bluuebunny/crossref_metadata_2025 huggingface dataset:
Candidate Markers of Olaparib Response from Genomic Data Analyses of Human Cancer Cell Lines
Authors: Amuzu Setor , Carmona Euridice , Mes-Masson Anne-Marie , Greenwood Celia M. T. , Tonin Patricia N. , Ragoussis Jiannis
Published: March 2021

The benefit of PARP inhibitor olaparib in relapsed and advanced high-grade serous ovarian carcinoma (HGSOC) is well established especially in BRCA1/2 mutation carriers. Identification of additional biomarkers can help expand the population of patients most likely to benefit from olaparib treatment. To identify candidate markers of olaparib response we analyzed genomic and in vitro olaparib response data from two independent groups of cancer cell lines. Using pan-cancer cell lines (n = 896) from the Genomics of Drug Sensitivity in Cancer database, we applied linear regression methods to identify statistically significant gene predictors of olaparib response based on mRNA expression. We then analyzed whole exome sequencing and mRNA gene expression data from our collection of 18 HGSOC cell lines previously classified as sensitive, intermediate, or resistant based on in vitro olaparib response for mutations, copy number variation and differential expression of candidate olaparib response genes. We identify genes previously associated with olaparib response (SLFN11, ABCB1), and discover novel candidate olaparib sensitivity genes with known functions including interaction with PARP1 (PUM3, EEF1A1) and involvement in homologous recombination DNA repair (ELP4). Further investigations at experimental and clinical levels are required to validate novel candidates, and ultimately determine their efficacy as potential biomarkers of olaparib sensitivity.
Lysosomal Calcium Channels in Autophagy and Cancer
Authors: Wu Yi , Huang Peng , Dong Xian-Ping
Published: March 2021

Ca2+ is pivotal intracellular messenger that coordinates multiple cell functions such as fertilization, growth, differentiation, and viability. Intracellular Ca2+ signaling is regulated by both extracellular Ca2+ entry and Ca2+ release from intracellular stores. Apart from working as the cellular recycling center, the lysosome has been increasingly recognized as a significant intracellular Ca2+ store that provides Ca2+ to regulate many cellular processes. The lysosome also talks to other organelles by releasing and taking up Ca2+. In lysosomal Ca2+-dependent processes, autophagy is particularly important, because it has been implicated in many human diseases including cancer. This review will discuss the major components of lysosomal Ca2+ stores and their roles in autophagy and human cancer progression.
Beyond First-Line Immunotherapy: Potential Therapeutic Strategies Based on Different Pattern Progressions: Oligo and Systemic Progression
Authors: Prelaj Arsela , Pircher Chiara Carlotta , Massa Giacomo , Martelli Valentino , Corrao Giulia , Lo Russo Giuseppe , Proto Claudia , Ferrara Roberto , Galli Giulia , De Toma Alessandro , Genova Carlo , Jereczek-Fossa Barbara Alicja , Braud Filippo de , Garassino Marina Chiara , Rebuzzi Sara Elena
Published: March 2021

First-line immune-checkpoint inhibitor (ICI)-based therapy has deeply changed the treatment landscape and prognosis in advanced non-small cell lung cancer (aNSCLC) patients with no targetable alterations. Nonetheless, a percentage of patients progressed on ICI as monotherapy or combinations. Open questions remain on patients’ selection, the identification of biomarkers of primary resistance to immunotherapy and the treatment strategies to overcome secondary resistance to first-line immunotherapy. Local ablative approaches are the main therapeutic strategies in oligoprogressive disease, and their role is emerging in patients treated with immunotherapy. Many therapeutic strategies can be adapted in aNSCLC patients with systemic progression to personalize the treatment approach according to re-characterization of the tumors, previous ICI response, and type of progression. This review’s aim is to highlight and discuss the current and potential therapeutic approaches beyond first-line ICI-based therapy in aNSCLC patients based on the pattern of disease progression (oligoprogression versus systemic progression).
Fatigue among Long-Term Breast Cancer Survivors: A Controlled Cross-Sectional Study
Authors: Maass Saskia W. M. C. , Brandenbarg Daan , Boerman Liselotte M. , Verhaak Peter F. M. , de Bock Geertruida H. , Berendsen Annette J.
Published: March 2021

Background: Fatigue is the most common and persistent symptom among women in the first five years after a breast cancer diagnosis. However, long-term prevalence of fatigue, among breast cancer survivors, needs further investigation. Aim: To compare fatigue experienced by long-term breast cancer survivors with that in a reference population and to evaluate the determinants of that fatigue. Design and Setting: A cross-sectional cohort study of 350 breast cancer survivors ≥5 years after diagnosis and a reference population of 350 women matched by age and general practitioner. Method: Fatigue was measured using the Multidimensional Fatigue Inventory (MFI-20), and a sum score of >60 (multidimensional fatigue) was the primary outcome. Logistic regression was applied to compare the prevalence of multidimensional fatigue between the survivor and reference populations, adjusted for body mass index (BMI) and for cardiovascular and psychological variables. Odds ratios (ORs) and 95% confidence intervals (95%CIs) were estimated. Logistic regression was applied to evaluate the determinants of multidimensional fatigue among the survivors. Results: Breast cancer survivors (median 10 years after diagnosis), more often experienced multidimensional fatigue than the reference population (26.6% versus 15.4%; OR, 2.0 [95%CI, 1.4–2.9]), even after adjusting for confounders. The odds of multidimensional fatigue were also higher among survivors with symptoms of depression (32.2% versus 2.7%; OR, 17.0 [95%CI, 7.1–40.5]) or anxiety (41.9% versus 10.1%; OR, 6.4 [95%CI, 3.6–11.4]). Conclusion: One in four breast cancer survivors experience multidimensional fatigue and fatigue occurs more frequently than in women of the same age and general practitioner. This fatigue appears to be associated with symptoms of depression and anxiety.
Agonistic CD40 Antibodies in Cancer Treatment
Authors: Djureinovic Dijana , Wang Meina , Kluger Harriet M.
Published: March 2021

