bluuebunny/crossref_metadata_2025 huggingface dataset:
The Impact of the Aromatization of Production Environment on Workers: A Systematic Literature Review
Authors: Čarnogurský Karol , Diačiková Anna , Madzík Peter
Published: June 2021

Literature on aromatization in production environments is very limited. The literature rather describes the impact of aromachology on employees in administrative premises, but published research results on the influence of aromachology in production premises are not available. There are no scientifically based studies and research that analyze and provide at least partial evidence of the impact of fragrances on the productivity and economic performance of companies. For the study of the literature of the area of our scientific interest, we chose the globally most frequently used scientific information database Scopus. In deciding on the selection of keyword combinations and in the search, we relied primarily on our previous experience and the area of research, which is the aromatization of spaces in industrial production, and its impact on the performance of employees, respectively. We also consider the industrial applications of aromachology, and how an indoor environment is important for people’s health and comfort.
Design and Simulation of a Vision-Based Automatic Trout Fish-Processing Robot
Authors: Azarmdel Hossein , Mohtasebi Seyed Saeid , Jafary Ali , Behfar Hossein , Rosado Muñoz Alfredo
Published: June 2021

Today, industrial automation is being applied in a wide range of fields. The initial modeling of robots and mechanical systems together with simulation results in optimal systems. In this study, the designed system is simulated to obtain the required velocities, accelerations and torques of the actuating arms in a vision-based automatic system. Due to the slippery skin of fish and the low friction coefficient, it is not easy to design an optimal tool to handle fish. Since the fish-processing operation is undertaken step by step and provides fish stability, it is essential that the gripper enables different processing operations along the system. The proposed system performs belly-cutting, beheading, gutting, and cleaning stages for different fish sizes, based on the extracted dimensions of the vision system. In the head-cutting section, the average speed of the actuator jack was considered as 500 mm s−1. Under these conditions, the maximum required force to provide this speed was 332.45 N. In the belly-cutting subsystem, the required torque for the stepper motor resulted in 1.79–2.15 N m. Finally, the maximum required torque for the gutting stepper motor was calculated as 0.69 N m in the tested processing capacities.
Zero Average Dynamic Controller for Speed Control of DC Motor
Authors: Hoyos Fredy E. , Candelo-Becerra John E. , Rincón Alejandro
Published: June 2021

This paper presents the use of the buck converter with Zero Average Dynamics to control the speed of a permanent magnet direct current motor. For this objective, we consider a fourth-order nonlinear model that describes the system’s dynamics and tests different scenarios to determine how the direct current motor responds. The results show a robust speed tracking performance of the direct current motor under the reference signal and controller parameter changes and disturbances in the load torque. A non-saturated duty cycle with fixed commutation frequency is obtained in the power supply of the DC motor, and a low steady-state value of the speed tracking error is achieved in both experimental and simulation results. In summary, the effectiveness of the Zero Average Dynamics control strategy for high order systems was experimentally proved.
Correlations between Process and Geometric Parameters in Additive Manufacturing of Austenitic Stainless Steel Components Using 3DPMD
Authors: Hoefer Kevin
Published: June 2021

The additive manufacturing of components is characterized by a layered build-up. The stability of the build-up process with regard to the component geometry and the layer thickness is essential for the success of the entire system. A prerequisite for this is the exact knowledge of the interrelationships between the process, construction parameters and the resulting component geometry, respectively. These correlations are determined within the study using the 3D Plasma Metal Deposition Process (3DPMD). For this purpose, the process is first subjected to a system analysis. Possible influencing variables were identified with regard to the question “Which system parameters influence the component geometry?” and then prioritized. Then, the influence of control factors (welding current intensity, welding speed, and powder mass flow) was investigated according to the specifications of the Design of Experiments (DOE) method by means of a full-factorial experimental design and evaluated on the basis of metallographic cross-sections. As a result, it was determined that the system parameter powder mass flow only influences the layer thickness and not the wall thickness and is, therefore, available as a process control variable. In sum, comprehensive knowledge of complex relationships between the control parameters and the component geometry in additive manufacturing using 3DPMD was achieved and forms the basis for further scientific work.
Methods of Constructing Time Series for Predicting Local Time Scales by Means of a GMDH-Type Neural Network
Authors: Sobolewski Łukasz , Miczulski Wiesław
Published: June 2021

Ensuring the best possible stability of UTC(k) (local time scale) and its compliance with the UTC scale (Universal Coordinated Time) forces predicting the [UTC-UTC(k)] deviations, the article presents the results of work on two methods of constructing time series (TS) for a neural network (NN), increasing the accuracy of UTC(k) prediction. In the first method, two prepared TSs are based on the deviations determined according to the UTC scale with a 5-day interval. In order to improve the accuracy of predicting the deviations, the PCHIP interpolating function is used in subsequent TSs, obtaining TS elements with a 1-day interval. A limitation in the improvement of prediction accuracy for these TS has been a too large prediction horizon. The introduction in 2012 of the additional UTC Rapid scale by BIPM makes it possible to shorten the prediction horizon, and the building of two TSs has been proposed according to the second method. Each of them consists of two subsets. The first subset is based on deviations determined according to the UTC scale, the second on the UTC Rapid scale. The research of the proposed TS in the field of predicting deviations for the Polish Timescale by means of GMDH-type NN shows that the best accuracy of predicting the deviations has been achieved for TS built according to the second method.
An Alternative Approach to Obtain a New Gain in Step-Size of LMS Filters Dealing with Periodic Signals
Authors: Ramos Lorente Pedro , Martín Ferrer Raúl , Arranz Martínez Fernando , Palacios-Navarro Guillermo
Published: June 2021

