bluuebunny/crossref_metadata_2025 huggingface dataset:
Prospective Surveillance of Healthcare-Associated Infections in Residents in Four Long-Term Care Facilities in Graz, Austria
Authors: König Elisabeth , Medwed Mara , Pux Christian , Uhlmann Michael , Schippinger Walter , Krause Robert , Zollner-Schwetz Ines
Published: May 2021

Healthcare-associated infections (HCAI) are a common cause for residents’ mortality and morbidity associated with a significant socio-economic burden. Data on HCAIs in Austrian long-term care facilities are scare. Therefore, we evaluated the incidence rate of HCAIs per 1000 resident days in four LTC facilities in Graz, Austria, characterized the spectrum of HCAIs and the use of antimicrobial substances. We conducted a prospective surveillance study from 1 January to 31 December 2018 in four LTCFs of the Geriatric Health Centre of the City of Graz (total of 388 beds). Nursing staff collected data on HCAIs once a week using an electronic reporting system. During the 12-month surveillance period, 252 infections of 165 residents were recorded. The overall incidence rate of HCAIs was 2.1 per 1000 resident days. Urinary tract infections were the most commonly recorded HCAIs (49%, 124/252, 1.03 per 1000 resident days), followed by skin and soft tissue infections and respiratory tract infections. Beta-lactams (ATC class J01C) were prescribed most frequently (63/212), followed by fluoroquinolones (J01M; 54/212). In conclusion, the overall incidence rate for HCAIs was relatively low at 2.1 per 1000 resident days. Our real-life data can serve as a basis for future antimicrobial stewardship and infection prevention interventions.
Excessively Enlarged Mitochondria in the Kidneys of Diabetic Nephropathy
Authors: Kim Kiyoung , Lee Eun-Young
Published: May 2021

Diabetic nephropathy (DN) is the most serious complication of diabetes and a leading cause of kidney failure and mortality in patients with diabetes. However, the exact pathogenic mechanisms involved are poorly understood. Impaired mitochondrial function and accumulation of damaged mitochondria due to increased imbalance in mitochondrial dynamics are known to be involved in the development and progression of DN. Accumulating evidence suggests that aberrant mitochondrial fission is involved in the progression of DN. Conversely, studies linking excessively enlarged mitochondria to DN pathogenesis are emerging. In this review, we summarize the current concepts of imbalanced mitochondrial dynamics and their molecular aspects in various experimental models of DN. We discuss the recent evidence of enlarged mitochondria in the kidneys of DN and examine the possibility of a therapeutic application targeting mitochondrial dynamics in DN.
Vulnerability in Deep Transfer Learning Models to Adversarial Fast Gradient Sign Attack for COVID-19 Prediction from Chest Radiography Images
Authors: Pal Biprodip , Gupta Debashis , Rashed-Al-Mahfuz Md. , Alyami Salem A. , Moni Mohammad Ali
Published: May 2021

The COVID-19 pandemic requires the rapid isolation of infected patients. Thus, high-sensitivity radiology images could be a key technique to diagnose patients besides the polymerase chain reaction approach. Deep learning algorithms are proposed in several studies to detect COVID-19 symptoms due to the success in chest radiography image classification, cost efficiency, lack of expert radiologists, and the need for faster processing in the pandemic area. Most of the promising algorithms proposed in different studies are based on pre-trained deep learning models. Such open-source models and lack of variation in the radiology image-capturing environment make the diagnosis system vulnerable to adversarial attacks such as fast gradient sign method (FGSM) attack. This study therefore explored the potential vulnerability of pre-trained convolutional neural network algorithms to the FGSM attack in terms of two frequently used models, VGG16 and Inception-v3. Firstly, we developed two transfer learning models for X-ray and CT image-based COVID-19 classification and analyzed the performance extensively in terms of accuracy, precision, recall, and AUC. Secondly, our study illustrates that misclassification can occur with a very minor perturbation magnitude, such as 0.009 and 0.003 for the FGSM attack in these models for X-ray and CT images, respectively, without any effect on the visual perceptibility of the perturbation. In addition, we demonstrated that successful FGSM attack can decrease the classification performance to 16.67% and 55.56% for X-ray images, as well as 36% and 40% in the case of CT images for VGG16 and Inception-v3, respectively, without any human-recognizable perturbation effects in the adversarial images. Finally, we analyzed that correct class probability of any test image which is supposed to be 1, can drop for both considered models and with increased perturbation; it can drop to 0.24 and 0.17 for the VGG16 model in cases of X-ray and CT images, respectively. Thus, despite the need for data sharing and automated diagnosis, practical deployment of such program requires more robustness.
SVM Performance for Predicting the Effect of Horizontal Screen Diameters on the Hydraulic Parameters of a Vertical Drop
Authors: Daneshfaraz Rasoul , Aminvash Ehsan , Ghaderi Amir , Abraham John , Bagherzadeh Mohammad
Published: May 2021