CD40 is expressed on a variety of antigen-presenting cells. Stimulation of CD40 results in inflammation by upregulation of other costimulatory molecules, increased antigen presentation, maturation (licensing) of dendritic cells, and activation of CD8+ T cells. Here we analyzed gene expression data from The Cancer Genome Atlas in melanoma, renal cell carcinoma, and pancreatic adenocarcinoma and found correlations between CD40 and several genes involved in antigen presentation and T cell function, supporting further exploration of CD40 agonists to treat cancer. Agonist CD40 antibodies have induced anti-tumor effects in several tumor models and the effect has been more pronounced when used in combination with other treatments (immune checkpoint inhibition, chemotherapy, and colony-stimulating factor 1 receptor inhibition). The reduction in tumor growth and ability to reprogram the tumor microenvironment in preclinical models lays the foundation for clinical development of agonistic CD40 antibodies (APX005M, ChiLob7/4, ADC-1013, SEA-CD40, selicrelumab, and CDX-1140) that are currently being evaluated in early phase clinical trials. In this article, we focus on CD40 expression and immunity in cancer, agonistic human CD40 antibodies, and their pre-clinical and clinical development. With the broad pro-inflammatory effects of CD40 and its ligand on dendritic cells and macrophages, and downstream B and T cell activation, agonists of this pathway may enhance the anti-tumor activity of other systemic therapies.
The Peripheral Immune Landscape of Breast Cancer: Clinical Findings and In Vitro Models for Biomarker Discovery
Authors: Batalha Sofia , Ferreira Sofia , Brito Catarina
Published: March 2021

Breast cancer is the deadliest female malignancy worldwide and, while much is known about phenotype and function of infiltrating immune cells, the same attention has not been paid to the peripheral immune compartment of breast cancer patients. To obtain faster, cheaper, and more precise monitoring of patients’ status, it is crucial to define and analyze circulating immune profiles. This review compiles and summarizes the disperse knowledge on the peripheral immune profile of breast cancer patients, how it departs from healthy individuals and how it changes with disease progression. We propose this data to be used as a starting point for validation of clinically relevant biomarkers of disease progression and therapy response, which warrants more thorough investigation in patient cohorts of specific breast cancer subtypes. Relevant clinical findings may also be explored experimentally using advanced 3D cellular models of human cancer–immune system interactions, which are under intensive development. We review the latest findings and discuss the strengths and limitations of such models, as well as the future perspectives. Together, the scientific advancement of peripheral biomarker discovery and cancer–immune crosstalk in breast cancer will be instrumental to uncover molecular mechanisms and putative biomarkers and drug targets in an all-human setting.
Overview on the Different Patterns of Tumor Vascularization
Authors: Ribatti Domenico , Pezzella Francesco
Published: March 2021

Angiogenesis is a crucial event in the physiological processes of embryogenesis and wound healing. During malignant transformation, dysregulation of angiogenesis leads to the formation of a vascular network of tumor-associated capillaries promoting survival and proliferation of the tumor cells. Starting with the hypothesis formulated by Judah Folkman that tumor growth is angiogenesis-dependent, this area of research has a solid scientific foundation and inhibition of angiogenesis is a major area of therapeutic development for the treatment of cancer. Over this period numerous authors published data of vascularization of tumors, which attributed the cause of neo-vascularization to various factors including inflammation, release of angiogenic cytokines, vasodilatation, and increased tumor metabolism. More recently, it has been demonstrated that tumor vasculature is not necessarily derived by endothelial cell proliferation and sprouting of new capillaries, but alternative vascularization mechanisms have been described, namely vascular co-option and vasculogenic mimicry. In this article, we have analyzed the mechanisms involved in tumor vascularization in association with classical angiogenesis, including post-natal vasculogenesis, intussusceptive microvascular growth, vascular co-option, and vasculogenic mimicry. We have also discussed the role of these alternative mechanism in resistance to anti-angiogenic therapy and potential therapeutic approaches to overcome resistance.
Cardiac Cell Therapy for Heart Repair: Should the Cells Be Left Out?
Authors: Zhu Dashuai , Cheng Ke
Published: March 2021