Partial updates (PU) of adaptive filters have been successfully applied in different contexts to lower the computational costs of many control systems. In a PU adaptive algorithm, only a fraction of the coefficients is updated per iteration. Particularly, this idea has been proved as a valid strategy in the active control of periodic noise consisting of a sum of harmonics. The convergence analysis carried out here is based on the periodic nature of the input signal, which makes it possible to formulate the adaptive process with a matrix-based approach, the periodic least-mean-square (P-LMS) algorithm In this paper, we obtain the upper bound that limits the step-size parameter of the sequential PU P-LMS algorithm and compare it to the bound of the full-update P-LMS algorithm. Thus, the limiting value for the step-size parameter is expressed in terms of the step-size gain of the PU algorithm. This gain in step-size is the quotient between the upper bounds ensuring convergence in the following two scenarios: first, when PU are carried out and, second, when every coefficient is updated during every cycle. This step-size gain gives the factor by which the step-size can be multiplied so as to compensate for the convergence speed reduction of the sequential PU algorithm, which is an inherently slower strategy. Results are compared with previous results based on the standard sequential PU LMS formulation. Frequency-dependent notches in the step-size gain are not present with the matrix-based formulation of the P-LMS. Simulated results confirm the expected behavior.
Estimation of Lane-Level Traffic Flow Using a Deep Learning Technique
Authors: Liu Chieh-Min , Juang Jyh-Ching
Published: June 2021

This paper proposes a neural network that fuses the data received from a camera system on a gantry to detect moving objects and calculate the relative position and velocity of the vehicles traveling on a freeway. This information is used to estimate the traffic flow. To estimate the traffic flows at both microscopic and macroscopic levels, this paper used YOLO v4 and DeepSORT for vehicle detection and tracking. The number of vehicles passing on the freeway was then calculated by drawing virtual lines and hot zones. The velocity of each vehicle was also recorded. The information can be passed to the traffic control center in order to monitor and control the traffic flows on freeways and analyze freeway conditions.
Assessment of GPM IMERG Satellite Precipitation Estimation under Complex Climatic and Topographic Conditions
Authors: Lu Chengxuan , Ye Jian , Fang Guohua , Huang Xianfeng , Yan Min
Published: June 2021

Satellite precipitation estimation provides crucial information for those places lacking rainfall observations from ground–based sensors, especially in terrestrial or marine areas with complex climatic or topographic conditions. This is the case over much of Western China, including Upper and Middle Lancang River Basin (UMLRB), an extremely important transnational river system in Asia (the Lancang–Mekong River Basin) with complex climate and topography that has limited long–term precipitation records and high–elevation data, and no operational weather radars. In this study, we evaluated three GPM IMERG satellite precipitation estimation (IMERG E, IMERG L and IMERG F) over UMLRB in terms of multi–year average precipitation distribution, amplitude consistency, occurrence consistency, and elevation–dependence in both dry and wet seasons. Results demonstrated that monsoon and solid precipitation mainly affected amplitude consistency of precipitation, aerosol affected occurrence consistency of precipitation, and topography and wind–induced errors affected elevation dependence. The amplitude and occurrence consistency of precipitation were best in wet seasons in the Climate Transition Zone and worst in dry seasons in the same zone. Regardless of the elevation–dependence of amplitude or occurrence in dry and wet seasons, the dry season in the Alpine Canyon Area was most positively dependent and most significant. More significant elevation–dependence was correlated with worse IMERG performance. The Local Weighted Regression (LOWERG) model showed a nonlinear relationship between precipitation and elevation in both seasons. The amplitude consistency and occurrence consistency of both seasons worsened with increasing precipitation intensity and was worst for extreme precipitation cases. IMERG F had great potential for application to hydroclimatic research and water resources assessment in the study area. Further research should assess how the dependence of IMERG’s spatial performance on climate and topography could guide improvements in global precipitation assessment algorithms and the study of mountain landslides, floods, and other natural disasters during the monsoon period.
Meteorological Extremes in Korea: Prediction, Assessment, and Impact
Authors: Lee Okjeong , Kim Sangdan
Published: June 2021

The extreme climates that occur around the world every year have a profound impact on the quality of life for mankind since they can cause natural disasters beyond our control, such as droughts and floods [...]
Performance Evaluation of a Nowcasting Modelling Chain Operatively Employed in Very Small Catchments in the Mediterranean Environment for Civil Protection Purposes
Authors: Raffellini Martina , Martina Federica , Silvestro Francesco , Giannoni Francesca , Rebora Nicola
Published: June 2021

