bluuebunny/crossref_metadata_2025 huggingface dataset:
Identification of Transferrin Receptor 1 (TfR1) Overexpressed in Lung Cancer Cells, and Internalization of Magnetic Au-CoFe2O4 Core-Shell Nanoparticles Functionalized with Its Ligand in a Cellular Model of Small Cell Lung Cancer (SCLC)
Authors: Villalobos-Manzo Rocío , Ríos-Castro Emmanuel , Hernández-Hernández José Manuel , Oza Goldie , Medina Mauricio A. , Tapia-Ramírez José
Published: August 2022

Lung cancer is, currently, one of the main malignancies causing deaths worldwide. To date, early prognostic and diagnostic markers for small cell lung cancer (SCLC) have not been systematically and clearly identified, so most patients receive standard treatment. In the present study, we combine quantitative proteomics studies and the use of magnetic core-shell nanoparticles (mCSNP’s), first to identify a marker for lung cancer, and second to functionalize the nanoparticles and their possible application for early and timely diagnosis of this and other types of cancer. In the present study, we used label-free mass spectrometry in combination with an ion-mobility approach to identify 220 proteins with increased abundance in small cell lung cancer (SCLC) cell lines. Our attention was focused on cell receptors for their potential application as mCSNP’s targets; in this work, we report the overexpression of Transferrin Receptor (TfR1) protein, also known as Cluster of Differentiation 71 (CD71) up to a 30-fold increase with respect to the control cell. The kinetics of endocytosis, evaluated by a flow cytometry methodology based on fluorescence quantification, demonstrated that receptors were properly activated with the transferrin supported on the magnetic core-shell nanoparticles. Our results are important in obtaining essential information for monitoring the disease and/or choosing better treatments, and this finding will pave the way for future synthesis of nanoparticles including chemotherapeutic drugs for lung cancer treatments.
Hollow Mesoporous CeO2-Based Nanoenzymes Fabrication for Effective Synergistic Eradication of Malignant Breast Cancer via Photothermal–Chemodynamic Therapy
Authors: Tan Huaxin , Li Yongzhen , Ma Jiaying , Wang Peiyuan , Chen Qiaoling , Hu Lidan
Published: August 2022

CeO2-based nanoenzymes present a very promising paradigm in cancerous therapy, as H2O2 can be effectively decomposed under the electron transmit between Ce3+ and Ce4+. However, the limitations of endogenous H2O2 and intracellular low Fenton-like reaction rate lead to single unsatisfied chemodynamic therapy (CDT) efficacy. Other therapeutic modalities combined with chemodynamic therapy are generally used to enhance the tumor eradiation efficacy. Here, we have synthesized a novel hollow pH-sensitive CeO2 nanoenzyme after a cavity is loaded with indocyanine green (ICG), as well as with surface modification of tumor targeting peptides, Arg-Gly-Asp (denoted as HCeO2@ICG-RGD), to successfully target tumor cells via αvβ3 recognition. Importantly, in comparison with single chemodynamic therapy, a large amount of reactive oxygen species in cytoplasm were induced by enhanced chemodynamic therapy with photothermal therapy (PTT). Furthermore, tumor cells were efficiently killed by a combination of photothermal and chemodynamic therapy, revealing that synergistic therapy was successfully constructed. This is mainly due to the precise delivery of ICG and release after HCeO2 decomposition in cytoplasm, in which effective hyperthermia generation was found under 808 nm laser irradiation. Meanwhile, our HCeO2@ICG-RGD can act as a fluorescent imaging contrast agent for an evaluation of tumor tissue targeting capability in vivo. Finally, we found that almost all tumors in HCeO2@ICG-RGD+laser groups were completely eradicated in breast cancer bearing mice, further proving the effective synergistic effect in vivo. Therefore, our novel CeO2-based PTT agents provide a proof-of-concept argumentation of tumor-precise multi-mode therapies in preclinical applications.
Beyond Formulation: Contributions of Nanotechnology for Translation of Anticancer Natural Products into New Drugs
Authors: Miguel Rodrigo dos A. , Hirata Amanda S. , Jimenez Paula C. , Lopes Luciana B. , Costa-Lotufo Leticia V.
Published: August 2022