Cardiovascular disease (CVD) is still the leading cause of death worldwide. Coronary artery occlusion, or myocardial infarction (MI) causes massive loss of cardiomyocytes. The ischemia area is eventually replaced by a fibrotic scar. From the mechanical dysfunctions of the scar in electronic transduction, contraction and compliance, pathological cardiac dilation and heart failure develops. Once end-stage heart failure occurs, the only option is to perform heart transplantation. The sequential changes are termed cardiac remodeling, and are due to the lack of endogenous regenerative actions in the adult human heart. Regenerative medicine and biomedical engineering strategies have been pursued to repair the damaged heart and to restore normal cardiac function. Such strategies include both cellular and acellular products, in combination with biomaterials. In addition, substantial progress has been made to elucidate the molecular and cellular mechanisms underlying heart repair and regeneration. In this review, we summarize and discuss current therapeutic approaches for cardiac repair and provide a perspective on novel strategies that holding potential opportunities for future research and clinical translation.
ACPA Status Correlates with Differential Immune Profile in Patients with Rheumatoid Arthritis
Authors: Floudas Achilleas , Canavan Mary , McGarry Trudy , Mullan Ronan , Nagpal Sunil , Veale Douglas J. , Fearon Ursula
Published: March 2021

Rheumatoid arthritis (RA) is a progressive erosive autoimmune disease that affects 1% of the world population. Anti-citrullinated protein autoantibodies (ACPA) are routinely used for the diagnosis of RA, however 20–30% of patients are ACPA negative. ACPA status is a delineator of RA disease endotypes with similar clinical manifestation but potentially different pathophysiology. Profiling of key peripheral blood and synovial tissue immune populations including B cells, T follicular helper (Tfh) cells and CD4 T cell proinflammatory cytokine responses could elucidate the underlying immunological mechanisms involved and inform a treat to target approach for both ACPA-positive and ACPA-negative RA. Detailed high dimensionality flow cytometric analysis with supervised and unsupervised algorithm analysis revealed unique RA patient peripheral blood B cell and Tfh cell profiles. Synovial tissue single cell analysis of B cell subpopulation distribution was similar between ACPA− and ACPA+ RA patients, highlighting a key role for specific B cell subsets in both disease endotypes. Interestingly, synovial tissue single cell analysis of CD4 T cell proinflammatory cytokine production was markedly different between ACPA− and APCA+ RA patients. RNAseq analysis of RA patient synovial tissue highlighted disease endotype specific gene signatures. ACPA status associates with unique immune profile signatures that reinforce the need for a treat to target approach for both endotypes of RA.
Engineering of Halide Cation in All-Inorganic Perovskite with Full-Color Luminescence
Authors: Gai Cuili , He Dawei , Wang Yongsheng , Wang Jigang , Li Junming
Published: March 2021

All-inorganic halide perovskites are emerging as a class of superstar semiconductors with excellent optoelectronic properties and show great potential for a broad range of applications in solar cells, lighting diodes, X-ray imaging, and photodetectors. Tremendous research about their device performance has been performed since 2015. In this study, we synthesized the all-inorganic perovskite by the hot-injection method and particularly investigated their crystal structural and photoluminescence properties. By halide anion engineering, the all-inorganic perovskites showed a high-symmetry cubic phase. They also showed a tunable optical bandgap, and almost the full color luminescence was achieved (434 to 624 nm). These basic optoelectronic properties could give a guide for further development of this area.
Influence of the Thermomechanical Characteristics of Low-Density Polyethylene Substrates on the Thermoresistive Properties of Graphite Nanoplatelet Coatings
Authors: Coscia Ubaldo , Longo Angela , Palomba Mariano , Sorrentino Andrea , Barucca Gianni , Di Bartolomeo Antonio , Urban Francesca , Ambrosone Giuseppina , Carotenuto Gianfranco
Published: March 2021

Morphological, structural, and thermoresistive properties of films deposited on low-density polyethylene (LDPE) substrates are investigated for possible application in flexible electronics. Scanning and transmission electron microscopy analyses, and X-ray diffraction measurements show that the films consist of overlapped graphite nanoplatelets (GNP) each composed on average of 41 graphene layers. Differential scanning calorimetry and dynamic-mechanical-thermal analysis indicate that irreversible phase transitions and large variations of mechanical parameters in the polymer substrates can be avoided by limiting the temperature variations between −40 and 40 °C. Electrical measurements performed in such temperature range reveal that the resistance of GNP films on LDPE substrates increases as a function of the temperature, unlike the behavior of graphite-based materials in which the temperature coefficient of resistance is negative. The explanation is given by the strong influence of the thermal expansion properties of the LDPE substrates on the thermo-resistive features of GNP coating films. The results show that, narrowing the temperature range from 20 to 40 °C, the GNP on LDPE samples can work as temperature sensors having linear temperature-resistance relationship, while keeping constant the temperature and applying mechanical strains in the 0–4.2 × 10−3 range, they can operate as strain gauges with a gauge factor of about 48.
Spectrally Selective Solar Absorber Coating of W/WAlSiN/SiON/SiO2 with Enhanced Absorption through Gradation of Optical Constants: Validation by Simulation
Authors: Niranjan K. , Kondaiah Paruchuri , Biswas Arup , Kumar V. Praveen , Srinivas G. , Barshilia Harish C.
Published: March 2021