The present study investigated the application of support vector machine algorithms for predicting hydraulic parameters of a vertical drop equipped with horizontal screens. The study incorporated varying sizes of a rectangular channel. Horizontal screens, in addition to being able to dissipate the destructive energy of the flow, cause turbulence. The turbulence in turn supplies oxygen to the system through the promotion of air–water mixing. To achieve the objectives of the present study, 164 experiments were analyzed under the same experimental conditions using a support vector machine. The approach utilized dimensionless terms that included scenario 1: the relative energy consumption and scenario 2: the relative pool depth. The performance of the models was evaluated with statistical criteria (RMSE, R2 and KGE) and the best model was introduced for each of the parameters. RMSE is the root mean square error, R2 is the correlation coefficient and KGE is the Kling–Gupta criterion. The results of the support vector machine showed that for the first scenario, the third combination with R2 = 0.991, RMSE = 0.00565 and KGE = 0.998 for the training mode and R2 = 0.991, RMSE = 0.00489 and KGE = 0.991 for the testing mode were optimal. For the second scenario, the third combination with R2 = 0.988, RMSE = 0.0395 and KGE = 0.998 for the training mode and R2 = 0.988, RMSE = 0.0389 and KGE = 0.993 for the testing mode were selected. Finally, a sensitivity analysis was performed that showed that the yc/H and D/H parameters are the most effective parameters for predicting relative energy dissipation and relative pool depth, respectively.
Atmospheric PM2.5 Prediction Based on Multiple Model Adaptive Unscented Kalman Filter
Authors: Li Jihan , Li Xiaoli , Wang Kang , Cui Guimei
Published: May 2021

The PM2.5 concentration model is the key to predict PM2.5 concentration. During the prediction of atmospheric PM2.5 concentration based on prediction model, the prediction model of PM2.5 concentration cannot be usually accurately described. For the PM2.5 concentration model in the same period, the dynamic characteristics of the model will change under the influence of many factors. Similarly, for different time periods, the corresponding models of PM2.5 concentration may be different, and the single model cannot play the corresponding ability to predict PM2.5 concentration. The single model leads to the decline of prediction accuracy. To improve the accuracy of PM2.5 concentration prediction in this solution, a multiple model adaptive unscented Kalman filter (MMAUKF) method is proposed in this paper. Firstly, the PM2.5 concentration data in three time periods of the day are taken as the research object, the nonlinear state space model frame of a support vector regression (SVR) method is established. Secondly, the frame of the SVR model in three time periods is combined with an adaptive unscented Kalman filter (AUKF) to predict PM2.5 concentration in the next hour, respectively. Then, the predicted value of three time periods is fused into the final predicted PM2.5 concentration by Bayesian weighting method. Finally, the proposed method is compared with the single support vector regression-adaptive unscented Kalman filter (SVR-AUKF), autoregressive model-Kalman (AR-Kalman), autoregressive model (AR) and back propagation neural network (BP). The prediction results show that the accuracy of PM2.5 concentration prediction is improved in whole time period.
Surgical Treatment of Sialolithiasis Leads to Improvement in the Complete Blood Count
Authors: Avishai Gal , Rabinovich Idan , Gilat Hanna , Chaushu Gavriel , Chaushu Liat
Published: May 2021

Sialolithiasis is a chronic disease in which a sialolith (salivary stone) causes recurrent inflammation of the affected salivary gland. Anemia of inflammation is a well-described pathology in which a chronic inflammatory disease leads to a reduction in the red blood cell count, hemoglobin and hematocrit values. In this retrospective cohort study, we aim to find whether removal of the sialolith and alleviation of the inflammation affect the complete blood count results. We examined data regarding forty-nine patients who underwent surgery for the removal of a submandibular gland sialolith using the duct-stretching technique. Complete blood counts two years before and after the surgical procedure were collected. The average pre-procedure and post-procedure values were calculated for each patient to establish the average blood profile. The pre- and post-procedure values were compared to evaluate the effect of the surgical treatment on the blood profile. We found that the average blood count values for patients with sialolithiasis were towards the lower end of the normal range. Post-surgery, a significant increase in hematocrit, hemoglobin and red blood cell count was observed, which was more pronounced in the older age group and in patients with co-morbidities. We conclude that sialolith removal surgery is associated with significant improvement in the complete blood count values, especially in the elderly and in patients and with co-morbidities. The speculated pathogenesis is relative anemia of inflammation.
Anti-Tumor Functions of Prelatent Antithrombin on Glioblastoma Multiforme Cells
Authors: Peñas-Martínez Julia , Luengo-Gil Ginés , Espín Salvador , Bohdan Nataliya , Ortega-Sabater Carmen , Ródenas Maria Carmen , Zaragoza-Huesca David , López-Andreo María José , Plasencia Carme , Vicente Vicente , Carmona-Bayonas Alberto , Martínez-Martínez Irene
Published: May 2021

Antithrombin, the main physiological inhibitor of the coagulation cascade, exerts anti-tumor effects on glioblastoma multiforme cells. Antithrombin has different conformations: native, heparin-activated, prelatent, latent, and cleaved. The prelatent form has an intermediate affinity between latent and native antithrombin, although it is the most antiangiogenic form. Herein, we investigate the effect of this conformation on the tumorigenic processes of glioblastoma multiforme cells. Antithrombin forms were purified by chromatography. Chromogenic/fluorogenic assays were carried out to evaluate enteropeptidase and hepsin inhibition, two serine proteases involved in these processes. Wound healing, Matrigel invasion and BrdU incorporation assays were performed to study migration, invasion and proliferation. E-cadherin, Vimentin, VEGFA, pAKT, STAT3, pSTAT3, and pERK1/2 expression was assessed by Western blot and/or qRT-PCR. Prelatent antithrombin inhibited both enteropeptidase and hepsin, although it was less efficient than the native conformation. Exposure to prelatent antithrombin significantly reduced migration and invasion but not proliferation of U-87 MG, being the conformation most efficient on migration. Prelatent antithrombin down-regulated VEGFA, pSTAT3, and pERK1/2 expression in U-87 MG cells. Our work elucidates that prelatent antithrombin has surprisingly versatile anti-tumor properties in U-87 MG glioblastoma multiforme cells. This associates with resistance pathway activation, the decreased expression of tumorigenic proteins, and increased angiogenesis, postulating the existence of a new, formerly unknown receptor with potential therapeutic implications.
The Role of Senescent Cells in Acquired Drug Resistance and Secondary Cancer in BRAFi-Treated Melanoma
Authors: Thompson Elizabeth L. , Hu Jiayi J. , Niedernhofer Laura J.
Published: May 2021