The Hydro-Meteorological Centre (CMI) of the Environmental Protection Agency of Liguria Region, Italy, is in charge of the hydrometeorological forecast and the in-event monitoring for the region. This region counts numerous small and very small basins, known for their high sensitivity to intense storm events, characterised by low predictability. Therefore, at the CMI, a radar-based nowcasting modelling chain called the Small Basins Model Chain, tailored to such basins, is employed as a monitoring tool for civil protection purposes. The aim of this study is to evaluate the performance of this model chain, in terms of: (1) correct forecast, false alarm and missed alarm rates, based on both observed and simulated discharge threshold exceedances and observed impacts of rainfall events encountered in the region; (2) warning times respect to discharge threshold exceedances. The Small Basins Model Chain is proven to be an effective tool for flood nowcasting and helpful for civil protection operators during the monitoring phase of hydrometeorological events, detecting with good accuracy the location of intense storms, thanks to the radar technology, and the occurrence of flash floods.
Characteristics and Source Apportionment of Black Carbon (BC) in a Suburban Area of Klang Valley, Malaysia
Authors: Ezani Eliani , Dhandapani Sairam , Heal Mathew R. , Praveena Sarva M. , Khan Md Firoz , Ramly Zamzam T. A.
Published: June 2021

Black carbon (BC) is of concern due to its contribution to poor air quality and its adverse effects human health. We carried out the first real-time monitoring of BC in Malaysia using an AE33 Aethalometer. Measurements were conducted between 1 January and 31 May 2020 in a university area in a suburban location of the Klang Valley. The measurement period coincided with the implementation of a movement control order (MCO) in response to COVID-19. The mean concentration of BC before the MCO was 2.34 µg/m3 which decreased by 38% to 1.45 µg/m3 during the MCO. The BC is dominated by fossil-fuel sources (mean proportion BCff = 79%). During the MCO, the BCff concentration decreased by more than the BCbb concentration derived from biomass burning. BC and BCff show very strong diurnal cycles, which also show some weekday–weekend differences, with maxima during the night and just before noon, and minima in the afternoon. These patterns indicate strong influences on concentrations from both traffic emissions and boundary layer depth. BC was strongly correlated with NO2 (R = 0.71), another marker of traffic emission, but less strongly with PM2.5 (R = 0.52). The BC absorption Ångström exponent (AAE) ranged between 1.1 and 1.6. We observed pronounced diurnal cycles of lower AAE in daytime, corresponding to BCff contributions from traffic. Average AAE also showed a pronounced increase during the MCO. Our data provides a new reference for BC in suburban Malaysia for the public and policy-makers, and a baseline for future measurements.
Spatial Regression Modeling Approach for Assessing the Spatial Variation of Air Pollutants
Authors: Park Seunghoon , Ko Dongwon
Published: June 2021

Over the past decades, industrialization has resulted in radical economic development in Korea. The resulting urban sprawl and unsustainable development have led to considerable air pollution. In this study, using spatial regression models, we examine the effects of the physical and socioeconomic characteristics of neighborhoods on particulate matter (PM10, PM2.5), NO2, CO, and SO2 concentrations in the Daegu Metropolitan area. Results reveal the following: (i) the socioeconomic characteristics were not statistically significant regardless of the air pollutant type; (ii) the effects of the built environment characteristics of the neighborhoods were different for each air pollutant. Compared with other pollutants, PM2.5 was affected more by the built environment. Concerning the neighborhoods’ main roads, the SO2 concentration was higher, that of PM2.5 was higher in neighborhoods with more bus stops, and those of CO and PM2.5 were possibly higher in the neighborhood of industrial zones. In neighborhoods with parks and green areas, air pollutant concentrations are likely to be lower. When the total used surface of residential buildings was higher, the air pollutant concentrations were lower. Contextually, similar neighborhoods with more single-family houses seemed to have high pollution levels. Overall, this study is expected to guide policymakers and planners in making smart decisions for eco-friendly and healthy cities.
A Refined Study of Atmospheric Wind Properties in the Beijing Urban Area Based on a 325 m Meteorological Tower
Authors: Zhang Shi , Li Bo , Solari Giovanni , Zhang Xinxin , Xu Xiaoda
Published: June 2021

The urban atmospheric boundary layer (UABL) is complex due to the heterogeneous underlying city surface. The nine anemometers installed at different heights along the 325 m meteorological tower provide an opportunity to carry out a refined study of wind properties in the UABL in central Beijing, China. Based on the recent 5-year high-resolution measured data, in total, 229,488 10-min length segments of wind records related to each anemometer are reliable for further analyses. Accordingly, the statistical properties of the wind speed and direction are first analyzed to present the local wind climate in a comprehensive way. Moreover, the pattern of the wind profiles related to two typical synoptic intense events are illustrated in order to give a preliminary perspective, then the statistical properties corresponding to a series of intense windstorms are described. Here, the deviations in the wind direction occur between 200 m and 280 m of the atmosphere, which might be due to the existence of an Ekman spiral; besides this, the laws of wind profiles based on open terrain are not suitable for the UABL, and the aerodynamic characteristic parameters of the UABL based on vertical stratified structures have to be considered. The results contribute to the establishment of revised models for the wind profile and are useful for the further understanding of the structure of UABL wind.
Can the European Hedgehog (Erinaceus europaeus) Be a Sentinel for One Health Concerns?
Authors: Jota Baptista Catarina Vinhas , Seixas Fernanda , Gonzalo-Orden José Manuel , Oliveira Paula A.
Published: June 2021