The properties of spectrally selective solar absorber coatings can be fine-tuned by varying the thickness and composition of the individual layers. We have deposited individual layers of WAlSiN, SiON, and SiO2 of thicknesses ~940, 445, and 400 nm, respectively, for measuring the refractive indices and extinction coefficients using spectroscopic ellipsometer measurements. Appropriate dispersion models were used for curve fitting of Ψ and Δ for individual and multilayer stacks in obtaining the optical constants. The W/WAlSiN/SiON/SiO2 solar absorber exhibits a high solar absorptance of 0.955 and low thermal emissivity of 0.10. The refractive indices and extinction coefficients of different layers in the multilayer stack decrease from the substrate to the top anti-reflection layer. The graded refractive index of the individual layers in the multilayer stack enhances the solar absorption. In the tandem absorber, WAlSiN is the main absorbing layer, whereas SiON and SiO2 act as anti-reflection layers. A commercial simulation tool was used to generate the theoretical reflectance spectra using the optical constants are in well accordance with the experimental data. We have attempted to understand the gradation in refractive indices of the multilayer stack and the physics behind it by computational simulation method in explaining the achieved optical properties. In brief, the novelty of the present work is in designing the solar absorber coating based on computational simulation and ellipsometry measurements of individual layers and multilayer stack in achieving a high solar selectivity. The superior optical properties of W/WAlSiN/SiON/SiO2 makes it a potential candidate for spectrally selective solar absorber coatings.
Towards a Rationalization of Ultrafast Laser-Induced Crystallization in Lithium Niobium Borosilicate Glasses: The Key Role of the Scanning Speed
Authors: Muzi Elisa , Cavillon Maxime , Lancry Matthieu , Brisset François , Que Ruyue , Pugliese Diego , Janner Davide , Poumellec Bertrand
Published: March 2021

Femtosecond (fs)-laser direct writing is a powerful technique to enable a large variety of integrated photonic functions in glass materials. One possible way to achieve functionalization is through highly localized and controlled crystallization inside the glass volume, for example by precipitating nanocrystals with second-order susceptibility (frequency converters, optical modulators), and/or with larger refractive indices with respect to their glass matrices (graded index or diffractive lenses, waveguides, gratings). In this paper, this is achieved through fs-laser-induced crystallization of LiNbO3 nonlinear crystals inside two different glass matrices: a silicate (mol%: 33Li2O-33Nb2O5-34SiO2, labeled as LNS) and a borosilicate (mol%: 33Li2O-33Nb2O5-13SiO2-21B2O3, labeled as LNSB). More specifically, we investigate the effect of laser scanning speed on the crystallization kinetics, as it is a valuable parameter for glass laser processing. The impact of scanning energy and speed on the fabrication of oriented nanocrystals and nanogratings during fs-laser irradiation is studied.Fs-laser direct writing of crystallized lines in both LNS and LNSB glass is investigated using both optical and electron microscopy techniques. Among the main findings to highlight, we observed the possibility to maintain crystallization during scanning at speeds ~5 times higher in LNSB relative to LNS (up to ~600 µm/s in our experimental conditions). We found a speed regime where lines exhibited a large polarization-controlled retardance response (up to 200 nm in LNSB), which is attributed to the texturation of the crystal/glass phase separation with a low scattering level. These characteristics are regarded as assets for future elaboration methods and designs of photonic devices involving crystallization. Finally, by using temperature and irradiation time variations along the main laser parameters (pulse energy, pulse repetition rate, scanning speed), we propose an explanation on the origin of (1) crystallization limitation upon scanning speed, (2) laser track width variation with respect to scanning speed, and (3) narrowing of the nanogratings volume but not the heat-affected volume.
Circulating miR-618 Has Prognostic Significance in Patients with Metastatic Colon Cancer
Authors: Radanova Maria , Mihaylova Galya , Mihaylova Zhasmina , Ivanova Desislava , Tasinov Oskan , Nazifova-Tasinova Neshe , Pavlov Pavel , Mirchev Milko , Conev Nikolay , Donev Ivan
Published: March 2021

The present study evaluated the prognostic role of circulating miRNA-618 in patients with metastatic colon cancer (mCC) and whether miR-618 gene rs2682818 single nucleotide polymorphisms (SNP) are associated with colon cancer susceptibility and expression levels of mature miR-618. In total, 104 patients with mCC before starting the chemotherapy were investigated. The expression status of circulating miR-618 in mCC was evaluated by quantitative PCR. TaqMan PCR assay was used for rs2682818 SNP genotyping. miR-618 was overexpressed in serum of mCC patients. Patients with high and intermediate expression of miR-618 had a significantly longer mean overall survival (OS) of 21 months than patients with low expression—16 months. In addition, multivariate Cox regression analysis confirmed the association between high/intermediate levels of miRNA-618 and longer OS, HR = 0.51, 95% CI: 0.30–0.86, p = 0.012. miR-618 rs2682818 SNP significantly decreased the risk of colon cancer susceptibility in both heterozygous codominant (AC vs. CC, OR = 0.39, 95% CI: 0.17–0.88, p = 0.024) and overdominant (AC vs. CC + AA, OR = 0.37, 95% CI: 0.16–0.85, p = 0.018) genetic models. Our data suggest that circulating miRNA-618 could be useful as a prognostic biomarker in mCC. Patients harboring AC rs2682818 genotype have a decreased risk for colon cancer in comparison with patients with CC and AA genotypes.
Long-Term Monitoring Reveals Differential Responses of Mussel and Host Fish Communities in a Biodiversity Hotspot
Authors: Sanchez Gonzalez Irene , Hopper Garrett W. , Bucholz Jamie , Atkinson Carla L.
Published: March 2021

