bluuebunny/crossref_metadata_2025 huggingface dataset:
Successful Prevention of Antimicrobial Resistance in Animals—A Retrospective Country Case Study of Sweden
Authors: Wierup Martin , Wahlström Helene , Bengtsson Björn
Published: January 2021

The misuse and overuse of antibiotics have resulted in an alarmingly high prevalence of antimicrobial resistance (AMR) in human and animal bacteria. European monitoring programmes show that AMR occurrence in food animals is lower in Sweden than in most other EU Member States and that the use of antibiotics for animals is among the lowest in Europe. In this retrospective country case study, we analysed published documents to identify factors contributing to this favourable situation. A fundamental factor identified was early insight into and sustained awareness of the risks of AMR and the need for the prudent use of antibiotics. Early and continuous access to data on antibiotic use and AMR made it possible to focus activities on areas of concern. Another factor identified was the long-term control and eradication of infectious animal diseases, including coordinated activities against endemic diseases, which reduced the need to use antibiotics. Structures and strategies for that purpose established at the national level have since proven useful in counteracting AMR as an integral part of disease prevention and control, guided by a “prevention is better than cure” approach. A third factor identified was consensus among stakeholders on the need to address AMR and their cooperation in the design and implementation of measures.
Mesoporous Polydopamine Nanoparticles Attenuate Morphine Tolerance in Neuropathic Pain Rats by Inhibition of Oxidative Stress and Restoration of the Endogenous Antioxidant System
Authors: Kuthati Yaswanth , Busa Prabhakar , Tummala Srikrishna , Rao Vaikar Navakanth , Davuluri Venkata Naga Goutham , Ho Yen-Peng , Wong Chih-Shung
Published: January 2021

Oxidative stress resulting from reactive oxygen species (ROS) is known to play a key role in numerous neurological disorders, including neuropathic pain. Morphine is one of the commonly used opioids for pain management. However, long-term administration of morphine results in morphine antinociceptive tolerance (MAT) through elevation of ROS and suppression of natural antioxidant defense mechanisms. Recently, mesoporous polydopamine (MPDA) nanoparticles (NPS) have been known to possess strong antioxidant properties. We speculated that morphine delivery through an antioxidant nanocarrier might be a reasonable strategy to alleviate MAT. MPDAs showed a high drug loading efficiency of ∼50%, which was much higher than conventional NPS. Spectral and in vitro studies suggest a superior ROS scavenging ability of NPS. Results from a rat neuropathic pain model demonstrate that MPDA-loaded morphine (MPDA@Mor) is efficient in minimizing MAT with prolonged analgesic effect and suppression of pro-inflammatory cytokines. Additionally, serum levels of liver enzymes and levels of endogenous antioxidants were measured in the liver. Treatment with free morphine resulted in elevated levels of liver enzymes and significantly lowered the activities of endogenous antioxidant enzymes in comparison with the control and MPDA@Mor-treated group. Histopathological examination of the liver revealed that MPDA@Mor can significantly reduce the hepatotoxic effects of morphine. Taken together, our current work will provide an important insight into the development of safe and effective nano-antioxidant platforms for neuropathic pain management.
Characteristics of Extratropical Cyclones That Cause Tornadoes in Italy: A Preliminary Study
Authors: Tochimoto Eigo , Miglietta Mario Marcello , Bagaglini Leonardo , Ingrosso Roberto , Niino Hiroshi
Published: January 2021

Characteristics of extratropical cyclones that cause tornadoes in Italy are investigated. Tornadoes between 2007 and 2016 are analyzed, and statistical analysis of the associated cyclone structures and environments is performed using the JRA-55 reanalysis. Tornadoes are distributed sporadically around the cyclone location within a window of 10° × 10°. The difference in the cyclone tracks partially explains the seasonal variability in the distribution of tornadoes. The highest number of tornadoes occur south of the cyclone centers, mainly in the warm sector, while a few are observed along the cold front. Composite mesoscale parameters are examined to identify the environmental conditions associated with tornadoes in different seasons. Potential instability is favorable to tornado development in autumn. The highest convective available potential energy (CAPE) in this season is associated with relatively high-temperature and humidity at low-levels, mainly due to the strong evaporation over the warm Mediterranean Sea. Upper-level potential vorticity (PV) anomalies and the associated cold air reduce the static stability above the cyclone center, mainly in spring and winter. On average, the values of CAPE are lower than for US tornadoes and comparable with those occurring in Japan, while storm relative helicity (SREH) is comparable with US tornadoes and higher than Japanese tornadoes, indicating that the environmental conditions for Italian tornadoes have peculiar characteristics. Overall, the conditions emerging in this study are close to the high-shear, low-CAPE environments typical of cool-season tornadoes in the Southeastern US.
Loading a Paul Trap: Densities, Capacities, and Scaling in the Saturation Regime
Authors: Blümel Reinhold
Published: January 2021