Erinaceus europaeus is a cosmopolitan mammalian species broadly distributed in Europe, from natural to suburban areas. Due to its ecological role and susceptibility to distinct zoonotic agents, E. europaeus could be a suitable sentinel candidate for many global problems that negatively affect human and animal health. Hedgehogs can work as bioindicators to environmental contamination and can be hosts for multiple tickborne zoonotic agents. Thus, people who directly or indirectly make physical contact with this species are exposed to a variety of threats. Moreover, it has also been studied as an indicator for antibiotic resistance, which was already confirmed for tetracyclines. Additionally, it was also reported as a reservoir for methicillin-resistant Staphylococcus aureus (MRSA). More recently, hedgehogs have been recently recognised as potential reservoirs of MERS-CoV-like strains. Among other animals, this species can possibly represent an intermediate reservoir for SARS-CoV-2. The aim of this review is to briefly expose the scientific attainments about hedgehog health, namely agents, diseases, and threats that significantly affect general health concerns and that contribute to achieve One Health principles.
Tobacco and Nervous System Development and Function—New Findings 2015–2020
Authors: Hajdusianek Wojciech , Żórawik Aleksandra , Waliszewska-Prosół Marta , Poręba Rafał , Gać Paweł
Published: June 2021

Tobacco is a one of the most common addictive stimulants used by people around the world. The smoke generated during tobacco combustion is a toxic mixture of more than 5000 chemicals of which over 30 are known human carcinogens. While its negative effects on the human body are well understood, it remains a serious public health problem. One of the multiple effects of smoking is tobacco’s effect on the nervous system—its development and function. This review aims to summarize the progress made in research on the effects of tobacco on the nervous system both of the perinatal period and adults and both in animals and humans in 2015–2020. The 1245 results that corresponded to the keywords “tobacco, cigarette, nervous system, brain, morphology, function” were reviewed, of which 200 abstracts were considered significant. Most of those articles broadened the knowledge about the negative effects of smoking on the human nervous system. Tobacco has a significant negative impact on the development of nervous structures, neurotransmission and cognitive functions, and promotes the development of neurodegenerative diseases, insomnia and cerebrovascular diseases. The only exception is the protective effect of the dopaminergic system in Parkinson’s disease. In conclusion, in recent years much effort has been devoted to describing, revealing and uncovering new aspects of tobacco detrimental to human life. The nicotine contained in tobacco smoke affects the human body in a multidimensional way, including a serious impact on the broadly understood neurological health.
Differentiating Functional Cognitive Disorder from Early Neurodegeneration: A Clinic-Based Study
Authors: Ball Harriet A. , Swirski Marta , Newson Margaret , Coulthard Elizabeth J. , Pennington Catherine M.
Published: June 2021

Functional cognitive disorder (FCD) is a relatively common cause of cognitive symptoms, characterised by inconsistency between symptoms and observed or self-reported cognitive functioning. We aimed to improve the clinical characterisation of FCD, in particular its differentiation from early neurodegeneration. Two patient cohorts were recruited from a UK-based tertiary cognitive clinic, diagnosed following clinical assessment, investigation and expert multidisciplinary team review: FCD, (n = 21), and neurodegenerative Mild Cognitive Impairment (nMCI, n = 17). We separately recruited a healthy control group (n = 25). All participants completed an assessment battery including: Hopkins Verbal Learning Test-Revised (HVLT-R), Trail Making Test Part B (TMT-B); Depression Anxiety and Stress Scale (DASS) and Minnesota Multiphasic Personality Inventory (MMPI-2RF). In comparison to healthy controls, the FCD and nMCI groups were equally impaired on trail making, immediate recall, and recognition tasks; had equally elevated mood symptoms; showed similar aberration on a range of personality measures; and had similar difficulties on inbuilt performance validity tests. However, participants with FCD performed significantly better than nMCI on HVLT-R delayed free recall and retention (regression coefficient −10.34, p = 0.01). Mood, personality and certain cognitive abilities were similarly altered across nMCI and FCD groups. However, those with FCD displayed spared delayed recall and retention, in comparison to impaired immediate recall and recognition. This pattern, which is distinct from that seen in prodromal neurodegeneration, is a marker of internal inconsistency. Differentiating FCD from nMCI is challenging, and the identification of positive neuropsychometric features of FCD is an important contribution to this emerging area of cognitive neurology.
Raman Spectroscopy Investigation of Graphene Oxide Reduction by Laser Scribing
Authors: Scardaci Vittorio , Compagnini Giuseppe
Published: June 2021

Laser scribing has been proposed as a fast and easy tool to reduce graphene oxide (GO) for a wide range of applications. Here, we investigate laser reduction of GO under a range of processing and material parameters, such as laser scan speed, number of laser passes, and material coverage. We use Raman spectroscopy for the characterization of the obtained materials. We demonstrate that laser scan speed is the most influential parameter, as a slower scan speed yields poor GO reduction. The number of laser passes is influential where the material coverage is higher, producing a significant improvement of GO reduction on a second pass. Material coverage is the least influential parameter, as it affects GO reduction only under restricted conditions.
Comment on Ibrahim et al. The Effects of In-Plane Spatial Resolution on CT-Based Radiomic Features’ Stability with and without ComBat Harmonization. Cancers 2021, 13, 1848
Authors: Orlhac Fanny , Buvat Irène
Published: June 2021