BRAF is the most common gene mutated in malignant melanoma, and predominately it is a missense mutation of codon 600 in the kinase domain. This oncogenic BRAF missense mutation results in constitutive activation of the mitogen-activate protein kinase (MAPK) pro-survival pathway. Several BRAF inhibitors (BRAFi) have been developed to specifically inhibit BRAFV600 mutations that improve melanoma survival, but resistance and secondary cancer often occur. Causal mechanisms of BRAFi-induced secondary cancer and resistance have been identified through upregulation of MAPK and alternate pro-survival pathways. In addition, overriding of cellular senescence is observed throughout the progression of disease from benign nevi to malignant melanoma. In this review, we discuss melanoma BRAF mutations, the genetic mechanism of BRAFi resistance, and the evidence supporting the role of senescent cells in melanoma disease progression, drug resistance and secondary cancer. We further highlight the potential benefit of targeting senescent cells with senotherapeutics as adjuvant therapy in combating melanoma.
Identifying Risk Factors and Patterns for Early Recurrence of Pancreatic Neuroendocrine Tumors: A Multi-Institutional Study
Authors: Heidsma Charlotte M. , Tsilimigras Diamantis I. , Rocha Flavio , Abbott Daniel E. , Fields Ryan , Poultsides George A. , Cho Clifford S. , Lopez-Aguiar Alexandra G. , Kanji Zaheer , Fisher Alexander V. , Krasnick Bradley A. , Idrees Kamran , Makris Eleftherios , Beems Megan , van Eijck Casper H. J. , Nieveen van Dijkum Elisabeth J. M. , Maithel Shishir K. , Pawlik Timothy M.
Published: May 2021

Background: Identifying patients at risk for early recurrence (ER) following resection for pancreatic neuroendocrine tumors (pNETs) might help to tailor adjuvant therapies and surveillance intensity in the post-operative setting. Methods: Patients undergoing surgical resection for pNETs between 1998–2018 were identified using a multi-institutional database. Using a minimum p-value approach, optimal cut-off value of recurrence-free survival (RFS) was determined based on the difference in post-recurrence survival (PRS). Risk factors for early recurrence were identified. Results: Among 807 patients who underwent curative-intent resection for pNETs, the optimal length of RFS to define ER was identified at 18 months (lowest p-value of 0.019). Median RFS was 11.0 months (95% 8.5–12.60) among ER patients (n = 49) versus 41.0 months (95% CI: 35.0–45.9) among non-ER patients (n = 77). Median PRS was worse among ER patients compared with non-ER patients (42.6 months vs. 81.5 months, p = 0.04). On multivariable analysis, tumor size (OR: 1.20, 95% CI: 1.05–1.37, p = 0.007) and positive lymph nodes (OR: 4.69, 95% CI: 1.41–15.58, p = 0.01) were independently associated with ER. Conclusion: An evidence-based cut-off value for ER after surgery for pNET was defined at 18 months. These data emphasized the importance of close follow-up in the first two years after surgery.
The Effect of Diffuse Liver Diseases on the Occurrence of Liver Metastases in Cancer Patients: A Systematic Review and Meta-Analysis
Authors: Monelli Filippo , Besutti Giulia , Djuric Olivera , Bonvicini Laura , Farì Roberto , Bonfatti Stefano , Ligabue Guido , Bassi Maria Chiara , Damato Angela , Bonelli Candida , Pinto Carmine , Pattacini Pierpaolo , Giorgi Rossi Paolo
Published: May 2021

This systematic review with meta-analysis aimed to assess the effect of diffuse liver diseases (DLD) on the risk of synchronous (S-) or metachronous (M-) liver metastases (LMs) in patients with solid neoplasms. Relevant databases were searched for systematic reviews and cross-sectional or cohort studies published since 1990 comparing the risk of LMs in patients with and without DLD (steatosis, viral hepatitis, cirrhosis, fibrosis) in non-liver solid cancer patients. Outcomes were prevalence of S-LMs, cumulative risk of M-LMs and LM-free survival. Risk of bias (ROB) was assessed using the Newcastle-Ottawa Scale. We report the pooled relative risks (RR) for S-LMs and hazard ratios (HR) for M-LMs. Subgroup analyses included DLD, primary site and continent. Nineteen studies were included (n = 37,591 patients), the majority on colorectal cancer. ROB appraisal results were mixed. Patients with DLD had a lower risk of S-LMs (RR 0.50, 95% CI 0.34–0.76), with a higher effect for cirrhosis and a slightly higher risk of M-LMs (HR 1.11 95% CI, 1.03–1.19), despite a lower risk of M-LMs in patients with vs without viral hepatitis (HR 0.57, 95% CI 0.40–0.82). There may have been a publication bias in favor of studies reporting a lower risk for patients with DLD. DLD are protective against S-LMs and slightly protective against M-LMs for viral hepatitis only.
Skeletal Muscle Volume Is an Independent Predictor of Survival after Sorafenib Treatment Failure for Hepatocellular Carcinoma
Authors: Saeki Issei , Yamasaki Takahiro , Yamauchi Yurika , Takami Taro , Kawaoka Tomokazu , Uchikawa Shinsuke , Hiramatsu Akira , Aikata Hiroshi , Kawano Reo , Kobayashi Kazufumi , Kondo Takayuki , Ogasawara Sadahisa , Chiba Tetsuhiro , Chayama Kazuaki , Kato Naoya , Sakaida Isao
Published: May 2021