Biodiversity hotspots can serve as protected areas that aid in species conservation. Long-term monitoring of multiple taxonomic groups within biodiversity hotspots can offer insight into factors influencing their dynamics. Mussels (Bivalvia: Unionidae) and fish are highly diverse and imperiled groups of organisms with contrasting life histories that should influence their response to ecological factors associated with local and global change. Here we use historical and contemporary fish and mussel survey data to assess fish and mussel community changes over a 33 year period (1986–2019) and relationships between mussel abundance and their host fish abundance in Bogue Chitto Creek, a tributary of the Alabama River and a biodiversity hotspot. Mussel abundance declined by ~80% and community composition shifted, with eight species previously recorded not found in 2019, and a single individual of the endangered Pleurobema decisum. Fish abundances increased and life history strategies in the community appeared stable and there was no apparent relationship between mussel declines and abundance of host fish. Temporal variation in the proportion of life history traits composing mussel assemblages was also indicative of the disturbances specifically affecting the mussel community. However, changes and declines in mussel assemblages in Bogue Chitto Creek cannot be firmly attributed to any specific factor or events because of gaps in historical environmental and biological data. We believe that mobility differences contributed to differential responses of fish and mussel communities to stressors including habitat degradation, recent droughts and invasive species. Overall, our work indicates that monitoring biodiversity hotspots using hydrological measurements, standardized survey methods and monitoring invasive species abundance would better identify the effects of multiple and interactive stressors that impact disparate taxonomic groups in freshwater ecosystems.
Endocranial Anatomy of the Giant Extinct Australian Mihirung Birds (Aves, Dromornithidae)
Authors: Handley Warren D. , Worthy Trevor H.
Published: March 2021

Dromornithids are an extinct group of large flightless birds from the Cenozoic of Australia. Their record extends from the Eocene to the late Pleistocene. Four genera and eight species are currently recognised, with diversity highest in the Miocene. Dromornithids were once considered ratites, but since the discovery of cranial elements, phylogenetic analyses have placed them near the base of the anseriforms or, most recently, resolved them as stem galliforms. In this study, we use morphometric methods to comprehensively describe dromornithid endocranial morphology for the first time, comparing Ilbandornis woodburnei and three species of Dromornis to one another and to four species of extant basal galloanseres. We reveal that major endocranial reconfiguration was associated with cranial foreshortening in a temporal series along the Dromornis lineage. Five key differences are evident between the brain morphology of Ilbandornis and Dromornis, relating to the medial wulst, the ventral eminence of the caudoventral telencephalon, and morphology of the metencephalon (cerebellum + pons). Additionally, dromornithid brains display distinctive dorsal (rostral position of the wulst), and ventral morphology (form of the maxillomandibular [V2+V3], glossopharyngeal [IX], and vagus [X] cranial nerves), supporting hypotheses that dromornithids are more closely related to basal galliforms than anseriforms. Functional interpretations suggest that dromornithids were specialised herbivores that likely possessed well-developed stereoscopic depth perception, were diurnal and targeted a soft browse trophic niche.
KazNewsDataset: Single Country Overall Digital Mass Media Publication Corpus
Authors: Yakunin Kirill , Kalimoldayev Maksat , Mukhamediev Ravil I. , Mussabayev Rustam , Barakhnin Vladimir , Kuchin Yan , Murzakhmetov Sanzhar , Buldybayev Timur , Ospanova Ulzhan , Yelis Marina , Zhumabayev Akylbek , Gopejenko Viktors , Meirambekkyzy Zhazirakhanym , Abdurazakov Alibek
Published: March 2021

Mass media is one of the most important elements influencing the information environment of society. The mass media is not only a source of information about what is happening but is often the authority that shapes the information agenda, the boundaries, and forms of discussion on socially relevant topics. A multifaceted and, where possible, quantitative assessment of mass media performance is crucial for understanding their objectivity, tone, thematic focus and, quality. The paper presents a corpus of Kazakhstan media, which contains over 4 million publications from 36 primary sources (which has at least 500 publications). The corpus also includes more than 2 million texts of Russian media for comparative analysis of publication activity of the countries, also about 4000 sections of state policy documents. The paper briefly describes the natural language processing and multiple-criteria decision-making methods, which are the algorithmic basis of the text and mass media evaluation method, and describes the results of several research cases, such as identification of propaganda, assessment of the tone of publications, calculation of the level of socially relevant negativity, comparative analysis of publication activity in the field of renewable energy. Experiments confirm the general possibility of evaluating the socially significant news, identifying texts with propagandistic content, evaluating the sentiment of publications using the topic model of the text corpus since the area under receiver operating characteristics curve (ROC AUC) values of 0.81, 0.73 and 0.93 were achieved on abovementioned tasks. The described cases do not exhaust the possibilities of thematic, tonal, dynamic, etc., analysis of the considered corpus of texts. The corpus will be interesting to researchers considering both multiple publications and mass media analysis, including comparative analysis and identification of common patterns inherent in the media of different countries.
Optimized Design of a Novel Hydraulic Propeller Turbine for Low Heads
Authors: Barsi Dario , Ubaldi Marina , Zunino Pietro , Fink Robert
Published: March 2021