We read with great interest the paper by Ibrahim et al. [...]
The Cellular and Biological Impact of Extracellular Vesicles in Pancreatic Cancer
Authors: Hussain Zainab , Nigri Jeremy , Tomasini Richard
Published: June 2021

Deciphering the interactions between tumor and stromal cells is a growing field of research to improve pancreatic cancer-associated therapies and patients’ care. Indeed, while accounting for 50 to 90% of the tumor mass, many pieces of evidence reported that beyond their structural role, the non-tumoral cells composing the intra-tumoral microenvironment influence tumor cells’ proliferation, metabolism, cell death and resistance to therapies, among others. Simultaneously, tumor cells can influence non-tumoral neighboring or distant cells in order to shape a tumor-supportive and immunosuppressive environment as well as influencing the formation of metastatic niches. Among intercellular modes of communication, extracellular vesicles can simultaneously transfer the largest variety of signals and were recently reported as key effectors of cell–cell communication in pancreatic cancer, from its development to its evolution as well as its ability to resist available treatments. This review focuses on extracellular vesicles-mediated communication between different cellular components of pancreatic tumors, from the modulation of cellular activities and abilities to their biological and physiological relevance. Taking into consideration the intra-tumoral microenvironment and its extracellular-mediated crosstalk as main drivers of pancreatic cancer development should open up new therapeutic windows.
Tolerance and Effectiveness of Targeted Therapies in Aged Patients with Metastatic Melanoma
Authors: Becquart Ondine , Oriano Bastien , Dalle Stéphane , Mortier Laurent , Leccia Marie Thérèse , Dutriaux Caroline , Dalac Sophie , Montaudié Henri , De Quatrebarbes Julie , Brunet-Possenti Florence , Saiag Philippe , Lesimple Thierry , Beylot-Barry Marie , Aubin Francois , Stoebner Pierre-Emmanuel , Arnault Jean-Philippe , Dreno Brigitte , Porcher Raphael , Lebbe Celeste , Guillot Bernard
Published: June 2021

Purpose: Melanoma’s incidence is increasing, and elderly people could be significantly impacted since the majority occurs in people over 65 years of age. Combined BRAF and MEK targeted therapies (TT) are current standard regimen for BRAF mutated metastatic melanoma (MM). Except for subgroups of pivotal trials, little data are available for TT in this population. Materials and Methods: Outcomes were explored in real life patients from MelBase, a French multicentric biobank dedicated to the prospective follow-up of unresectable stage III or IV melanoma. Patients treated by BRAF TT and/or MEK TT combined or not, were included from 2013 to 2017 in 2 groups: group 1 ≤ 65-year-old (yo), group 2 > 65 yo, analyzed for tolerance and efficacy. Results: 353 patients were included: 231 in group 1, 122 in group 2. Median follow-up was 12 months (M). Median time of treatment was 6.9 M. A total of 80% had at least one Adverse Effect (AE). Most frequent AE (all grades) were mainly skin and subcutaneous, general, and gastrointestinal disorders. A total of 31% of AE were grade 3–4: 28% in group 1 and 39% in group 2 (p = 0.05). No differences were observed in all AE grades proportion, dose modifications, interruptions, and discontinuations. For each group, median overall survival was 20.3 M (CI 95%: 15.5–27.9) and 16.3 M (CI: 14.5–26.9), respectively (p = 0.8). Median progression free survival was 7.8 M (6.4–9.9) and 7.7 M (CI: 5.8–11.3) (p = 0.4). Objective response rate was 59% and 50% (p = 0.6). Conclusion: This study on a large multicentric cohort is the first to assess that TT is well tolerated in elderly BRAF-mutated patients such as in patients younger than 65. Efficacy was similar between groups with outcomes reaching those from pivotal studies. There is thus no argument against using TT in elderly people, although an onco-geriatric opinion is welcome for the most vulnerable.
Front-Line Window Therapy with Temozolomide and Irinotecan in Patients with Primary Disseminated Multifocal Ewing Sarcoma: Results of the ISG/AIEOP EW-2 Study
Authors: Asaftei Sebastian Dorin , Puma Nadia , Paioli Anna , Petraz Marco , Morosi Carlo , Podda Marta , Tamburini Angela , Palmerini Emanuela , Coccoli Luca , Grignani Giovanni , Manzitti Carla , Bertulli Rossella , De Leonardis Francesco , Rabusin Marco , Campello Anna , Tirtei Elisa , Picci Piero , Prete Arcangelo , Longhi Alessandra , Fagioli Franca , Luksch Roberto
Published: June 2021

