets of fusion validity of difference features, and a novel construction method of fusion validity distribution based on intuition-possible sets is proposed. Secondly, in view of multiple amplitude intervals of each difference feature, this paper proposes a distribution combination method based on intuition-possible set ordering. Difference feature score results are aggregated by a fuzzy operator. Joint drop shadows of difference feature score results are obtained. Finally, the experimental results indicate that our proposed method can achieve optimal selection of algorithms that has relatively better effect on the fusion of difference features according to the varied feature amplitudes.
Plants’ Epigenetic Mechanisms and Abiotic Stress
Authors: Miryeganeh Matin
Published: July 2021

Plants are sessile organisms that need to adapt to constantly changing environmental conditions. Unpredictable climate change places plants under a variety of abiotic stresses. Studying the regulation of stress-responsive genes can help to understand plants’ ability to adapt to fluctuating environmental conditions. Changes in epigenetic marks such as histone modifications and DNA methylation are known to regulate gene expression by their dynamic variation in response to stimuli. This can then affect their phenotypic plasticity, which helps with the adaptation of plants to adverse conditions. Epigenetic marks may also provide a mechanistic basis for stress memory, which enables plants to respond more effectively and efficiently to recurring stress and prepare offspring for potential future stresses. Studying epigenetic changes in addition to genetic factors is important to better understand the molecular mechanisms underlying plant stress responses. This review summarizes the epigenetic mechanisms behind plant responses to some main abiotic stresses.
Basil as Secondary Crop in Cascade Hydroponics: Exploring Salinity Tolerance Limits in Terms of Growth, Amino Acid Profile, and Nutrient Composition
Authors: Avdouli Denisa , Max Johannes F. J. , Katsoulas Nikolaos , Levizou Efi
Published: July 2021

In a cascade hydroponic system, the used nutrient solution drained from a primary crop is directed to a secondary crop, enhancing resource-use efficiency while minimizing waste. Nevertheless, the inevitably increased EC of the drainage solution requires salinity-tolerant crops. The present study explored the salinity-tolerance thresholds of basil to evaluate its potential use as a secondary crop in a cascade system. Two distinct but complemented approaches were used; the first experiment examined basil response to increased levels of salinity (5, 10 and 15 dS m−1, compared with 2 dS m−1 of control) to identify the limits, and the second experiment employed a cascade system with cucumber as a primary crop to monitor basil responses to the drainage solution of 3.2 dS m−1. Growth, ascorbate content, nutrient concentration, and total amino acid concentration and profile were determined in both experiments. Various aspects of basil growth and biochemical performance collectively indicated the 5 dS m−1 salinity level as the upper limit/threshold of tolerance to stress. Higher salinity levels considerably suppressed fresh weight production, though the total concentration of amino acids showed a sevenfold increase under 15 dS m−1 and 4.5-fold under 5 and 10 dS m−1 compared to the control. The performance of basil in the cascade system was subject to a compromise between a reduction of fresh produce and an increase of total amino acids and ascorbate content. This outcome indicated that basil performed well under the conditions and the system employed in the present study, and might be a good candidate for use as a secondary crop in cascade-hydroponics systems.
A Machine Learning Model for Photorespiration Response to Multi-Factors
Authors: Zheng Kunpeng , Bo Yu , Bao Yanda , Zhu Xiaolei , Wang Jian , Wang Yu
Published: July 2021

Photorespiration results in a large amount of leaf photosynthesis consumption. However, there are few studies on the response of photorespiration to multi-factors. In this study, a machine learning model for the photorespiration rate of cucumber leaves’ response to multi-factors was established. It provides a theoretical basis for studies related to photorespiration. Machine learning models of different methods were designed and compared. The photorespiration rate was expressed as the difference between the photosynthetic rate at 2% O2 and 21% O2 concentrations. The results show that the XGBoost models had the best fit performance with an explained variance score of 0.970 for both photosynthetic rate datasets measured using air and 2% O2, with mean absolute errors of 0.327 and 0.181, root mean square errors of 1.607 and 1.469, respectively, and coefficients of determination of 0.970 for both. In addition, this study indicates the importance of the features of temperature, humidity and the physiological status of the leaves for predicted results of photorespiration. The model established in this study performed well, with high accuracy and generalization ability. As a preferable exploration of the research on photorespiration rate simulation, it has theoretical significance and application prospects.
The Relationship between the Urinary Cadmium Concentration and Cause-Specific Mortality in Subjects without Severe Renal Damage: A 35-Year Follow-Up Study in a Cadmium-Polluted Area of Japan
Authors: Sakurai Masaru , Suwazono Yasushi , Nishijo Muneko , Nogawa Kazuhiro , Watanabe Yuuka , Yoneda Kazuka , Ishizaki Masao , Morikawa Yuko , Kido Teruhiko , Nakagawa Hideaki
Published: July 2021