Providing ideal conditions for the study of ion-neutral collisions, we investigate here the properties of the saturated, steady state of a three-dimensional Paul trap, loaded from a magneto-optic trap. In particular, we study three assumptions that are sometimes made under saturated, steady-state conditions: (i) The pseudopotential provides a good approximation for the number, Ns, of ions in the saturation regime, (ii) the maximum of Ns occurs at a loading rate of approximately 1 ion per rf cycle, and (iii) the ion density is approximately constant. We find that none of these assumptions are generally valid. However, based on detailed classical molecular dynamics simulations, and as a function of loading rate and trap control parameter, we show where to find convenient dynamical regimes for ion-neutral collision experiments, or how to rescale to the pseudo-potential predictions. We also investigate the fate of the electrons generated during the loading process and present a new heating mechanism, insertion heating, that in some regimes of trapping and loading may rival and even exceed the rf-heating power of the trap.
Immunohistochemical Markers in Endometrial Cancer
Authors: Mais Valerio , Peiretti Michele
Published: January 2021

In 2018, 382,069 new cases of uterine cancer were registered worldwide and 89,929 deaths from this cancer were reported [...]
Eighty Years of Targeting Androgen Receptor Activity in Prostate Cancer: The Fight Goes on
Authors: Estébanez-Perpiñá Eva , Bevan Charlotte L. , McEwan Iain J.
Published: January 2021

Prostate cancer (PCa) is the most common cancer in men in the West, other than skin cancer, accounting for over a quarter of cancer diagnoses in US men. In a seminal paper from 1941, Huggins and Hodges demonstrated that prostate tumours and metastatic disease were sensitive to the presence or absence of androgenic hormones. The first hormonal therapy for PCa was thus castration. In the subsequent eighty years, targeting the androgen signalling axis, where possible using drugs rather than surgery, has been a mainstay in the treatment of advanced and metastatic disease. Androgens signal via the androgen receptor, a ligand-activated transcription factor, which is the direct target of many such drugs. In this review we discuss the role of the androgen receptor in PCa and how the combination of structural information and functional screenings is continuing to be used for the discovery of new drug to switch off the receptor or modify its function in cancer cells.
The Value of Early Tumor Size Response to Chemotherapy in Pediatric Rhabdomyosarcoma
Authors: van Ewijk Roelof , Vaarwerk Bas , Breunis Willemijn B. , Schoot Reineke A. , ter Horst Simone A. J. , van Rijn Rick R. , van der Lee Johanna H. , Merks Johannes H. M.
Published: January 2021

Rhabdomyosarcoma is the most common soft tissue sarcoma in childhood. Results of clinical trials, with three-year event-free and overall survival as primary outcomes, often take 7 to 10 years. Identification of an early surrogate biomarker, predictive for survival, is therefore crucial. We conducted a systematic review to define the prognostic value of early tumor size response in children with IRSG group III rhabdomyosarcoma. The search included MEDLINE/EMBASE from inception to 18 November 2020. In total, six studies were included, describing 2010 patients, and assessed by the Quality in Prognosis Studies (QUIPS) instrument. Four studies found no prognostic value for tumor size response, whereas two studies reported a prognostic effect. In these two studies, the survival rate of patients with progressive disease was not separately analyzed from patients with stable disease, potentially explaining the difference in study outcome. In conclusion, our findings support that early progression of disease is associated with poorer survival, justifying adaptation of therapy. However, in patients with non-progressive disease, there is no evidence that the degree of response is a prognostic marker for survival. Because the vast majority of patients do not have progressive disease, early tumor size response should be reconsidered for assessment of treatment efficacy. Therefore, at present, early surrogate biomarkers for survival are still lacking.
Postoperative Trends and Prognostic Values of Inflammatory and Nutritional Biomarkers after Liver Transplantation for Hepatocellular Carcinoma
Authors: Pravisani Riccardo , Mocchegiani Federico , Isola Miriam , Lorenzin Dario , Adani Gian Luigi , Cherchi Vittorio , De Martino Maria , Risaliti Andrea , Lai Quirino , Vivarelli Marco , Baccarani Umberto
Published: January 2021

Preoperative inflammatory biomarkers such as the Platelet-to-Lymphocyte Ratio (PLR) and the Neutrophil-to-Lymphocyte Ratio (NLR) strongly predict the outcome in surgically treated patients with hepatocellular carcinoma (HCC), while nutritional biomarkers such as the Controlling Nutritional Status (CONUT) and the Prognostic Nutritional Index (PNI) show an analogue prognostic value in hepatic resection (HR) but not in liver transplant (LT) cases. Data on the impact of LT on the inflammatory and nutritional/metabolic function are heterogeneous. Therefore, we investigated the post-LT trend of these biomarkers up to postoperative month (POM) 12 in 324 HCC patients treated with LT. Inflammatory biomarkers peaked in the early post-LT period but at POM 3 leveled off at values similar (NLR) or higher (PLR) than pre-LT ones. CONUT and PNI worsened in the early post-LT period, but at POM 3 they stabilized at significantly better values than pre-LT. In LT recipients with an overall survival >1 year and no evidence of early HCC recurrence, 1 year post-LT NLR and PNI independently predicted patient overall survival, while 1 year post-LT PLR independently predicted late tumor recurrence. In conclusion, at 1 year post-LT, the nutritional status of liver-transplanted HCC patients significantly improved while their inflammatory state tended to persist. Consequently, post-LT PLR and NLR maintained a prognostic value for LT outcome while post-LT CONUT and PNI acquired it.
Genetic Analysis of Multiple Myeloma Identifies Cytogenetic Alterations Implicated in Disease Complexity and Progression
Authors: Li Can , Wendlandt Erik B. , Darbro Benjamin , Xu Hongwei , Thomas Gregory S. , Tricot Guido , Chen Fangping , Shaughnessy John D. , Zhan Fenghuang
Published: January 2021