Purpose: The main objective was to evaluate the activity and tolerability of TEMIRI as a front-line treatment in primary disseminated Ewing sarcoma (PDMES) using the RECIST 1.1 criteria. The secondary objectives included the assessment of toxicity and the performance status/symptom changes. Methods: Between 2012 and 2018, patients with PDMES received two courses of temozolomide 100 mg/sqm/day + irinotecan 50 mg/sqm/day for 5 days every 3 weeks as an amendment to the Italian Sarcoma Group/Associazione Italiana EmatoIogia ed Oncologia Pediatrica (ISG/AIEOP) EW-2 protocol (EUDRACT#2009-012353-37, Vers. 1.02). Results: Thirty-four patients were enrolled. The median age at diagnosis was 19 years (range 3–55). After TEMIRI, the RECIST response was as follows: a partial response in 20 (59%) patients, stable disease in 11 (32%), and disease progression in 3 (9%). The ECOG/Lansky score was improved in 25/34 (73.5%) cases, and a reduction or disappearance of pain was observed in 31/34 patients (91%). The incidence of grade 3–4 toxicity was 3%. The 3-year event-free survival (EFS) and overall survival (OS) were 21% (95% CI 6–35%) and 36% (95% CI: 18–54%), respectively. Conclusion: the smooth handling and encouraging activity demonstrated by up-front TEMIRI did not change the EFS in PDMES, so this result suggests the need for the further evaluation of the efficacy of TEMIRI in combination with conventional treatments in non-metastatic patients.
Cancer and Pregnancy: A Comprehensive Review
Authors: Schwab Roxana , Anic Katharina , Hasenburg Annette
Published: June 2021

Cancer diagnosis and treatment in pregnant women is a challenging situation. A multidisciplinary network of specialists is required to guide both, the expecting mother and the unborn child through the diagnostic workup and the cytotoxic therapy, by balancing the respective risks and benefits. Tumor entity, stage, biology and gestational week at diagnosis determine the appropriate approach. As premature delivery emerged as one of the main risk factors for adverse long-term outcome of the progeny, it should be avoided, if reasonable from the oncological perspective. This article offers a comprehensive review with respect to the various aspects of cancer in pregnancy.
Fibroblast Growth Factor Receptor (FGFR) Signaling in GIST and Soft Tissue Sarcomas
Authors: Napolitano Andrea , Ostler Alexandra E. , Jones Robin L. , Huang Paul H.
Published: June 2021

Sarcomas are a heterogeneous group of rare malignancies originating from mesenchymal tissues with limited therapeutic options. Recently, alterations in components of the fibroblast growth factor receptor (FGFR) signaling pathway have been identified in a range of different sarcoma subtypes, most notably gastrointestinal stromal tumors, rhabdomyosarcomas, and liposarcomas. These alterations include genetic events such as translocations, mutations, and amplifications as well as transcriptional overexpression. Targeting FGFR has therefore been proposed as a novel potential therapeutic approach, also in light of the clinical activity shown by multi-target tyrosine kinase inhibitors in specific subtypes of sarcomas. Despite promising preclinical evidence, thus far, clinical trials have enrolled very few sarcoma patients and the efficacy of selective FGFR inhibitors appears relatively low. Here, we review the known alterations of the FGFR pathway in sarcoma patients as well as the preclinical and clinical evidence for the use of FGFR inhibitors in these diseases. Finally, we discuss the possible reasons behind the current clinical data and highlight the need for biomarker stratification to select patients more likely to benefit from FGFR targeted therapies.
Mismatch Repair: From Preserving Genome Stability to Enabling Mutation Studies in Real-Time Single Cells
Authors: Elez Marina
Published: June 2021

Mismatch Repair (MMR) is an important and conserved keeper of the maintenance of genetic information. Miroslav Radman’s contributions to the field of MMR are multiple and tremendous. One of the most notable was to provide, along with Bob Wagner and Matthew Meselson, the first direct evidence for the existence of the methyl-directed MMR. The purpose of this review is to outline several aspects and biological implications of MMR that his work has helped unveil, including the role of MMR during replication and recombination editing, and the current understanding of its mechanism. The review also summarizes recent discoveries related to the visualization of MMR components and discusses how it has helped shape our understanding of the coupling of mismatch recognition to replication. Finally, the author explains how visualization of MMR components has paved the way to the study of spontaneous mutations in living cells in real time.
A High-Response Electrochemical As(III) Sensor Using Fe3O4–rGO Nanocomposite Materials
Authors: Hu Haibing , Lu Wenjie , Liu Xingnan , Meng Fancheng , Zhu Jianxiong
Published: June 2021

Nowadays, heavy metal ion pollution in water is becoming more and more common, especially arsenic, which seriously threatens human health. In this work, we used Fe3O4–rGO nanocomposites to modify a glassy carbon electrode and selected square wave voltametric electrochemical detection methods to detect trace amounts of arsenic in water. Field emission scanning electron microscopy (FESEM) and transmission electron microscopy (TEM) showed that Fe3O4 nanoparticles were uniformly distributed on the rGO sheet, with a particle size of about 20 nm. Raman spectroscopy and electrochemical impedance spectroscopy (EIS) showed that rGO provides higher sensitivity and conductive substrates. Under optimized experimental conditions, Fe3O4–rGO-modified glassy carbon electrodes showed a higher sensitivity (2.15 µA/ppb) and lower limit of detection (1.19 ppb) for arsenic. They also showed good selectivity, stability, and repeatability.
Development of Electrospun Films from Wastewater Treatment Plant Sludge
Authors: Lavrič Gregor , Miletić Aleksandra , Pilić Branka , Medvešček Daša , Nastran Saša , Vrabič-Brodnjak Urška
Published: June 2021