In the present paper, an optimized design procedure capable of providing the geometry of a high efficiency compact hydraulic propeller turbine for low head is proposed and developed. The turbine preliminary design is based on fundamental turbomachinery mean-line equations and on the employment of statistical correlations, which relate the main geometrical parameters to the fundamental design parameters. The first obtained geometry represents the starting point of an automated aerodynamic single point optimization procedure based on a genetic algorithm generating and updating a wide database of turbine geometries. The approach employs a three-dimensional (3D) Reynolds averaged Navier–Stokes (RANS) solver for the construction of the corresponding database of performance. A meta-model, such as an artificial neural network (ANN), is used to speed up the design optimization process. The procedure has been applied on the practical case of a novel simplified hydraulic propeller turbine prototype for very low heads. The adopted design optimization procedure is able to modify the turbine blade and vane geometries in order to achieve automatically the targeted net head and the maximum for the total to total internal efficiency once diameter, mass flow rate, and rotational speed are assigned.
Quantifying the Effects of Vibration on Medicines in Transit Caused by Fixed-Wing and Multi-Copter Drones
Authors: Oakey Andrew , Waters Tim , Zhu Wanqing , Royall Paul , Cherrett Tom , Courtney Patrick , Majoe Dennis , Jelev Nickolay
Published: March 2021

The concept of transporting medical products by drone is gaining a lot of interest amongst the medical and logistics communities. Such innovation has generated several questions, a key one being the potential effects of flight on the stability of medical products. The aims of this study were to quantify the vibration present within drone flight, study its effect on the quality of the medical insulin through live flight trials, and compare the effects of vibration from drone flight with traditional road transport. Three trials took place in which insulin ampoules and mock blood stocks were transported to site and flown using industry standard packaging by a fixed-wing or a multi-copter drone. Triaxial vibration measurements were acquired, both in-flight and during road transit, from which overall levels and frequency spectra were derived. British Pharmacopeia quality tests were undertaken in which the UV spectra of the flown insulin samples were compared to controls of known turbidity. In-flight vibration levels in both the drone types exceeded road induced levels by up to a factor of three, and predominant vibration occurred at significantly higher frequencies. Flown samples gave clear insulin solutions that met the British Pharmacopoeia specification, and no aggregation of insulin was detected.
Adaptive Information Sharing with Ontological Relevance Computation for Decentralized Self-Organization Systems
Authors: Liu Wei , Ran Weizhi , Nantogma Sulemana , Xu Yang
Published: March 2021

Decentralization is a peculiar characteristic of self-organizing systems such as swarm intelligence systems, which function as complex collective responsive systems without central control and operates based on contextual local coordination among relatively simple individual systems. The decentralized particularity of self-organizing systems lies in their capacity to spontaneously respond to accommodate environmental changes in a cooperative manner without external control. However, if members cannot obtain observations of the state of the whole team and environment, they have to share their knowledge and policies with each other through communication in order to adapt to the environment appropriately. In this paper, we propose an information sharing mechanism as an independent decision phase to improve individual members’ joint adaption to the world to fulfill an optimal self-organization in general. We design the information sharing decision analogous to human information sharing mechanisms. In this case, information can be shared among individual members by evaluating the semantic relationship of information based on ontology graph and their local knowledge. That is, if individual member collects more relevant information, the information will be used to update its local knowledge and improve sharing relevant information by measuring the ontological relevance. This will enable more related information to be acquired so that their models will be reinforced for more precise information sharing. Our simulations and experimental results show that this design can share information efficiently to achieve optimal adaptive self-organizing systems.
Tracking an Auto-Regressive Process with Limited Communication per Unit Time
Authors: Jinan Rooji , Parag Parimal , Tyagi Himanshu
Published: March 2021

Samples from a high-dimensional first-order auto-regressive process generated by an independently and identically distributed random innovation sequence are observed by a sender which can communicate only finitely many bits per unit time to a receiver. The receiver seeks to form an estimate of the process value at every time instant in real-time. We consider a time-slotted communication model in a slow-sampling regime where multiple communication slots occur between two sampling instants. We propose a successive update scheme which uses communication between sampling instants to refine estimates of the latest sample and study the following question: Is it better to collect communication of multiple slots to send better refined estimates, making the receiver wait more for every refinement, or to be fast but loose and send new information in every communication opportunity? We show that the fast but loose successive update scheme with ideal spherical codes is universally optimal asymptotically for a large dimension. However, most practical quantization codes for fixed dimensions do not meet the ideal performance required for this optimality, and they typically will have a bias in the form of a fixed additive error. Interestingly, our analysis shows that the fast but loose scheme is not an optimal choice in the presence of such errors, and a judiciously chosen frequency of updates outperforms it.
Interstage Pressures of a Multistage Compressor with Intercooling
Authors: Lugo-Méndez Helen , Lopez-Arenas Teresa , Torres-Aldaco Alejandro , Torres-González Edgar Vicente , Sales-Cruz Mauricio , Lugo-Leyte Raúl
Published: March 2021