Few studies exist on the relationship between post-progression survival (PPS) and skeletal muscle volume in hepatocellular carcinoma (HCC) patients receiving sorafenib. This study aimed to analyze the effects of muscle volume on clinical outcomes. We retrospectively enrolled 356 HCC patients. Various clinical parameters, including skeletal muscle index, were analyzed as predictors of overall survival (OS), progression-free survival (PFS), and PPS. Patients with high muscle volume showed longer survival or PPS than those with low muscle volume (median survival time: 12.8 vs. 9.5 months, p = 0.005; median PPS: 8.2 vs. 6.3 months, p = 0.015); however, no differences in PFS were found. Multivariate analysis indicated that muscle volume was an independent predictor of PPS and OS. Skeletal muscle volume was a PPS predictor in HCC patients receiving sorafenib. Therefore, survival can be prolonged by the upregulation of skeletal muscle volume, especially in HCC patients with skeletal muscle depletion.
Claudin-Low Breast Cancer Inflammatory Signatures Support Polarization of M1-Like Macrophages with Protumoral Activity
Authors: Suárez-Arriaga Mayra Cecilia , Méndez-Tenorio Alfonso , Pérez-Koldenkova Vadim , Fuentes-Pananá Ezequiel M.
Published: May 2021

We previously reported that triple-negative breast cancer (BRCA) cells overexpress the cytokines GM-CSF, G-CSF, MCP-1, and RANTES, and when monocytes were 3-D co-cultured with them, M1-like macrophages were generated with the ability to induce aggressive features in luminal BRCA cell lines. These include upregulation of mesenchymal and stemness markers and invasion. In this study, we stimulated peripheral blood monocytes with the four cytokines and confirmed their capacity to generate protumoral M1-like macrophages. Using the METABRIC BRCA database, we observed that GM-CSF, MCP-1, and RANTES are associated with triple-negative BRCA and reduced overall survival, particularly in patients under 55 years of age. We propose an extended M1-like macrophage proinflammatory signature connected with these three cytokines. We found that the extended M1-like macrophage signature coexists with monocyte/macrophage, Th1 immune response, and immunosuppressive signatures, and all are enriched in claudin-low BRCA samples, and correlate with reduced patient overall survival. Furthermore, we observed that all these signatures are also present in mesenchymal carcinomas of the colon (COAD) and bladder (BLCA). The claudin-low tumor subtype has an adverse clinical outcome and remains poorly understood. This study places M1 macrophages as potential protumoral drivers in already established cancers, and as potential contributors to claudin-low aggressiveness and poor prognosis.
IGF2 Mediates Resistance to Isoform-Selective-Inhibitors of the PI3K in HPV Positive Head and Neck Cancer
Authors: Badarni Mai , Prasad Manu , Golden Artemiy , Bhattacharya Baisali , Levin Liron , Yegodayev Ksenia M. , Dimitstein Orr , Joshua Ben-Zion , Cohen Limor , Khrameeva Ekaterina , Kong Dexin , Porgador Angel , Braiman Alex , Grandis Jennifer R. , Rotblat Barak , Elkabets Moshe
Published: May 2021

Over 50% of human papilloma positive head-and-neck cancer (HNCHPV+) patients harbor genomic-alterations in PIK3CA, leading to hyperactivation of the phosphatidylinositol-4, 5-bisphosphate 3-kinase (PI3K) pathway. Nevertheless, despite PI3K pathway activation in HNCHPV+ tumors, the anti-tumor activities of PI3K pathway inhibitors are moderate, mostly due to the emergence of resistance. Thus, for potent and long-term tumor management, drugs blocking resistance mechanisms should be combined with PI3K inhibitors. Here, we delineate the molecular mechanisms of the acquisition of resistance to two isoform-selective inhibitors of PI3K (isiPI3K), alpelisib (BYL719) and taselisib (GDC0032), in HNCHPV+ cell lines. By comparing the transcriptional landscape of isiPI3K-sensitive tumor cells with that of their corresponding isiPI3K-acquired-resistant tumor cells, we found upregulation of insulin growth factor 2 (IGF2) in the resistant cells. Mechanistically, we show that upon isiPI3K treatment, isiPI3K-sensitive tumor cells upregulate the expression of IGF2 to induce cell proliferation via the activation of the IGF1 receptor (IGF1R). Stimulating tumor cells with recombinant IGF2 limited isiPI3K efficacy and released treated cells from S phase arrest. Knocking-down IGF2 with siRNA, or blocking IGF1R with AEW541, resulted in superior anti-tumor activity of isiPI3K in vitro and ex vivo. In vivo, the combination of isiPI3K and IGF1R inhibitor induced stable disease in mice bearing either tumors generated by the HNCHPV+ UM-SCC47 cell line or HPV+ patient-derived xenografts. These findings indicate that IGF2 and the IGF2/IGF1R pathway may constitute new targets for combination therapies to enhance the efficacy of PI3K inhibitors for the treatment of HNCHPV+.
Post-Transcriptional Regulation of Viral RNA through Epitranscriptional Modification
Authors: Courtney David G.
Published: May 2021