Electrospinning is a versatile method for producing continuous polymer nanofibers, including from wastewater treatment plant sludge (WTPS). In this context, purified WTPS was successfully used to produce electrospun fibers. The main objective of our research was to produce new, local, circular, renewable and environmentally friendly packaging material. The aim of the research was to purify and treat WTPS to make it suitable for the electrospinning process, thus producing a new material and chemically characterizing it in the first step. One of the major advantages of our process was that the electrospinning process could be carried out with water and ethylenediaminetetraacetic acid. The optimal viscosity was determined to be 20,000 mPas in order to produce sufficient nanofibers. Analyses such as Fourier-Transform Infrared Spectroscopy (FTIR) and 1H-NMR (proton nuclear magnetic resonance) were used to determine the substances of unpurified and purified WTPS. The tensile properties, contact angle, surface properties and differential scanning calorimetry of the final material were determined and used. The 1H-NMR analysis confirmed the presence of a small quantity of polyhydroxyalkanoates in the samples. Based on the properties, the final material was brittle and less stretchable compared to electrospun packaging films available in the market.
Tautomeric Equilibrium of an Asymmetric β-Diketone in Halogen-Bonded Cocrystals with Perfluorinated Iodobenzenes
Authors: Martinez Valentina , Bedeković Nikola , Stilinović Vladimir , Cinčić Dominik
Published: June 2021

In order to study the effect of halogen bond on tautomerism in β-diketones in the solid-state, we have prepared a series of cocrystals derived from an asymmetric β-diketone, benzoyl-4-pyridoylmethane (b4pm), as halogen bond acceptor and perfluorinated iodobenzenes: iodopentaflourobenzene (ipfb), 1,2-, 1,3- and 1,4-diiodotetraflorobenzene (12tfib, 13tfib and 14tfib) and 1,3,5-triiodo-2,4,6-trifluorobenzene (135titfb). All five cocrystals are assembled by I···N halogen bonds involving pyridyl nitrogen and iodoperfluorobenzene iodine resulting in 1:1 (four compounds) or 1:2 (one compound) cocrystal stoichiometry. Tautomer of b4pm in which hydrogen atom is adjacent to the pyridyl fragment was found to be more stable in vacuo than tautomer with a benzoyl hydroxyl group. This tautomer is also found to be dominant in the majority of crystal structures, somewhat more abundantly in crystal structures of cocrystals in which additional I···O halogen bond with the benzoyl oxygen has been established. Attempts have also been made to prepare an equivalent series of cocrystals using a closely related asymmetric β-diketone, benzoyl-3-pyridoylmethane (b3pm); however, all attempts were unsuccessful, which is attributed to more effective crystal packing of b3pm isomer compared to b4pm, which reduced the probability of cocrystal formation.
Balanced Mechanical and Tribological Performance of High-Frequency-Sintered Al-SiC Achieved via Innovative Milling Route—Experimental and Theoretical Study
Authors: Fouly Ahmed , Almotairy Saud M. , Aijaz Muhammad Omer , Alharbi Hamad F. , Abdo Hany S.
Published: June 2021

In this study, Al-SiC nanocomposite was fabricated via powder metallurgy route using different innovative high-energy ball-milling techniques (HEBM). The powder mixture was consolidated using high-frequency induction heat sintering process (HFIHS). With the aim of studying the physical, mechanical, and tribological performance of the fabricated nanocomposites. Relative density, hardness, compressive yield strength, Young’s modulus, toughness, elongation, specific wear rate and coefficient of friction were experimentally investigated. A finite element model for the frictional process was built to find out the distribution of contact stresses as result of samples sliding. It was found that the highest the energy of the milling, the more improvement in the mechanical and tribological performance could significantly achieved due to the homogeneous distribution and the excellent bonding effect of the composite. In addition, field emission scanning electron microscope was used for studying the sliding surface morphology in order to explicate the mechanism of the dry wear process.
Effect of Batchelor Flow on Polymorphic Crystallization in a Rotating Disk Crystallizer
Authors: Li Zun-Hua , Kim Jinsoo , Kim Woo-Sik
Published: June 2021

In this work, the influence of Batchelor flow on the polymorphic crystallization in a rotating disk (RD) crystallizer was investigated. By regulating crystallization parameters, i.e., the rotation speed, cooling rate, and ethanol fraction, we found that a higher fraction of L-histidine stable Form-A at the induction time and a faster rate of phase transformation could be obtained in the RD crystallizer as compared to previous results in a mixing tank crystallizer. Based on these results, we concluded that the polymorphic crystallization in the RD crystallizer was more effective due to Batchelor flow fluid motion.
Long Term Real-World Outcomes of Trifluridine/Tipiracil in Metastatic Colorectal Cancer—A Single UK Centre Experience
Authors: Tong Daniel , Wang Lei , Mendis Jeewaka , Essapen Sharadah
Published: June 2021

In the UK, Trifluridine-tipiracil (Lonsurf) is used to treat metastatic colorectal cancer in the third-line setting, after prior exposure to fluoropyrimidine-based regimes. Current data on the real-world use of Lonsurf lack long-term follow-up data. A retrospective evaluation of patients receiving Lonsurf at our Cancer Centre in 2016–2017 was performed, all with a minimum of two-year follow-up. Fifty-six patients were included in the review. The median number of cycles of Lonsurf administered was 3. Median follow-up was 6.0 months, with all patients deceased at the time of analysis. Median progression-free survival (PFS) was 3.2 months, and overall survival (OS) was 5.8 months. The median interval from Lonsurf discontinuation to death was two months, but seven patients received further systemic treatment and median OS gained was 12 months. Lonsurf offered a slightly better PFS but inferior OS to that of the RECOURSE trial, with PFS similar to real-world data previously presented. Interestingly, 12.5% had a PFS > 9 months, and this cohort had primarily left-sided and RAS wild-type disease. A subset received further systemic treatment on Lonsurf discontinuation with good additional OS benefit. Lonsurf may alter the course of disease for a subset of patients, and further treatment on progression can be considered in carefully selected patients.
Group and Shuffle Convolutional Neural Networks with Pyramid Pooling Module for Automated Pterygium Segmentation
Authors: Abdani Siti Raihanah , Zulkifley Mohd Asyraf , Zulkifley Nuraisyah Hani
Published: June 2021