Nature is the largest pharmacy in the world. Doxorubicin (DOX) and paclitaxel (PTX) are two examples of natural-product-derived drugs employed as first-line treatment of various cancer types due to their broad mechanisms of action. These drugs are marketed as conventional and nanotechnology-based formulations, which is quite curious since the research and development (R&D) course of nanoformulations are even more expensive and prone to failure than the conventional ones. Nonetheless, nanosystems are cost-effective and represent both novel and safer dosage forms with fewer side effects due to modification of pharmacokinetic properties and tissue targeting. In addition, nanotechnology-based drugs can contribute to dose modulation, reversion of multidrug resistance, and protection from degradation and early clearance; can influence the mechanism of action; and can enable drug administration by alternative routes and co-encapsulation of multiple active agents for combined chemotherapy. In this review, we discuss the contribution of nanotechnology as an enabling technology taking the clinical use of DOX and PTX as examples. We also present other nanoformulations approved for clinical practice containing different anticancer natural-product-derived drugs.
Primary Care Wound Clinics: A Qualitative Descriptive Study of Patient Experiences in Community Pharmacies
Authors: Sheehan Lusi , Dias Sheldon , Joseph Michael , Mungroo Sahil , Pantinople Jake , Lee Kenneth
Published: August 2022

The expansion of primary care wound services serves to alleviate secondary and tertiary care utilization. However, patient satisfaction is required to ensure service uptake. In recent years, various community pharmacies in Australia have begun to offer dedicated wound clinics; however, evaluations of patient experiences have yet to be conducted. Thus, the present study seeks to explore: (1) the experiences and satisfaction of patients who have received wound care consultations for their acute wounds in a community pharmacy setting; and (2) how current pharmacy-based wound services can be improved. Semi-structured individual interviews were conducted with patients across five pharmacy-based wound care clinics in Western Australia. Interviews were audio-recorded, transcribed verbatim, and imported into QSR NVivo 12 Plus. Interview transcripts were coded and thematically analyzed using the framework method. Twelve interviews were required to reach data saturation. Five key themes emerged: the accessibility of wound services, the comprehensiveness of wound care services, confidence in wound care consultants, the awareness and promotion of wound services, and the expansion of wound care services. Overall, participants were satisfied with the accessibility and comprehensiveness of pharmacy-based wound service delivery, trusted the health care providers, and wanted the service to be expanded. The reported patient satisfaction, confidence in the health care provider, and desire to expand the service suggests there is potential for the service to grow in Australia. Due to the growing costs of wound care globally, there is scope to further evaluate and expand wound care services in the primary care setting on an international level.
Pathophysiology of Placenta in Antiphospholipid Syndrome
Authors: Bobircă Anca , Dumitrache Ana , Alexandru Cristina , Florescu Anca , Ciobotaru George , Bobircă Florin , Sima Romina-Marina , Poalelungi Cristian , Bojincă Mihai , Ancuța Ioan
Published: August 2022

Antiphospholipid syndrome (APS) is an autoimmune disorder characterized by clinical manifestations caused by arterial or venous thrombosis and pregnancy conditions such as recurrent miscarriage, fetal death, or premature birth in the presence of antiphospholipid antibodies. The obstetrical manifestations are strongly related to the placental alterations. The aim of this review is to summarize the latest data on pathophysiology of obstetrical APS, emphasizing the disturbance of the placentation process. Due to a lack of extravillous trophoblasts to properly reconstruct the spiral arteries, APS causes hypoxic or ischemic injury or high-speed blood flow that damages the placenta. This results in decreased or interrupted maternal blood flow to the placenta and a lack of nutrients for the fetus. Antiphospholipid antibodies can lower the proliferation and infiltration of the extravillous trophoblasts. The placental mal-perfusion causes the release of antiangiogenic substances such as soluble fms-like tyrosine kinase-1 and soluble endoglin. Placental growth factor and vascular endothelial growth factor (VEGF) may be sequestered by sFlt1 and blocked from binding to trophoblast and endothelial cell VEGF receptors, inhibiting their proangiogenic effects. Preeclampsia is the clinical result from a lack of angiogenic factors needed for endothelial vascular homeostasis due to an excess of sFlt1 in the maternal circulation.
Study on Shearing Behavior of Circular Concrete-Filled CFRP (Carbon Fiber-Reinforced Plastics)-Steel Tube
Authors: Wang Qingli , Liu Xiaokang , Peng Kuan
Published: August 2022