Multiple myeloma (MM) is a genetically heterogeneous disease characterized by genomic chaos making it difficult to distinguish driver from passenger mutations. In this study, we integrated data from whole genome gene expression profiling (GEP) microarrays and CytoScan HD high-resolution genomic arrays to integrate GEP with copy number variations (CNV) to more precisely define molecular alterations in MM important for disease initiation, progression and poor clinical outcome. We utilized gene expression arrays from 351 MM samples and CytoScan HD arrays from 97 MM samples to identify eight CNV events that represent possible MM drivers. By integrating GEP and CNV data we divided the MM into eight unique subgroups and demonstrated that patients within one of the eight distinct subgroups exhibited common and unique protein network signatures that can be utilized to identify new therapeutic interventions based on pathway dysregulation. Data also point to the central role of 1q gains and the upregulated expression of ANP32E, DTL, IFI16, UBE2Q1, and UBE2T as potential drivers of MM aggressiveness. The data presented here utilized a novel approach to identify potential driver CNV events in MM, the creation of an improved definition of the molecular basis of MM and the identification of potential new points of therapeutic intervention.
Clinical and Molecular-Based Approach in the Evaluation of Hepatocellular Carcinoma Recurrence after Radical Liver Resection
Authors: Gruttadauria Salvatore , Barbera Floriana , Conaldi Pier Giulio , Pagano Duilio , Liotta Rosa , Gringeri Enrico , Miraglia Roberto , Burgio Gaetano , Barbara Marco , Pietrosi Giada , Cammà Calogero , Di Francesco Fabrizio
Published: January 2021

Background: Hepatic resection remains the treatment of choice for patients with early-stage HCC with preserved liver function. Unfortunately, however, the majority of patients develop tumor recurrence. While several clinical factors were found to be associated with tumor recurrence, HCC pathogenesis is a complex process of accumulation of somatic genomic alterations, which leads to a huge molecular heterogeneity that has not been completely understood. The aim of this study is to complement potentially predictive clinical and pathological factors with next-generation sequencing genomic profiling and loss of heterozygosity analysis. Methods: 124 HCC patients, who underwent a primary hepatic resection from January 2016 to December 2019, were recruited for this study. Next-generation sequencing (NGS) analysis and allelic imbalance assessment in a case-control subgroup analysis were performed. A time-to-recurrence analysis was performed as well by means of Kaplan–Meier estimators. Results: Cumulative number of HCC recurrences were 26 (21%) and 32 (26%), respectively, one and two years after surgery. Kaplan–Meier estimates for the probability of recurrence amounted to 37% (95% C.I.: 24–47) and to 51% (95% C.I.: 35–62), after one and two years, respectively. Multivariable analysis identified as independent predictors of HCC recurrence: hepatitis C virus (HCV) infection (HR: 1.96, 95%C.I.: 0.91–4.24, p = 0.085), serum bilirubin levels (HR: 5.32, 95%C.I.: 2.07–13.69, p = 0.001), number of nodules (HR: 1.63, 95%C.I.: 1.12–2.38, p = 0.011) and size of the larger nodule (HR: 1.11, 95%C.I.: 1.03–1.18, p = 0.004). Time-to-recurrence analysis showed that loss of heterozygosity in the PTEN loci (involved in the PI3K/AKT/mTOR signaling pathway) was significantly associated with a lower risk of HCC recurrence (HR: 0.35, 95%C.I.: 0.13–0.93, p = 0.036). Conclusions: multiple alterations of cancer genes are associated with HCC progression. In particular, the evidence of a specific AI mutation presented in 20 patients seemed to have a protective effect on the risk of HCC recurrence.
Prognostic Factors for Functional Outcome of Patients with Optic Nerve Sheath Meningiomas Treated with Stereotactic Radiotherapy–Evaluation of Own and Meta-Analysis of Published Data
Authors: Pintea Bogdan , Boström Azize , Katsigiannis Sotiris , Gousias Konstantinos , Pintea Rares , Baumert Brigitta , Boström Jan
Published: January 2021