The field of mRNA modifications has been steadily growing in recent years as technologies have improved and the importance of these residues became clear. However, a subfield has also arisen, specifically focused on how these modifications affect viral RNA, with the possibility that viruses can also be used as a model to best determine the role that these modifications play on cellular mRNAs. First, virologists focused on the most abundant internal mRNA modification, m6A, mapping this modification and elucidating its effects on the RNA of a wide range of RNA and DNA viruses. Next, less common RNA modifications including m5C, Nm and ac4C were investigated and also found to be present on viral RNA. It now appears that viral RNA is littered with a multitude of RNA modifications. In biological systems that are under constant evolutionary pressure to out compete both the host as well as newly arising viral mutants, it poses an interesting question about what evolutionary benefit these modifications provide as it seems evident, at least to this author, that these modifications have been selected for. In this review, I discuss how RNA modifications are identified on viral RNA and the roles that have now been uncovered for these modifications in regard to viral replication. Finally, I propose some interesting avenues of research that may shed further light on the exact role that these modifications play in viral replication.
The Discovery of Naringenin as Endolysosomal Two-Pore Channel Inhibitor and Its Emerging Role in SARS-CoV-2 Infection
Authors: D’Amore Antonella , Gradogna Antonella , Palombi Fioretta , Minicozzi Velia , Ceccarelli Matteo , Carpaneto Armando , Filippini Antonio
Published: May 2021

The flavonoid naringenin (Nar), present in citrus fruits and tomatoes, has been identified as a blocker of an emerging class of human intracellular channels, namely the two-pore channel (TPC) family, whose role has been established in several diseases. Indeed, Nar was shown to be effective against neoangiogenesis, a process essential for solid tumor progression, by specifically impairing TPC activity. The goal of the present review is to illustrate the rationale that links TPC channels to the mechanism of coronavirus infection, and how their inhibition by Nar could be an efficient pharmacological strategy to fight the current pandemic plague COVID-19.
Voltammetric Study of the Total Activity of Antioxidants in the Blood Serum of Patients with Neurological Diseases
Authors: Voronova Olesya A. , Korotkova Elena I. , Plotnikov Evgenii V. , Geraskevich Alina V. , Kataeva Nadegda G. , Dorozhko Elena V. , Gamayurova Irina S. , Lipskikh Olga I. , Derina Ksenia V.
Published: May 2021

One of the main directions in the development of modern electroanalytical chemistry is the development of new effective methods for research and analysis of biological objects, particularly, human blood serum. The creation of new electrochemical sensors is a promising approach, which has determined several main directions in applied voltammetry in the field of chemical analytical control. In this work, the dynamics and parameters of total antioxidant activity of human serum blood of patients with chronic cerebral ischemia, during treatment with pharmaceutical drugs Mexidol, Cavinton Comfort, and Cytoflavin was tested by cathode voltammetry with a model process of oxygen electroreduction, using a new electrochemical sensor.
Beyond Planning Tools: Experiential Learning in Climate Adaptation Planning and Practices
Authors: Schmitt Kristen M. , Ontl Todd A. , Handler Stephen D. , Janowiak Maria K. , Brandt Leslie A. , Butler-Leopold Patricia R. , Shannon P. Danielle , Peterson Courtney L. , Swanston Christopher W.
Published: May 2021

In the past decade, several dedicated tools have been developed to help natural resources professionals integrate climate science into their planning and implementation; however, it is unclear how often these tools lead to on-the-ground climate adaptation. Here, we describe a training approach that we developed to help managers effectively plan to execute intentional, climate-informed actions. This training approach was developed through the Climate Change Response Framework (CCRF) and uses active and focused work time and peer-to-peer interaction to overcome observed barriers to using adaptation planning tools. We evaluate the effectiveness of this approach by examining participant evaluations and outlining the progress of natural resources projects that have participated in our trainings. We outline a case study that describes how this training approach can lead to place and context-based climate-informed action. Finally, we describe best practices based on our experience for engaging natural resources professionals and helping them increase their comfort with climate-informed planning.
Gestational Diabetes Mellitus per Different Diagnostic Criteria, Risk Factors, Obstetric Outcomes and Postpartum Glycemia: A Prospective Study in Ghana
Authors: Agbozo Faith , Abubakari Abdulai , Zotor Francis , Jahn Albrecht
Published: May 2021