Concrete-filled CFRP steel tube (CF-CFRP-ST) structures often suffer from shear loading in practical engineering, such as joints with diagonal braces. To study the shear properties of CF-CFRP-ST, we take the concrete strength and the longitudinal CFRP layers as the main parameters, and static shear tests of overall 9 circular concrete-filled CFRP-steel tube (C-CF-CFRP-ST) and 3 circular concrete-filled steel tube (C-CFST) are carried out. The research is carried out from two aspects: experiment and finite element. The experimental results show that the shear loading-displacement curves of the specimens can be divided into elastic stage, strengthening stage, and softening stage. The increases of the strength of the concrete and the layers of the transverse CFRP can both enhance the shearing load carrying capacity of the specimen. With the increase of concrete strength, there is no obvious change in the shape of the shear stress-shear strain curves of the specimens, and the shear stress and the stiffness of the curve in the elastic stage of the specimen are slightly increased. The shear loading-displacement curves of the specimens are simulated by using finite element software ABAQUS and it is found that the predicted results agree reasonably well with the test results. Then, the whole process of loading and the parameters of the main influencing factors are analyzed. Finally, the calculation equation of CFRP concrete-filled steel tubular shear capacity is established.
Preparation and Characterization of Graphene Oxide/Polyaniline/Polydopamine Nanocomposites towards Long-Term Anticorrosive Performance of Epoxy Coatings
Authors: Huang Yunyun , Zhang Borui , Wu Jian , Hong Ruoyu , Xu Jinjia
Published: August 2022

To address the challenging issues of metal materials corrosion in industries, which has caused huge economic losses and security threats to many facilities in marine environments, functional polymer coatings have been widely used and regarded as one of the simplest and most effective methods to prevent such an undesirable event. In this study, a new type of coating filler consisting of graphene oxide/polyaniline/polydopamine (GO-PANI-PDA) nanocomposites has been successfully synthesized. The morphology, structure, composition, and corrosion resistance performance of the GO-PANI-PDA (GPP) nanocomposites were investigated via a series of characterization methods. The results from our electrochemical impedance spectroscopy, potentiodynamic polarization curve and salt spray experiment showed that the best corrosion resistance performance of the coating is from GPP 21 with the epoxy/GO-PANI:PDA ratio of 2:1, which exhibited a positive corrosion potential (−0.51 V) shift from epoxy/GO-PANI coating (−0.64 V). The corrosion current density (3.83 × 10−8 A/cm2) of GPP 21 is nearly an order of magnitude lower than that of epoxy/GO-PANI (7.05 × 10−7 A/cm2). The good anti-corrosion performance was fascinatingly observed in salt spray tests even without obvious corrosion phenomenon after 30 days of testing. Due to these remarkable properties, GPP nanocomposites can be an outstanding candidate for the rapid development of broadband shielding and anticorrosive materials.
Study on the Effect of Processing Parameters on Residual Stresses of Injection Molded Micro-Pillar Array
Authors: Zhang Xiaoyu , Ding Tao , Wang Wanlin , Liu Jiezhen , Weng Can
Published: August 2022