Objective: To evaluate prognostic factors for a favorable outcome (improvement of the visual acuity or visual fields) after fractionated stereotactic radiotherapy (fSRT) of optic nerve sheath meningioma (ONSM). Methods: We performed a database search for ONSM treatments during the period from April 2008 to September 2019 in the prospective database for stereotactic radiosurgery/radiotherapy (SRS/SRT) of the Robert Janker Clinic Bonn (Department of Radiotherapy) and performed a literature review and meta-analysis of published data on ONSM between 2010 and 2019. Ophthalmic status before and after treatment was evaluated and the collective was dichotomized into two groups: functional improvement (FI; improvement of either visual acuity or visual fields) and non functional improvement (NFI; with stable or deteriorating visual acuity or visual fields). The two groups were compared regarding different variables: pretreatment visual acuity, age, gender, gross tumor volume (GTV), follow up (FU) time, tumor localization, and maximal retina dose. Results: Overall, 13 stereotactic radiotherapies were performed for ONSM (12 × fSRT, 1 × SRS). Mean follow up was 3 years (range: 1–5 years). The total dose was 50.4 Gy (5 × 1.8 Gy/week) in 12 patients treated with fSRT and 1 × 14 Gy in one SRS case. Mean GTV was 1.13 ccm (range: 0.44–2.20 ccm). During follow up, all tumors were stable or showed shrinkage of tumor volume (100% tumor control), no adverse events were observed, 53% of the patients achieved either better visual acuity or visual fields. Pretreatment visual acuity was significantly different between the FI and the NFI group (0.17 vs. 0.63, p = 0.03) in our series and in the meta analysis (p < 0.01). Moreover, shorter FU time and lower retinal dose were significantly linked (p < 0.05 and p < 0.01, respectively) with a better outcome in the meta-analysis but not in our patient cohort. Intracranial tumor localization, gender, and age were not significantly different between the two outcome groups. Conclusion: FSRT for ONSM achieves in over 50% of cases an improvement of the ophthalmic status with low morbidity and excellent tumor control in our series and the meta analysis. Patients with a favorable outcome had in all analysis a significantly higher visual acuity before treatment start. Therefore, we advocate using fSRT as early as possible before vision deterioration occurs.
CDK4/6 Inhibition Reprograms Mitochondrial Metabolism in BRAFV600 Melanoma via a p53 Dependent Pathway
Authors: Santiappillai Nancy T. , Abuhammad Shatha , Slater Alison , Kirby Laura , McArthur Grant A. , Sheppard Karen E. , Smith Lorey K.
Published: January 2021

Cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitors are being tested in numerous clinical trials and are currently employed successfully in the clinic for the treatment of breast cancers. Understanding their mechanism of action and interaction with other therapies is vital in their clinical development. CDK4/6 regulate the cell cycle via phosphorylation and inhibition of the tumour suppressor RB, and in addition can phosphorylate many cellular proteins and modulate numerous cellular functions including cell metabolism. Metabolic reprogramming is observed in melanoma following standard-of-care BRAF/MEK inhibition and is involved in both therapeutic response and resistance. In preclinical models, CDK4/6 inhibitors overcome BRAF/MEK inhibitor resistance, leading to sustained tumour regression; however, the metabolic response to this combination has not been explored. Here, we investigate how CDK4/6 inhibition reprograms metabolism and if this alters metabolic reprogramming observed upon BRAF/MEK inhibition. Although CDK4/6 inhibition has no substantial effect on the metabolic phenotype following BRAF/MEK targeted therapy in melanoma, CDK4/6 inhibition alone significantly enhances mitochondrial metabolism. The increase in mitochondrial metabolism in melanoma cells following CDK4/6 inhibition is fuelled in part by both glutamine metabolism and fatty acid oxidation pathways and is partially dependent on p53. Collectively, our findings identify new p53-dependent metabolic vulnerabilities that may be targeted to improve response to CDK4/6 inhibitors.
Mechanisms and Therapeutic Implications of GSK-3 in Treating Neurodegeneration
Authors: Rippin Ido , Eldar-Finkelman Hagit
Published: January 2021

Neurodegenerative disorders are spreading worldwide and are one of the greatest threats to public health. There is currently no adequate therapy for these disorders, and therefore there is an urgent need to accelerate the discovery and development of effective treatments. Although neurodegenerative disorders are broad ranging and highly complex, they may share overlapping mechanisms, and thus potentially manifest common targets for therapeutic interventions. Glycogen synthase kinase-3 (GSK-3) is now acknowledged to be a central player in regulating mood behavior, cognitive functions, and neuron viability. Indeed, many targets controlled by GSK-3 are critically involved in progressing neuron deterioration and disease pathogenesis. In this review, we focus on three pathways that represent prominent mechanisms linking GSK-3 with neurodegenerative disorders: cytoskeleton organization, the mammalian target of rapamycin (mTOR)/autophagy axis, and mitochondria. We also consider the challenges and opportunities in the development of GSK-3 inhibitors for treating neurodegeneration.
How Living in Vulnerable Conditions Undermines Cognitive Development: Evidence from the Pediatric Population of Guatemala
Authors: Ibáñez-Alfonso Joaquín A. , Company-Córdoba Rosalba , García de la Cadena Claudia , Sianes Antonio , Simpson Ian Craig
Published: January 2021

Low-socioeconomic backgrounds represent a risk factor for children’s cognitive development and well-being. Evidence from many studies highlights that cognitive processes may be adversely affected by vulnerable contexts. The aim of this study was to determine if living in vulnerable conditions affects childhood cognitive development. To achieve this, we assessed the performance of a sample of 347 Guatemalan children and adolescents aged from 6 to 17 years (M = 10.8, SD = 3) in a series of 10 neuropsychological tasks recently standardized for the pediatric population of this country. Two-fifths of the sample (41.5%) could be considered to have vulnerable backgrounds, coming from families with low-socioeconomic status or having had a high exposure to violence. As expected, results showed lower scores in language and attention for the vulnerable group. However, contrary to expectations, consistent systematic differences were not found in the executive function tasks. Vulnerable children obtained lower scores in cognitive flexibility compared to the non-vulnerable group, but higher scores in inhibition and problem-solving tasks. These results suggest the importance of developing pediatric standards of cognitive performance that take environmental vulnerable conditions into consideration. These findings, one of the first obtained in the Guatemalan population, also provide relevant information for specific educational interventions and public health policies which will enhance vulnerable children and adolescent cognitive development.
The INUS Platform: A Modular Solution for Object Detection and Tracking from UAVs and Terrestrial Surveillance Assets
Authors: Maltezos Evangelos , Douklias Athanasios , Dadoukis Aris , Misichroni Fay , Karagiannidis Lazaros , Antonopoulos Markos , Voulgary Katerina , Ouzounoglou Eleftherios , Amditis Angelos
Published: January 2021