This paper considers the criterion of minimum compression work to derive an expression for the interstage pressure of a multistage compressor with intercooling that includes the gas properties, pressure drops in the intercoolers, different suction gas temperatures, and isentropic efficiencies in each compression stage. The analytical expression for the interstage pressures is applied to estimate the number of compression stages and to evaluate its applicability in order to estimate interstage pressures in the operation of multistage compressors, which can be especially useful when their measurements are not available.
An FPGA-Based LSTM Acceleration Engine for Deep Learning Frameworks
Authors: He Dazhong , He Junhua , Liu Jun , Yang Jie , Yan Qing , Yang Yang
Published: March 2021

Over the past two decades, Long Short-Term Memory (LSTM) networks have been used to solve problems that require modeling of long sequence because they can selectively remember certain patterns over a long period, thus outperforming traditional feed-forward neural networks and Recurrent Neural Network (RNN) on learning long-term dependencies. However, LSTM is characterized by feedback dependence, which limits the high parallelism of general-purpose processors such as CPU and GPU. Besides, in terms of the energy efficiency of data center applications, the high consumption of GPU and CPU computing cannot be ignored. To deal with the above problems, Field Programmable Gate Array (FPGA) is becoming an ideal alternative. FPGA has the characteristics of low power consumption and low latency, which are helpful for the acceleration and optimization of LSTM and other RNNs. This paper proposes an implementation scheme of the LSTM network acceleration engine based on FPGA and further optimizes the implementation through fixed-point arithmetic, systolic array and lookup table for nonlinear function. On this basis, for easy deployment and application, we integrate the proposed acceleration engine into Caffe, one of the most popular deep learning frameworks. Experimental results show that, compared with CPU and GPU, the FPGA-based acceleration engine can achieve performance improvement of 8.8 and 2.2 times and energy efficiency improvement of 16.9 and 9.6 times, respectively, within Caffe framework.
Stable Local Bit-Line 6 T SRAM Architecture Design for Low-Voltage Operation and Access Enhancement
Authors: Sheu Ming-Hwa , Morsalin S M Salahuddin , Tsai Chang-Ming , Yang Cheng-Jie , Hsia Shih-Chang , Hsueh Ya-Hsin , Lin Jin-Fa , Chang Chuan-Yu
Published: March 2021

To incur the memory interface and faster access of static RAM for near-threshold operation, a stable local bit-line static random-access memory (SRAM) architecture has been proposed along with the low-voltage pre-charged and negative local bit-line (NLBL) scheme. In addition to the low-voltage pre-charged and NLBL scheme being operated by the write bit-line column to work out for the write half-select condition. The proposed local bit-line SRAM design reduces variations and enhances the read stability, the write capacity, prevents the bit-line leakage current, and the designed pre-charged circuit has achieved an optimal pre-charge voltage during the near-threshold operation. Compared to the conventional 6 T SRAM design, the optimal pre-charge voltage has been improved up to 15% for the read static noise margin (RSNM) and the write delay enriched up to 22% for the proposed NLBL SRAM design which is energy-efficient. At 400 mV supply voltage and 25 MHz operating frequency, the read and write energy consumption is 0.22 pJ and 0.23 pJ respectively. After comparing with the related works, the access average energy (AAE) is lower than in other works. The overall performance for the proposed local bit-line SRAM has achieved the highest figure of merit (FoM). The designed architecture has been implemented based on the 1-Kb SRAM macros and TSMC−40 nm GP process technology.
ACIMS: Analog CIM Simulator for DNN Resilience
Authors: Ding Dong , Wang Lei , Yang Zhijie , Hu Kai , He Hongjun
Published: March 2021

Analog Computing In Memory (ACIM) combines the advantages of both Compute In Memory (CIM) and analog computing, making it suitable for the design of energy-efficient hardware accelerators for computationally intensive DNN applications. However, their use will introduce hardware faults that decrease the accuracy of DNN. In this work, we take Sandwich-Ram as the real hardware example of ACIM and are the first to propose a fault injection and fault-aware training framework for it, named Analog Computing In Memory Simulator (ACIMS). Using this framework, we can simulate and repair the hardware faults of ACIM. The experimental results show that ACIMS can recover 91.0%, 93.7% and 89.8% of the DNN’s accuracy drop through retraining on the MNIST, SVHN and Cifar-10 datasets, respectively; moreover, their adjusted accuracy can reach 97.0%, 95.3% and 92.4%.
Economic and Ecological Design of Hybrid Renewable Energy Systems Based on a Developed IWO/BSA Algorithm
Authors: Kharrich Mohammed , Kamel Salah , Ellaia Rachid , Akherraz Mohammed , Alghamdi Ali S. , Abdel-Akher Mamdouh , Eid Ahmad , Mosaad Mohamed I.
Published: March 2021