As one of the main methods for fabricating microstructured surfaces, micro-injection molding has the advantages of short cycle time, high production efficiency, and the potential for batch manufacturing. However, non-negligible residual stresses inside the molded part could affect the replication quality, dimensions, and physical properties of the microstructure. Therefore, studying the effects of processing parameters on residual stresses is a necessary prerequisite to ensure the successful fabrication of microstructured parts. In this paper, an injection molding simulation model of micro-pillar arrays was developed using molecular dynamics software, and a series of injection molding experiments were conducted. It was found that increasing the mold temperature and melt temperature can reduce the thermal residual stresses and molecular orientation stresses, and effectively improve the uniformity of residual stress distribution. The increase in the packing pressure can make the shear field of flow more intense and increase the molecular orientation stresses, thus making the residual stresses more severe.
Natural Ageing of PLA Filaments, Can It Be Frozen?
Authors: Orellana-Barrasa Jaime , Ferrández-Montero Ana , Ferrari Begoña , Pastor José Ygnacio
Published: August 2022

The physical ageing of polylactic acid (PLA) is a phenomenon that changes the material’s properties over time. This ageing process is highly dependent on ambient variables, such as temperature and humidity. For PLA, the ageing is noticeable even at room temperatures, a process commonly referred to as natural ageing. Stopping the ageing by freezing the material can be helpful to preserve the properties of the PLA and stabilise it at any time during its storage until it is required for testing. However, it is essential to demonstrate that the PLA’s mechanical properties are not degraded after defrosting the samples. Four different methods for stopping the ageing (anti-ageing processes) are analysed in this paper—all based on freezing and defrosting the PLA samples. We determine the temperature and ambient water vapor influence during the freezing and defrosting process using desiccant and zip bags. The material form selected is PLA filaments (no bulk material or scaffold structures) printed at 190 °C with diameters between 400 and 550 µm and frozen at −24 °C in the presence or absence of a desiccant. The impact of the anti-ageing processes on PLA’s ageing and mechanical integrity is studied regarding the thermal, mechanical and fractographical properties. In conclusion, an anti-ageing process is defined to successfully stop the natural ageing of the PLA for an indefinite length of time. This process does not affect the mechanical properties or the structural integrity of the PLA. As a result, large quantities of this material can be produced in a single batch and be safely stored to be later characterised under the same manufacturing and ageing conditions, which is currently a limiting factor from an experimental point of view as polymeric filament properties can show significant variety from batch to batch.
Adsorption Behavior of Methylene Blue Cationic Dye in Aqueous Solution Using Polypyrrole-Polyethylenimine Nano-Adsorbent
Authors: Birniwa Abdullahi Haruna , Mahmud Habibun Nabi Muhammad Ekramul , Abdullahi Shehu Sa’ad , Habibu Shehu , Jagaba Ahmad Hussaini , Ibrahim Mohamad Nasir Mohamad , Ahmad Akil , Alshammari Mohammed B. , Parveen Tabassum , Umar Khalid
Published: August 2022

In this work, a polypyrrole-polyethyleneimine (PPy-PEI) nano-adsorbent was successfully synthesized for the removal of methylene blue (MB) from an aqueous solution. Synthetic dyes are among the most prevalent environmental contaminants. A new conducting polymer-based adsorbent called (PPy-PEI) was successfully produced using ammonium persulfate as an oxidant. The PEI hyper-branched polymer with terminal amino groups was added to the PPy adsorbent to provide more effective chelating sites for dyes. An efficient dye removal from an aqueous solution was demonstrated using a batch equilibrium technique that included a polyethyleneimine nano-adsorbent (PPy-PEI). The best adsorption parameters were measured at a 0.35 g dosage of adsorbent at a pH of 6.2 and a contact period of 40 min at room temperature. The produced PPy-PEI nano-adsorbent has an average particle size of 25–60 nm and a BET surface area of 17 m2/g. The results revealed that PPy-PEI nano-composite was synthesized, and adsorption was accomplished in the minimum amount of time. The maximum monolayer power, qmax, for MB was calculated using the isothermal adsorption data, which matched the Langmuir isotherm model, and the kinetic adsorption data, which more closely fitted the Langmuir pseudo-second-order kinetic model. The Langmuir model was used to calculate the maximum monolayer capacity, or qmax, for MB, which was found to be 183.3 mg g−1. The as-prepared PPy-PEI nano-adsorbent totally removes the cationic dyes from the aqueous solution.
Efficient OLEDs Based on Slot-Die-Coated Multicomponent Emissive Layer
Authors: Witkowska Ewelina , Glowacki Ireneusz , Ke Tung-Huei , Malinowski Pawel , Heremans Paul
Published: August 2022