Situational awareness is a critical aspect of the decision-making process in emergency response and civil protection and requires the availability of up-to-date information on the current situation. In this context, the related research should not only encompass developing innovative single solutions for (real-time) data collection, but also on the aspect of transforming data into information so that the latter can be considered as a basis for action and decision making. Unmanned systems (UxV) as data acquisition platforms and autonomous or semi-autonomous measurement instruments have become attractive for many applications in emergency operations. This paper proposes a multipurpose situational awareness platform by exploiting advanced on-board processing capabilities and efficient computer vision, image processing, and machine learning techniques. The main pillars of the proposed platform are: (1) a modular architecture that exploits unmanned aerial vehicle (UAV) and terrestrial assets; (2) deployment of on-board data capturing and processing; (3) provision of geolocalized object detection and tracking events; and (4) a user-friendly operational interface for standalone deployment and seamless integration with external systems. Experimental results are provided using RGB and thermal video datasets and applying novel object detection and tracking algorithms. The results show the utility and the potential of the proposed platform, and future directions for extension and optimization are presented.
Acknowledgment to Reviewers of Drones in 2020
Authors:   Drones Editorial Office
Published: January 2021

Peer review is the driving force of journal development, and reviewers are gatekeepers who ensure that Drones maintains its standards for the high quality of its published papers [...]
U-Model-Based Two-Degree-of-Freedom Internal Model Control of Nonlinear Dynamic Systems
Authors: Li Ruobing , Zhu Quanmin , Narayan Pritesh , Yue Alex , Yao Yufeng , Deng Mingcong
Published: January 2021

This paper proposes a U-Model-Based Two-Degree-of-Freedom Internal Model Control (UTDF-IMC) structure with strength in nonlinear dynamic inversion, and separation of tracking design and robustness design. This approach can effectively accommodate modeling error and disturbance while removing those widely used linearization techniques for nonlinear plants/processes. To assure the expansion and applications, it analyses the key properties associated with the UTDF-IMC. For initial benchmark testing, computational experiments are conducted using MATLAB/Simulink for two mismatched linear and nonlinear plants. Further tests consider an industrial system, in which the IMC of a Permanent Magnet Synchronous Motor (PMSM) is simulated to demonstrate the effectiveness of the design procedure for potential industrial applications.
A Multi-Scale Feature Extraction-Based Normalized Attention Neural Network for Image Denoising
Authors: Wang Yi , Song Xiao , Gong Guanghong , Li Ni
Published: January 2021

Due to the rapid development of deep learning and artificial intelligence techniques, denoising via neural networks has drawn great attention due to their flexibility and excellent performances. However, for most convolutional network denoising methods, the convolution kernel is only one layer deep, and features of distinct scales are neglected. Moreover, in the convolution operation, all channels are treated equally; the relationships of channels are not considered. In this paper, we propose a multi-scale feature extraction-based normalized attention neural network (MFENANN) for image denoising. In MFENANN, we define a multi-scale feature extraction block to extract and combine features at distinct scales of the noisy image. In addition, we propose a normalized attention network (NAN) to learn the relationships between channels, which smooths the optimization landscape and speeds up the convergence process for training an attention model. Moreover, we introduce the NAN to convolutional network denoising, in which each channel gets gain; channels can play different roles in the subsequent convolution. To testify the effectiveness of the proposed MFENANN, we used both grayscale and color image sets whose noise levels ranged from 0 to 75 to do the experiments. The experimental results show that compared with some state-of-the-art denoising methods, the restored images of MFENANN have larger peak signal-to-noise ratios (PSNR) and structural similarity index measure (SSIM) values and get better overall appearance.
Reaction Characteristics of Organosolv-Fractionation Process for Selective Extraction of Carbohydrates and Lignin from Rice Husks
Authors: Kim Tae Hoon , Kwak Hyun , Kim Tae Hyun , Oh Kyeong Keun
Published: January 2021

The organosolv-fractionation process can act as a biorefinery process because it can separate the main components of biomass, such as lignin and hemicellulose, with high purity. The ethanol-based organosolv-fractionation process was applied to separate carbohydrates and lignin from rice husks, and the extraction behavior was observed according to various reaction variables. Various reaction conditions such as different temperatures (150 °C, 170 °C, and 190 °C), reaction times (30 min, 60 min, and 120 min), and ethanol concentrations (40%, 60%, and 80%) were tested while maintaining the solid:liquid ratio (1:10) and sulfuric acid concentration (0.25 wt.%). Two optimal reaction conditions for the target components were chosen: for sugar recovery, 150 °C, 60 min, and 40% ethanol were used as condition 1, and for lignin recovery, 170 °C, 120 min, and 80% ethanol were used as condition 2. Under condition 1, 91.5% of the glucan was preserved in the residual solid, and 75.0% of the xylan was extracted from the liquid hydrolysate. For condition 2, 59.9% of the lignin was recovered. To properly choose and apply the correct fractionation method and conditions, the reaction behavior (such as carbohydrate retention and extraction), lignin solubilization, and precipitation should be carefully considered.
A Grid-Tied Fuel Cell Multilevel Inverter with Low Harmonic Distortions
Authors: Ben Hamad Khlid , Luta Doudou N. , Raji Atanda K.
Published: January 2021