The surge in gestational diabetes mellitus (GDM) globally requires a health system tailored approach towards prevention, detection and management. We estimated the prevalence of GDM using diverse recommended tests and diagnostic thresholds, and also assessed the risk factors and obstetric outcomes, including postpartum glycemia. Using a prospective cohort design, 446 singleton pregnant women without pre-existing diabetes did GDM tests in five hospitals in Ghana from 20–34 weeks using fasting plasma glucose (FPG), one-hour and 2-h oral glucose tolerance test (OGTT). Birth outcomes of 403 were assessed. GDM was diagnosed using six international diagnostic criteria. At 12 weeks postpartum, impaired fasting glucose (6.1–6.9 mmol/L) and diabetes (FPG ≥7.0 mmol/L) were measured for 100 women. Per FPG and 2-h OGTT cut-offs, GDM prevalence ranged between 8.3–23.8% and 4.4–14.3%, respectively. Risk factors included overweight (OR = 2.13, 95% CI: 1.13–4.03), previous miscarriage (OR = 4.01, 95% CI: 1.09–14.76) and high caloric intake (OR = 2.91, 95% CI: 1.05–8.07). Perineal tear (RR = 2.91, 95% CI: 1.08–5.57) and birth asphyxia (RR = 3.24, 95% CI: 1.01–10.45) were the associated perinatal outcomes. At 12 weeks postpartum, 15% had impaired fasting glucose, and 5% had diabetes. Tackling modifiable risk factors is crucial for prevention. Glycemic monitoring needs to be integral in postpartum and well-child reviews.
Chest X-ray Bone Suppression for Improving Classification of Tuberculosis-Consistent Findings
Authors: Rajaraman Sivaramakrishnan , Zamzmi Ghada , Folio Les , Alderson Philip , Antani Sameer
Published: May 2021

Chest X-rays (CXRs) are the most commonly performed diagnostic examination to detect cardiopulmonary abnormalities. However, the presence of bony structures such as ribs and clavicles can obscure subtle abnormalities, resulting in diagnostic errors. This study aims to build a deep learning (DL)-based bone suppression model that identifies and removes these occluding bony structures in frontal CXRs to assist in reducing errors in radiological interpretation, including DL workflows, related to detecting manifestations consistent with tuberculosis (TB). Several bone suppression models with various deep architectures are trained and optimized using the proposed combined loss function and their performances are evaluated in a cross-institutional test setting using several metrics such as mean absolute error (MAE), peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and multiscale structural similarity measure (MS–SSIM). The best-performing model (ResNet–BS) (PSNR = 34.0678; MS–SSIM = 0.9828) is used to suppress bones in the publicly available Shenzhen and Montgomery TB CXR collections. A VGG-16 model is pretrained on a large collection of publicly available CXRs. The CXR-pretrained model is then fine-tuned individually on the non-bone-suppressed and bone-suppressed CXRs of Shenzhen and Montgomery TB CXR collections to classify them as showing normal lungs or TB manifestations. The performances of these models are compared using several performance metrics such as accuracy, the area under the curve (AUC), sensitivity, specificity, precision, F-score, and Matthews correlation coefficient (MCC), analyzed for statistical significance, and their predictions are qualitatively interpreted through class-selective relevance maps (CRMs). It is observed that the models trained on bone-suppressed CXRs (Shenzhen: AUC = 0.9535 ± 0.0186; Montgomery: AUC = 0.9635 ± 0.0106) significantly outperformed (p < 0.05) the models trained on the non-bone-suppressed CXRs (Shenzhen: AUC = 0.8991 ± 0.0268; Montgomery: AUC = 0.8567 ± 0.0870).. Models trained on bone-suppressed CXRs improved detection of TB-consistent findings and resulted in compact clustering of the data points in the feature space signifying that bone suppression improved the model sensitivity toward TB classification.
Magnetic Resonance Spectroscopy of Hepatic Fat from Fundamental to Clinical Applications
Authors: Pasanta Duanghathai , Htun Khin Thandar , Pan Jie , Tungjai Montree , Kaewjaeng Siriprapa , Kim Hongjoo , Kaewkhao Jakrapong , Kothan Suchart
Published: May 2021

The number of individuals suffering from fatty liver is increasing worldwide, leading to interest in the noninvasive study of liver fat. Magnetic resonance spectroscopy (MRS) is a powerful tool that allows direct quantification of metabolites in tissue or areas of interest. MRS has been applied in both research and clinical studies to assess liver fat noninvasively in vivo. MRS has also demonstrated excellent performance in liver fat assessment with high sensitivity and specificity compared to biopsy and other imaging modalities. Because of these qualities, MRS has been generally accepted as the reference standard for the noninvasive measurement of liver steatosis. MRS is an evolving technique with high potential as a diagnostic tool in the clinical setting. This review aims to provide a brief overview of the MRS principle for liver fat assessment and its application, and to summarize the current state of MRS study in comparison to other techniques.
Can Quantum Correlations Lead to Violation of the Second Law of Thermodynamics?
Authors: Melkikh Alexey V.
Published: May 2021

Quantum entanglement can cause the efficiency of a heat engine to be greater than the efficiency of the Carnot cycle. However, this does not mean a violation of the second law of thermodynamics, since there is no local equilibrium for pure quantum states, and, in the absence of local equilibrium, thermodynamics cannot be formulated correctly. Von Neumann entropy is not a thermodynamic quantity, although it can characterize the ordering of a system. In the case of the entanglement of the particles of the system with the environment, the concept of an isolated system should be refined. In any case, quantum correlations cannot lead to a violation of the second law of thermodynamics in any of its formulations. This article is devoted to a technical discussion of the expected results on the role of quantum entanglement in thermodynamics.
An Indoor Localization System Using Residual Learning with Channel State Information
Authors: Xu Chendong , Wang Weigang , Zhang Yunwei , Qin Jie , Yu Shujuan , Zhang Yun
Published: May 2021