The optimization of multicomponent emissive layer (EML) deposition by slot-die coating for organic light-emitting diodes (OLEDs) is presented. In the investigated EMLs, the yellow-green iridium complex (Ir) was doped in two types of host: a commonly used mixture of poly(N-vinylcarbazole) (PVK) with oxadiazole derivative (PBD) or PVK with thermally activated delayed fluorescence-assisted dopant (10-(4-(4,6-diphenyl-1,3,5-triazin-2-yl)phenyl)-10H-spiro[acridine-9,9′-fluorene], SpiroAC-TRZ). In this article, OLEDs with EML prepared in air by slot-die coating, facilitating industrial manufacturing, are confronted with those with spin-coated EML in nitrogen. OLEDs based on PVK:PBD + 2 wt.% Ir-dopant exhibit comparable performance: ~13 cd A−1, regardless of the used method. The highest current efficiency (21 cd A−1) is shown by OLEDs based on spin-coated PVK with 25 wt.% SpiroAC-TRZ and 2 wt.% Ir-dopant. It is three times higher than the efficiency of OLEDs with slot-die-coated EML in air. The performance reduction, connected with the adverse oxygen effect on the energy transfer from TADF to emitter molecules, is minimized by the rapid EML annealing in a nitrogen atmosphere. This post-treatment causes more than a doubling of the OLED efficiency, from 7 cd A−1 to over 15 cd A−1. Such an approach may be easily implemented in other printing techniques and result in a yield enhancement.
Molecular Dynamics Study on the Adsorption and Modification Mechanism of Polymeric Sand-Fixing Agent
Authors: Huang Wei , Geng Xueyu , Li Jing , Zhou Cuiying , Liu Zhen
Published: August 2022

Chemical sand-fixing technology has shown good potential in preventing desertification, but the effect is determined by materials. In this paper, the adsorption behavior of quartz and six common polymer sand-fixing agents under dry conditions was studied by molecular dynamics method. The results show that all polymers could be adsorbed on the surface of quartz and their functional groups play an important role in the adsorption process. Compared with other materials, the binding energy and the number of hydrogen bonds of PAA-quartz composites were improved by 30.7–65.6% and 8.3–333.3%, respectively. It was found that the number of hydrogen bonds formed under the unit molecular was positively correlated with the mechanical properties of the improved sandy soil. This study provides an accurate, efficient and inexpensive qualitative evaluation method for the curing effect of sand fixers, which will assist in the screening and development of new high performance sand fixers.
Qian Xuexi and William Empson’s Discussion of Arthur Waley’s English Translation of the Daodejing
Authors: Yao Dadui
Published: August 2022

Between June and August 1947, Qian Xuexi and William Empson exchanged 12 letters on the issue of Arthur Waley’s misinterpretation of the Daodejing. Through a thorough analysis of these new-found letters and Qian’s English translation of the Daodejing, I intended to show that the central arguments between Qian and Empson are around two major problems concerning Waley’s translation: Waley’s ideas of the Daodejing being part of the “Yoga-Quietism” tradition that Waley himself tried to invent, and Waley’s idea of opposing Daoism to Legalism. Qian firmly rejected that the ideas in the Daodejing were the same as some Western ideas. Neither did he accept that the ideas of the Daodejing were under the influence of either Western culture or Indian religious philosophy. Instead, Qian explained that the so-called “Yoga-Quietism” did not derive from China. Therefore, in his view, Waley’s approach was fundamentally problematic. Qian’s view eventually convinced Empson, who initially opposed Qian’s stance. Qian and Empson’s letters and Qian’s English translation of the Daodejing, though never published, indicate the value of Qian’s ideas and the meaning of their intellectual interaction.
17-α Hydroxyprogesterone Caproate Immunology, a Special Focus on Preterm Labor, Preeclampsia, and COVID-19
Authors: Al-Lami Rasha A.
Published: August 2022