As a result of global energy demand increase, concerns over global warming, and rapid exhaustion of fossil fuels, there is a growing interest in energy system dependence on clean and sustainable energy resources. Attractive power technologies include photovoltaic panels, wind turbines, and biomass power. Fuel cells are also clean energy units that substitute power generators based on fossil fuels. They are employed in various applications, including transportation, stationary power, and small portable power. Fuel cell connections to utility grids require that the power conditioning units, interfacing the fuel cells and the grids, operate accordingly (by complying with the grid requirements). This study aims to model a centralised, single-stage grid-tied three-level diode clamped inverter interfacing a multi-stack fuel cell system. The inverter is expected to produce harmonic distortions of less than 0.5% and achieve an efficiency of 85%. Besides the grid, the system consists of a 1.54 MW/1400 V DC proton exchange membrane fuel cell, a 1.3 MW three-level diode clamped inverter with a nominal voltage of 600 V, and an inductance-capacitance-inductance (LCL) filter. Two case studies based on the load conditions are considered to assess the developed system’s performance further. In case 1, the fuel cell system generates enough power to fully meet this load and exports the excess to the grid. In the other case, a load of 2.5 MW was connected at the grid-tied fuel cell inverter’s output terminals. The system imports the grid’s power to meet the 2.5 MW load since the fuel cell can only produce 1.54 MW. It is demonstrated that the system can supply and also receive power from the grid. The results show the developed system’s good performance with a low total harmonic distortion of about 0.12% for the voltage and 0.07% for the current. The results also reveal that the fuel cell inverter voltage and the frequency at the point of common coupling comply with the grid requirements.
Do Environment-Related Policy Instruments and Technologies Facilitate Renewable Energy Generation? Exploring the Contextual Evidence from Developed Economies
Authors: Shahzad Umer , Radulescu Magdalena , Rahim Syed , Isik Cem , Yousaf Zahid , Ionescu Stefan
Published: January 2021

Attaining sustainable development and cleaner production is a major challenge both for developed and developing economies; income, institutional regulations, institutional quality and international trade are the key determinants of environmental externalities. The current work attempts to study the role of environmental taxes and regulations on renewable energy generation for developed economies. For that, the authors have used the annual dataset for the period 1994 to 2018. More specifically, the study investigates the impacts of environmental taxes, environment-related technologies and the environmental policy stringency index on renewable electricity generation in 29 developed countries. Given the short available data of these countries, the authors have developed panel cointegration and panel regressions models (fully modified ordinary least square (FMOLS), quantile regressions). The heterogeneous panel empirics stated that environmental regulations and income level support renewable electricity generation. The conclusions further mention that bureaucratic qualities such as decision making and trade openness tend to reduce renewable energy generation. The empirical findings allowed us to draw new narrative and implications. Overall, the conclusions argue that innovative regulations and policies can be useful for attaining specific sustainable development goals (e.g., SDG-7: cleaner and cheap energy).
Model-Based Evaluation of Air-Side Fouling in Closed-Circuit Cooling Towers
Authors: Nienborg Björn , Mathieu Marc , Schwärzler Alexander , Conzelmann Katharina , Schnabel Lena
Published: January 2021

Fouling is a permanent problem in process technology and is estimated to cost 0.25% of the gross national product. Evaporative cooling systems are especially susceptible to air-side fouling: as they work with untreated outside air, they are exposed to both natural (e.g., pollen) and human-made (e.g., industrial dust) contaminants. In addition, suspended solid particles and dissolved salts in the spray water are an issue. In this study we analyzed an approach for fouling detection based on a semi-physical (grey-box) cooling tower model which we calibrated with measurement data. A test series with reliable laboratory data indicates good applicability of the model. In three datasets, the performance decreases due to fouling (scaling, which was provoked intentionally) in the range of 5–11% were clearly detected. When applied to measurement data of two cooling towers in real applications, the model also proved to be well calibratable with relatively little data (two to four operating days). For two data sets, the model yielded reasonable results when applied to long term data: a cooling tower cleaning could be retraced and nominal operation was verified during the remaining time. During the analysis of a third data set a temporary performance deviation was found, which could not be explained with the recorded data. Thus, the approach turned out to be generally applicable but requires further verification and refinement in order to increase the robustness. If successful, it can be transferred to a commercial product for need-oriented maintenance in order to reduce cooling tower operating costs and environmental impact.
Development of a Deep Neural Network Model for Estimating Joint Location of Occupant Indoor Activities for Providing Thermal Comfort
Authors: Choi Eun Ji , Moon Jin Woo , Han Ji-hoon , Yoo Yongseok
Published: January 2021