With the increasing demand of location-based services, neural network (NN)-based intelligent indoor localization has attracted great interest due to its high localization accuracy. However, deep NNs are usually affected by degradation and gradient vanishing. To fill this gap, we propose a novel indoor localization system, including denoising NN and residual network (ResNet), to predict the location of moving object by the channel state information (CSI). In the ResNet, to prevent overfitting, we replace all the residual blocks by the stochastic residual blocks. Specially, we explore the long-range stochastic shortcut connection (LRSSC) to solve the degradation problem and gradient vanishing. To obtain a large receptive field without losing information, we leverage the dilated convolution at the rear of the ResNet. Experimental results are presented to confirm that our system outperforms state-of-the-art methods in a representative indoor environment.
Foreign Language Learning Gamification Using Virtual Reality—A Systematic Review of Empirical Research
Authors: Pinto Rafael Darque , Peixoto Bruno , Melo Miguel , Cabral Luciana , Bessa Maximino
Published: May 2021

Virtual reality has shown to have great potential as an educational tool when it comes to new learning methods. With the growth and dissemination of this technology, there is a massive opportunity for teachers to add this technology to their methods of teaching a second/foreign language, since students keep showing a growing interest in new technologies. This systematic review of empirical research aims at understanding whether the use of gaming strategies in virtual reality is beneficial for the learning of a second/foreign language or not. Results show that more than half of the articles proved that virtual reality technologies with gaming strategies can be used to learn a foreign language. It was also found that “learning” was the most evaluated dependent variable among the chosen records, augmented reality was the leading technology used, primary education and lower secondary was the most researched school stages, and the most used language to evaluate the use of gamified technology was by far the English language. Given the lack of directed investigation, it is recommended to use these technologies to support second language learning and not entirely replace traditional approaches. A research agenda is also proposed by the authors.
Performance Improvement of ZnSnO Thin-Film Transistors with Low-Temperature Self-Combustion Reaction
Authors: Han Ye-Ji , Lee Se Hyeong , Bak So-Young , Han Tae-Hee , Kim Sangwoo , Yi Moonsuk
Published: May 2021

Conventional sol-gel solutions have received significant attention in thin-film transistor (TFT) manufacturing because of their advantages such as simple processing, large-scale applicability, and low cost. However, conventional sol-gel processed zinc tin oxide (ZTO) TFTs have a thermal limitation in that they require high annealing temperatures of more than 500 °C, which are incompatible with most flexible plastic substrates. In this study, to overcome the thermal limitation of conventional sol-gel processed ZTO TFTs, we demonstrated a ZTO TFT that was fabricated at low annealing temperatures of 350 °C using self-combustion. The optimized device exhibited satisfactory performance, with μsat of 4.72 cm2/V∙s, Vth of −1.28 V, SS of 0.86 V/decade, and ION/OFF of 1.70 × 106 at a low annealing temperature of 350 °C for one hour. To compare a conventional sol-gel processed ZTO TFT with the optimized device, thermogravimetric and differential thermal analyses (TG-DTA) and X-ray photoelectron spectroscopy (XPS) were implemented.
Temperature Measurement at Curved Surfaces Using 3D Printed Planar Resistance Temperature Detectors
Authors: Steckiewicz Adam , Konopka Kornelia , Choroszucho Agnieszka , Stankiewicz Jacek Maciej
Published: May 2021

In this article, novel 3D printed sensors for temperature measurement are presented. A planar structure of the resistive element is made, utilizing paths of a conductive filament embedded in an elastic base. Both electrically conductive and flexible filaments are used simultaneously during the 3D printing procedure, to form a ready–to–use measuring device. Due to the achieved flexibility, the detectors may be used on curved and irregular surfaces, with no concern for their possible damage. The geometry and properties of the proposed resistance detectors are discussed, along with a printing procedure. Numerical models of considered sensors are characterized, and the calculated current distributions as well as equivalent resistances of the different structures are compared. Then, a nonlinear influence of temperature on the resistance is experimentally determined for the exemplary planar sensors. Based on these results, using first–order and hybrid linear–exponential approximations, the analytical formulae are derived. Additionally, the device to measure an average temperature from several measuring surfaces is considered. Since geometry of the sensor can be designed utilizing presented approach and printed by applying fused deposition modeling, the functional device can be customized to individual needs.
Valuation of Energy Security for Natural Gas—European Example
Authors: Kosowski Piotr , Kosowska Katarzyna
Published: May 2021

Recently there has been an ongoing discussion about energy security. This has been caused by tensions affecting international relations, and the emergence of new geopolitical threats. As one of the main sources of primary energy, natural gas is an obvious subject of interest in this discussion. In Europe, the natural gas market is rapidly evolving, which has resulted in a lack of clarity regarding who is responsible for the security of the gas supply. It is not clear now how to measure the security of the gas supply in economic estimates and by whom that security should be financed. In this paper, the authors present an approach which can be used for valuation of energy security concerning the security of natural gas storage using stochastic modelling based on the mathematical model of the “Newsvendor problem”. The valuation is made from the point of view of countries and considers their individual attitudes to the risk of disruption of deliveries, which is a novel approach to the problem. The authors believe that the current level of storage capacities, as compared to the demand for natural gas, can show the attitude of each country to the risk and potential cost of stockout. In line with this belief, the target value in the model is not the optimal level of inventory, but the cost of stockout. The results show significant variations in the assessment of the risk. The future of natural gas as an important fuel and source of primary energy in Europe is not clear and unfavorable changes have been sped up by the COVID-19 pandemic. Gas (energy) companies in Europe are turning to decarbonization and green energy, and the pandemic has accelerated these changes. European energy companies used to see the use of natural gas as a transition fuel and a key component of their long-term decarbonization strategies, but now they are switching to multi-energy models through massive investments in renewables and hydrogen. Experts expect that gas will remain an important part of Europe’s energy supply, but it may be gradually replaced by hydrogen and renewables.
Magnetic Steel Slag Biochar for Ammonium Nitrogen Removal from Aqueous Solution
Authors: Kim Gyuhyeon , Kim Young , Kim Su , Cho Hyun , Park Jong
Published: May 2021