In this paper, an optimal design of a microgrid including four houses in Dakhla city (Morocco) is proposed. To make this study comprehensive and applicable to any hybrid system, each house has a different configuration of renewable energies. The configurations of these four houses are PV/wind turbine (WT)/biomass/battery, PV/biomass, PV/diesel/battery, and WT/diesel/battery systems. The comparison factor among these configurations is the cost of energy (COE), comparative index, where the load is different in the four houses. Otherwise, the main objective function is the minimization of the net present cost (NPC), subject to several operating constraints, the power loss, the power generated by the renewable sources (renewable fraction), and the availability. This objective function is achieved using a developed optimization algorithm. The main contribution of this paper is to propose and apply a new optimization technique for the optimal design of a microgrid considering different economic and ecological aspects. The developed optimization algorithm is based on the hybridization of two metaheuristic algorithms, the invasive weed optimization (IWO) and backtracking search algorithm (BSA), with the aim of collecting the advantages of both. The proposed hybrid optimization algorithm (IWO/BSA) is compared with the original two optimization methods (IWO and BSA) as well as other well-known optimization methods. The results indicate that PV/biomass and PV/diesel/battery systems have the best energy cost using the proposed IWO/BSA algorithm with 0.1184 $/kWh and 0.1354 $/kWh, respectively. The best system based on its LCOE factor is the PV/biomass which represents an NPC of 124,689 $, the size of this system is 349.55 m2 of PV area and the capacity of the biomass is 18.99 ton/year. The PV/diesel/battery option has also good results, with a system NPC of 142,233 $, the size of this system is about 391.39 m2 of PV area, rated power of diesel generator about 0.55 kW, and a battery capacity of 12.97 kWh. Otherwise, the proposed IWO/BSA has the best convergence in all cases. It is observed that the wind turbine generates more dumped power, and the PV system is highly suitable for the studied area.
Pixel P Air-Wise Fragile Image Watermarking Based on HC-Based Absolute Moment Block Truncation Coding
Authors: Lin Chia-Chen , He Si-Liang , Chang Chin-Chen
Published: March 2021

In this paper, we first designed Huffman code (HC)-based absolute moment block truncation coding (AMBTC). Then, we applied Huffman code (HC)-based absolute moment block truncation coding (AMBTC) to design a pixel pair-wise fragile image watermarking method. Pixel pair-wise tampering detection and content recovery mechanisms were collaboratively applied in the proposed scheme to enhance readability even when images have been tampered with. Representative features are derived from our proposed HC-based AMBTC compression codes of the original image, and then serve as authentication code and recovery information at the same time during tamper detection and recovery operations. Recovery information is embedded into two LSB of the original image with a turtle shell-based data hiding method and a pre-determined matrix. Therefore, each non-overlapping pixel-pair carries four bits of recovery information. When the recipient suspects that the received image may have been tampered with, the compressed image can be used to locate tampered pixels, and then the recovery information can be used to restore the tampered pixels.
Deep-Learning Forecasting Method for Electric Power Load via Attention-Based Encoder-Decoder with Bayesian Optimization
Authors: Jin Xue-Bo , Zheng Wei-Zhen , Kong Jian-Lei , Wang Xiao-Yi , Bai Yu-Ting , Su Ting-Li , Lin Seng
Published: March 2021

Short-term electrical load forecasting plays an important role in the safety, stability, and sustainability of the power production and scheduling process. An accurate prediction of power load can provide a reliable decision for power system management. To solve the limitation of the existing load forecasting methods in dealing with time-series data, causing the poor stability and non-ideal forecasting accuracy, this paper proposed an attention-based encoder-decoder network with Bayesian optimization to do the accurate short-term power load forecasting. Proposed model is based on an encoder-decoder architecture with a gated recurrent units (GRU) recurrent neural network with high robustness on time-series data modeling. The temporal attention layer focuses on the key features of input data that play a vital role in promoting the prediction accuracy for load forecasting. Finally, the Bayesian optimization method is used to confirm the model’s hyperparameters to achieve optimal predictions. The verification experiments of 24 h load forecasting with real power load data from American Electric Power (AEP) show that the proposed model outperforms other models in terms of prediction accuracy and algorithm stability, providing an effective approach for migrating time-serial power load prediction by deep-learning technology.
An Industrial Scale, Mechanical Process for Improving Pellet Quality and Biogas Production from Hazelnut and Olive Pruning
Authors: Bianchini Leonardo , Costa Paolo , Dell’Omo Pier Paolo , Colantoni Andrea , Cecchini Massimo , Monarca Danilo
Published: March 2021

The effects of a mechanical process on the solid fuel quality and anaerobic biodegradability of hazelnut and olive pruning were determined. The feedstock was treated using a two-stage dry milling process, followed by fractionation into four different products. The coarser products from the processing of both the raw materials, named C and M, were notable for the high reduction in both the ash and nitrogen content. Therefore, for hazelnut, they met the requirement of the EN ISO 17225-2 standard for both the industrial and residential pellets, whereas C and M from olive processing met the requirements only for the industrial pellet. The raw materials and the finest products from processing, named F1 and F2, were anaerobically digested in batch reactors under mesophilic conditions. The F2 product from hazelnut processing reached a methane yield of 118.1 Nm3 tVS−1, corresponding to a +70.1% gain over the untreated substrate, whereas F2 from olive pruning processing reached 176.5 Nm3 tVS−1, corresponding to a methane yield gain of about +93.5% over the untreated raw material. These results suggest that the investigated process could be successfully used to improve the quality of pruning and establish new markets for them.