The type of occupant activities is a significantly important factor to determine indoor thermal comfort; thus, an accurate method to estimate occupant activity needs to be developed. The purpose of this study was to develop a deep neural network (DNN) model for estimating the joint location of diverse human activities, which will be used to provide a comfortable thermal environment. The DNN model was trained with images to estimate 14 joints of a person performing 10 common indoor activities. The DNN contained numerous shortcut connections for efficient training and had two stages of sequential and parallel layers for accurate joint localization. Estimation accuracy was quantified using the mean squared error (MSE) for the estimated joints and the percentage of correct parts (PCP) for the body parts. The results show that the joint MSEs for the head and neck were lowest, and the PCP was highest for the torso. The PCP for individual activities ranged from 0.71 to 0.92, while typing and standing in a relaxed manner were the activities with the highest PCP. Estimation accuracy was higher for relatively still activities and lower for activities involving wide-ranging arm or leg motion. This study thus highlights the potential for the accurate estimation of occupant indoor activities by proposing a novel DNN model. This approach holds significant promise for finding the actual type of occupant activities and for use in target indoor applications related to thermal comfort in buildings.
Optimization of Multi-Way Valve Structure in Digital Hydraulic System of Loader
Authors: Li Chunshuang , Liu Xinhui , Wang Xin , Chen Jinshi , Wang Yuqi
Published: January 2021

In this paper, a digital hydraulic variable control method based on multi-way valve spool displacement feedback is proposed, which combines the advantages of low cost and high reliability of the loader fixed displacement pump hydraulic system, and the distinguished energy saving effect of the loader variable pump hydraulic system. Based on the principle of hydraulic resistance, the mathematical model of flow-pressure of multi-way valve was established. Meanwhile, the theoretical structure of a valve spool suitable for digital hydraulic system was deduced. On this basis, an improvement scheme of the valve spool was proposed in combination with machining feasibility. The simulation model of multi-way valve was established, the correctness of which was verified by experiment with the significance test method, and the valve port parameters of the multi-way valve were optimized by genetic algorithm. The simulation model before and after optimization was analyzed by AMESim software. The simulation results showed that the digital hydraulic system can basically realize the function of a variable system, and the energy consumption was significantly reduced compared with the fixed displacement pump hydraulic system. The optimized valve spool structure of the digital hydraulic system had more stable load characteristics than the fixed displacement pump system and a larger speed range. The increase range accounts for about 27% of the total stroke.
ELM-QR-Based Nonparametric Probabilistic Prediction Method for Wind Power
Authors: Niu Honghai , Yang Yu , Zeng Lingchao , Li Yiguo
Published: January 2021

Wind power has significant randomness. Probabilistic prediction of wind power is necessary to solve the problem of safe and stable power grid dispatching with the integration of large-scale wind power. Therefore, this paper proposes a novel nonparametric probabilistic prediction model for wind power based on extreme learning machine-quantile regression (ELM-QR). Firstly, the ELM-QR models of multiple quantiles are established, and then the new comprehensive index (NCI) is optimized by particle swarm optimization (PSO) to obtain the weighting coefficients corresponding to the lower and upper bounds of the prediction intervals. The final prediction interval is obtained by integrating the outputs of ELM-QR models and the weighting coefficients. Finally, case studies are carried out with the real wind farm operation data, simulation results show that the proposed algorithm can obtain narrower prediction intervals while ensuring high reliability. Through sensitivity analysis and comparison with other algorithms, the effectiveness of the proposed algorithm is further verified.
Effectiveness of Power Electronic Controllers in Mitigating Acoustic Noise and Vibration in High-Rotor Pole SRMs
Authors: Zhang Ziyan , Yaman Selin , Salameh Mohamad , Singh Suryadev , Chen Chengxiu , Krishnamurthy Mahesh
Published: January 2021

This paper presents a comparative evaluation of power electronic control approaches for vibro-acoustic noise reduction in High Rotor-Pole Switched Reluctance Machines (HR-SRM). It carries out a fundamental analysis of approaches that can be used to target acoustic noise and vibration reduction. Based on the comprehensive study, four candidates for control have been identified and applied to the HR-SRM drive to evaluate their effectiveness and identify challenges. These four methods include phase advancing, current shaping based on field reconstruction, and random hysteresis band with and without spectrum shaping. The theoretical background, implementation, and vibro-acoustic noise reduction performance of each method are presented in detail. Comparative studies from simulation and experimental measurements have been used to identify the most effective solution to acoustic noise and vibration reduction in HR-SRM configuration.
Effects of SiO2 Nanoparticle Dispersion on The Heat Storage Property of the Solar Salt for Solar Power Applications
Authors: Li Zhao , Cui Liu , Li Baorang , Du Xiaoze
Published: January 2021