We evaluated the association between urinary cadmium concentration (uCd, μg/g Cr) and risk of cause-specific mortality according to urinary β2-microglobulin (MG) concentration. Participants were 1383 male and 1700 female inhabitants of the Cd-polluted Kakehashi River basin. The uCd and β2-MG were evaluated in a survey in 1981–1982, where those participants were followed-up over 35 years later. Among the participants with a urinary β2-MG < 1000, the hazard ratios (HRs) (95% confidence interval) for mortality were significantly higher in those with a uCd of ≥10.0 compared with <5.0 for cardiovascular disease [HR 1.92 (1.08–3.40) for men, 1.71 (1.07–2.71) for women], pneumonia or influenza [2.10 (1.10–4.00) for men, 2.22 (1.17–4.19) for women], and digestive diseases [for men; 3.81 (1.49–9.74)]. The uCd was significantly associated with mortality from heart failure in women and digestive diseases in men, after adjustment for other causes of death using the Fine and Gray competing risk regression model. For participants with a urinary β2-MG of ≥1000, no significant association was observed between uCd and any major cause of death. In the absence of kidney damage, Cd may increase the risk of death from cardiovascular disease, pneumonia, and digestive diseases.
Bagging Machine Learning Algorithms: A Generic Computing Framework Based on Machine-Learning Methods for Regional Rainfall Forecasting in Upstate New York
Authors: Yu Ning , Haskins Timothy
Published: July 2021

Regional rainfall forecasting is an important issue in hydrology and meteorology. Machine learning algorithms especially deep learning methods have emerged as a part of prediction tools for regional rainfall forecasting. This paper aims to design and implement a generic computing framework that can assemble a variety of machine learning algorithms as computational engines for regional rainfall forecasting in Upstate New York. The algorithms that have been bagged in the computing framework include the classical algorithms and the state-of-the-art deep learning algorithms, such as K-Nearest Neighbors, Support Vector Machine, Deep Neural Network, Wide Neural Network, Deep and Wide Neural Network, Reservoir Computing, and Long Short Term Memory methods. Through the experimental results and the performance comparisons of these various engines, we have observed that the SVM- and KNN-based method are outstanding models over other models in classification while DWNN- and KNN-based methods outstrip other models in regression, particularly those prevailing deep-learning-based methods, for handling uncertain and complex climatic data for precipitation forecasting. Meanwhile, the normalization methods such as Z-score and Minmax are also integrated into the generic computing framework for the investigation and evaluation of their impacts on machine learning models.
A Preliminary Assessment of Amblyseius andersoni (Chant) as a Potential Biocontrol Agent against Phytophagous Mites Occurring on Coniferous Plants
Authors: Puchalska Ewa , Zagrodzki Stanisław Kamil , Kozak Marcin , Rector Brian G. , Mauer Anna
Published: July 2021

Development, survival and reproduction of Ambyseius andersoni (Chant), a predatory mite widely distributed in Europe, were assessed on different food items. These included two key pests of ornamental coniferous plants, i.e., Oligonychus ununguis (Jacobi) and Pentamerismus taxi (Haller) and pollen of Pinus sylvestris L. The rationale behind these experiments was to provide a preliminary assessment of the potential of A. andersoni as a biocontrol agent of the above phytophagous arthropods and evaluate pine pollen as an alternative food source for the predator. Under laboratory conditions (23 ± 0.5 °C, 70 ± 10% RH and 16L:8D) A. andersoni was able to feed, develop and reproduce on all tested diets. The shortest development time (egg to female) was obtained when the predator fed on P. taxi (mean = 5.12 d) and the longest was on pine pollen (mean = 6.55 d). The rm value was significantly higher on both tested prey (0.166 on P. taxi and 0.160 on O. ununguis) than on pollen (0.139). Thus, we do not recommend pine pollen for mass rearing of A. andersoni; however, we conclude that pollen may provide sufficient sustenance for the predator population under field conditions when prey are absent. The potential of A. andersoni as a biocontrol agent of O. ununguis and P. taxi is discussed.