Pterygium is an eye condition that is prevalent among workers that are frequently exposed to sunlight radiation. However, most of them are not aware of this condition, which motivates many volunteers to set up health awareness booths to give them free health screening. As a result, a screening tool that can be operated on various platforms is needed to support the automated pterygium assessment. One of the crucial functions of this assessment is to extract the infected regions, which directly correlates with the severity levels. Hence, Group-PPM-Net is proposed by integrating a spatial pyramid pooling module (PPM) and group convolution to the deep learning segmentation network. The system uses a standard mobile phone camera input, which is then fed to a modified encoder-decoder convolutional neural network, inspired by a Fully Convolutional Dense Network that consists of a total of 11 dense blocks. A PPM is integrated into the network because of its multi-scale capability, which is useful for multi-scale tissue extraction. The shape of the tissues remains relatively constant, but the size will differ according to the severity levels. Moreover, group and shuffle convolution modules are also integrated at the decoder side of Group-PPM-Net by placing them at the starting layer of each dense block. The addition of these modules allows better correlation among the filters in each group, while the shuffle process increases channel variation that the filters can learn from. The results show that the proposed method obtains mean accuracy, mean intersection over union, Hausdorff distance, and Jaccard index performances of 0.9330, 0.8640, 11.5474, and 0.7966, respectively.
Meta-Tree Random Forest: Probabilistic Data-Generative Model and Bayes Optimal Prediction
Authors: Dobashi Nao , Saito Shota , Nakahara Yuta , Matsushima Toshiyasu
Published: June 2021

This paper deals with a prediction problem of a new targeting variable corresponding to a new explanatory variable given a training dataset. To predict the targeting variable, we consider a model tree, which is used to represent a conditional probabilistic structure of a targeting variable given an explanatory variable, and discuss statistical optimality for prediction based on the Bayes decision theory. The optimal prediction based on the Bayes decision theory is given by weighting all the model trees in the model tree candidate set, where the model tree candidate set is a set of model trees in which the true model tree is assumed to be included. Because the number of all the model trees in the model tree candidate set increases exponentially according to the maximum depth of model trees, the computational complexity of weighting them increases exponentially according to the maximum depth of model trees. To solve this issue, we introduce a notion of meta-tree and propose an algorithm called MTRF (Meta-Tree Random Forest) by using multiple meta-trees. Theoretical and experimental analyses of the MTRF show the superiority of the MTRF to previous decision tree-based algorithms.
No-Reference Quality Assessment for 3D Synthesized Images Based on Visual-Entropy-Guided Multi-Layer Features Analysis
Authors: Jin Chongchong , Peng Zongju , Zou Wenhui , Chen Fen , Jiang Gangyi , Yu Mei
Published: June 2021

Multiview video plus depth is one of the mainstream representations of 3D scenes in emerging free viewpoint video, which generates virtual 3D synthesized images through a depth-image-based-rendering (DIBR) technique. However, the inaccuracy of depth maps and imperfect DIBR techniques result in different geometric distortions that seriously deteriorate the users’ visual perception. An effective 3D synthesized image quality assessment (IQA) metric can simulate human visual perception and determine the application feasibility of the synthesized content. In this paper, a no-reference IQA metric based on visual-entropy-guided multi-layer features analysis for 3D synthesized images is proposed. According to the energy entropy, the geometric distortions are divided into two visual attention layers, namely, bottom-up layer and top-down layer. The feature of salient distortion is measured by regional proportion plus transition threshold on a bottom-up layer. In parallel, the key distribution regions of insignificant geometric distortion are extracted by a relative total variation model, and the features of these distortions are measured by the interaction of decentralized attention and concentrated attention on top-down layers. By integrating the features of both bottom-up and top-down layers, a more visually perceptive quality evaluation model is built. Experimental results show that the proposed method is superior to the state-of-the-art in assessing the quality of 3D synthesized images.
Unifying Node Labels, Features, and Distances for Deep Network Completion
Authors: Wei Qiang , Hu Guangmin
Published: June 2021

Collected network data are often incomplete, with both missing nodes and missing edges. Thus, network completion that infers the unobserved part of the network is essential for downstream tasks. Despite the emerging literature related to network recovery, the potential information has not been effectively exploited. In this paper, we propose a novel unified deep graph convolutional network that infers missing edges by leveraging node labels, features, and distances. Specifically, we first construct an estimated network topology for the unobserved part using node labels, then jointly refine the network topology and learn the edge likelihood with node labels, node features and distances. Extensive experiments using several real-world datasets show the superiority of our method compared with the state-of-the-art approaches.