The effects of SiO2 nanoparticles on the heat storage properties of Solar Salt (NaNO3-KNO3) are studied using experimental and molecular dynamics (MD) simulations. The experiment results show the specific heat capacity of the molten salt-based nanofluids is higher than that of the pure base salt. We focus on the inference regarding the possible mechanisms behind the enhancement of the specific heat capacity which are considered more acceptable by the majority of researchers, the energy and force in the system are analyzed by MD simulations. The results demonstrate that the higher specific heat capacity of the nanoparticle is not the reason leading to the heat storage enhancement. Additionally, the analysis of potential energy and system configuration shows that the other possible mechanisms (i.e., interfacial thermal resistance theory and compressed layer theory) are only superficial. The forces between the nanoparticle atoms and base salt ions construct the constraint of the base salt ions, further forms the interfacial thermal resistance, and the compressed layer around the nanoparticle. This constraint has a more stable state and requires more energy to deform it, leading to the improvement of the heat storage property of nanofluids. Our findings uncover the mechanisms of specific heat capacity enhancement and guide the preparation of molten salt-based nanofluids.
Council Press Offices as Sources of Political Information: Between Journalism for Accountability and Propaganda
Authors: Rodríguez-Breijo Vanessa , Simelio Núria , Molina-Rodríguez-Navas Pedro
Published: January 2021

This study uses a qualitative approach to examine what political and technical leaders of municipalities understand transparency and public information to mean, and what role they believe the different subjects involved (government, opposition, and the public) should have. The websites of 605 Spanish councils with more than 100,000 inhabitants were analysed and three focus groups were held with political and technical leaders from a selection of sample councils. The results show that the technical and political leaders of the councils do not have a clear awareness of their function of management accountability or of the need to apply journalistic criteria to the information they publish, defending with nuances the use of propaganda criteria to focus on the actions of the local government, its information, the lack of space dedicated to public debate and the opposition’s actions. In relation to accountability and citizen participation, they have a negative view of citizens, who they describe as being disengaged. However, they emphasize that internally it is essential to continue improving in terms of the culture of transparency and the public information they provide citizens.
Teaching Physics for Computer Science Students in Higher Education During the COVID-19 Pandemic: A Fully Internet-Supported Course
Authors: Delgado Francisco
Published: January 2021

The COVID-19 pandemic has modified and diversified the ways that students receive education. During confinements, complex courses integrating previous knowledge must be carefully designed and implemented to effectively replace the elements present in face-to-face learning to improve the students’ experience. This work assesses the implementation of a digital-learning physics course for computer science students in a skill-based education program in higher education. The assessment was useful for the institution to evaluate if the digital strategy implemented in the course fulfilled the original premises and objectives. The analyses performed provide useful knowledge of theoretical and operational actions applied in this methodology that could be adapted to similar courses for the younger generations in this university. COVID-19 confinement will continue in Mexico in 2021. This assessment resulted in a positive evaluation of the digital strategy being followed, which can be continued while the contingency lasts. Three teachers came together to design math, physics, and computational sciences content for various sections of a physics course. The analysis was developed and implemented according to an institutional digital delivery model for the COVID-19 pandemic. Elements related to attendance, digital access, performance distribution by gender, activity types, and the course learning sections were considered. The analysis was performed with some techniques found in the literature for small groups, complemented when necessary by standard statistical tests to discern meaningful trends. A primary goal was to assess skill-based learning in the course delivered digitally due to the COVID-19 confinement. Furthermore, additional issues concerning the learning dynamics were searched, reported, and analyzed. Finally, the outcomes of an institutional exit survey collecting students’ opinions supported certain observed behaviors. The analysis produced meaningful evidence that the course’s skill-based development was well supported by the digital delivery during the confinement. Furthermore, differences in the students’ performances in the various course content sections proved statistically significant and are discussed in this work.
TLR-Mediated Cytokine Gene Expression in Chicken Peripheral Blood Mononuclear Cells as a Measure to Characterize Immunobiotics
Authors: Slawinska Anna , Dunislawska Aleksandra , Plowiec Arkadiusz , Gonçalves José , Siwek Maria
Published: January 2021

Immunobiotics are probiotics that promote intestinal health by modulating immune responses. Immunobiotics are recognized by Toll-like receptors (TLRs) and activate cytokine gene expression. This study aimed to characterize cytokine gene expression in the chicken peripheral blood mononuclear cells (PBMC) stimulated with purified TLR ligands and live probiotics. PBMC were isolated from the whole blood. PBMC were stimulated with: lipopolysaccharide (LPS), CpG ODN, Pam3CSK4, Zymosan, galactooligosaccharides (GOS), Lactococcuslactis subsp. cremoris (L. lactis), and Saccharomyces cerevisiae at 42.5 °C and 5% CO2 for 3 h, 6 h, and 9 h. After each time-point, PBMC were harvested for RNA isolation. Relative gene expression was analyzed with RT-qPCR for cytokine genes (IL-1β, IL-2, IL-3, IL-4, IL-6, IL-8, IL-10, IL-12p40, and IFN-ɣ) and reference genes (ACTB and G6PDH). Genes were clustered into pro-inflammatory genes, Th1/Th2 genes, and Th1-regulators. The gene expression differed between treatments in IL1-β, IL-6, IL-8, IL-10, and IL-12p40 (p < 0.001). The genes IL-1β, IL-6, and IL-8 had the highest fold change of mRNA expression at 3 h in response to TLR ligands. L. lactis up-regulated the pro-inflammatory genes at the 6 h time-point. L. lactis did not activate the anti-inflammatory IL-10 gene, but activated IL-12p40 at 6 h. Hereby, L. lactis was proven to exert immunostimulatory properties in PBMC.