In this study, magnetic steel slag biochar (MSSB) was synthesized from low-cost steel slag waste to investigate the effectiveness of steel slag biochar composite for NH4-N removal and magnetic properties in aqueous solution. The maximum adsorption capacity of NH4-N by MSSB was 4.366 mg/g according to the Langmuir model. The magnetic properties of MSSB indicated paramagnetic behavior and a saturation magnetic moment of 2.30 emu/g at 2 Tesla. The NH4-N adsorption process was well characterized by the pseudo-second order kinetic model and Temkin isotherm model. This study demonstrated the potential of magnetic biochar synthesized from steel slag waste for NH4-N removal in aqueous solution.
Mineral Policy within the Framework of Limited Critical Resources and a Green Energy Transition
Authors: Nate Silviu , Bilan Yuriy , Kurylo Mariia , Lyashenko Olena , Napieralski Piotr , Kharlamova Ganna
Published: May 2021

The green energy transition is associated with the use of a wide range of metals and minerals that are exhaustible. Most of these minerals are limited in access due to small resource fields, their concentration in several locations and a broader scale of industry usage which is not limited exclusively to energy and environmental sectors. This article classifies 17 minerals that are critical in the green energy transition concerning the 10 main technologies. The following classification signs of metal resources were used: (1) the absolute amount of metals used in the current period for energy; (2) projected annual demand in 2050 from energy technologies as a percentage of the current rate; (3) the number of technologies where there is a need for an individual metal; (4) cumulative emissions of CO2, which are associated with metal production; (5) period of reserves availability; (6) the number of countries that produced more than 1% of global production; (7) countries with the maximum annual metal productivity. The ranking of metals according to these characteristics was carried out using two scenarios, and the index of the availability of each mineral was determined. The lowest availability index values (up to 0.15) were calculated for cobalt, graphite and lithium, which are key battery minerals for energy storage. Low indices (up to 0.20) were also obtained for iron, nickel and chromium. The calculation of the availability index for each mineral was enhanced with linear trend modelling and the fuzzy logic technique. There are two scenarios of demand–supply commodity systems with a pre-developed forecast up to 2050: basic independent parameter probability and balanced fuzzy sum. Both scenarios showed comparable results, but the second one highlighted supply chain importance. Generally, the lowest availability index values (up to 0.15) were calculated for cobalt, graphite and lithium, which are key battery minerals for energy storage. Low indices (up to 0.20) were also obtained for iron, nickel and chromium. The fuzzy logic model helped to reveal two scenarios up to 2050. The two scenarios presented in the current research expose a high level of uncertainty of the projected 2050 forecast.
Measuring the Energy Efficiency of Evaporative Systems through a New Index—EvaCOP
Authors: Santos Alexandre F. , Gaspar Pedro D. , Souza Heraldo J. L.
Published: May 2021

Evaporative systems are probably the oldest technology for thermal comfort. However, they are still an essential technology in the food industry, environments for thermal comfort, and even for cooling data centers. Standards have been improved to compare the energy efficiency of this type of equipment. Using AHRI concepts with temperature data from the 29 most populous cities in the world, an EvaCOP index was created from temperatures that are easier to simulate than current parameters. The index parameters were tested in a laboratory located in Curitiba (Brazil). EvaCOP values of 45.58 and 25.77 W/W were found in the calculation in two different simulated equipment and compared with the compression cycle systems that in the most efficient machines is around 6.29 W/W.
Long-Term Soil Fertility and Site Productivity in Stem-Only and Whole-Tree Harvested Stands in Boreal Forest of Quebec (Canada)
Authors: Ouimet Rock , Duchesne Louis , Tremblay Stéphane
Published: May 2021

Using residual biomass from forest harvesting to produce energy is viewed increasingly as a means to reduce fossil fuel consumption. However, the impact such practices on soil and future site productivity remains a major concern. We revisited 196 forest plots that were subject to either whole-tree (WTH) or stem-only (SOH) harvesting 30 years ago in the boreal forest in Quebec, Canada. Plots were stratified by four soil regions grouped by so-called ‘soil provinces’. Soil analyses indicated that after 30 years, the forest floor of WTH sites had smaller pools of N (−8%), exchangeable Ca (−6%) and exchangeable Mn (−21%) and a higher C/N ratio (+12%) than that of SOH sites. Mineral soil responses to the two harvesting intensities differed among soil provinces. In the two coarse-textured granitic soil provinces, organic matter, organic carbon, and nitrogen pools over the whole solum (0–60 cm soil depth) were at least 28% smaller after WTH than after SOH. Site productivity indicators followed differences between soils and were lower after WTH than after SOH in the two granitic soil provinces. The study shows that soil characteristics greatly influence a soil’s sensitivity to increased forest biomass harvesting in the long term.