17-α hydroxyprogesterone caproate (17-OHPC) could alter the immune response and inflammation, specifically affecting the risk of preterm labor and preeclampsia. However, the exact immune and inflammatory effects of 17-OHPC remain hard to be identified. The current literature on 17-OHPC immune effects is limited and more research is needed to identify these mechanistic pathways. Further, coronavirus disease 2019 (COVID-19) infection in pregnancy involves heightened immune response, widespread inflammation and high rates of preterm labor and preeclampsia. Since the pathogenesis of preterm labor, preeclampsia and COVID-19 involves inflammation and altered immune response, it is important to explore the possible immune effects of 17-OHPC in pregnant women with COVID-19. This commentary article will explain the immune effects of 17-OHPC and their implications in preterm labor, preeclampsia and COVID-19.
Digital Outcrop Model Generation from Hybrid UAV and Panoramic Imaging Systems
Authors: Aires Alysson Soares , Marques Junior Ademir , Zanotta Daniel Capella , Spigolon André Luiz Durante , Veronez Mauricio Roberto , Gonzaga Luiz
Published: August 2022

The study of outcrops in geosciences is being significantly improved by the enhancement of technologies that aims to build digital outcrop models (DOMs). Usually, the virtual environment is built by a collection of partially overlapped photographs taken from diverse perspectives, frequently using unmanned aerial vehicles (UAV). However, in situations including very steep features or even sub-vertical patterns, incomplete coverage of objects is expected. This work proposes an integration framework that uses terrestrial spherical panoramic images (SPI), acquired by omnidirectional fusion camera, and a UAV survey to overcome gaps left by traditional mapping in complex natural structures, such as outcrops. The omnidirectional fusion camera produces wider field of view images from different perspectives, which are able to considerably improve the representation of the DOM, mainly where the UAV has geometric view restrictions. We designed controlled experiments to guarantee the equivalent performance of SPI compared with UAV. The adaptive integration is accomplished through an optimized selective strategy based on an octree framework. The quality of the 3D model generated using this approach was assessed by quantitative and qualitative indicators. The results show the potential of generating a more reliable 3D model using SPI allied with UAV image data while reducing field survey time and complexity.
Thirty-Four-Year Record (1987–2021) of the Spatiotemporal Dynamics of Algal Blooms in Lake Dianchi from Multi-Source Remote Sensing Insights
Authors: Ma Jinge , He Feng , Qi Tianci , Sun Zhe , Shen Ming , Cao Zhigang , Meng Di , Duan Hongtao , Luo Juhua
Published: August 2022

Lake Dianchi is one of the most eutrophic lakes in China. The decline in water quality and the occurrence of massive algal blooms pose a significant threat to the health and environmental safety of the water ecosystem, making Lake Dianchi a key concern for algal bloom management in China. Obtaining the spatiotemporal dynamics of algal blooms for the longest time possible is crucial to algal bloom management and future prediction. However, it is difficult to acquire a long-term record of algal blooms from a single sensor in order to cover a more extended period of eutrophication in the lake due to the limitation of the spatial and temporal resolution of the sensors. In this study, Landsat and Moderate-Resolution Imaging Spectroradiometer (MODIS) images were combined with the Floating Algae Index (FAI) to reconstruct a unified time series of bloom areas to analyze the algal bloom dynamics in Lake Dianchi in recent decades. Regarding the interannual variation, the bloom area showed an increasing trend from 1987 to 2021, with larger bloom areas in 1991–1992, 2000–2003, 2012–2013, and 2020–2021. In terms of seasonal characteristics, the bloom area was significantly more prominent in the rainy season compared with the dry season during the year. The spatial distribution of the bloom frequency showed a pattern of higher frequencies in the north and lower frequencies in the south. From 2000 to 2021, the initial bloom time and bloom duration showed a trend of delaying and then advancing and decreasing and then increasing, respectively. We analyzed the importance of long-term records of algal blooms and found that the percentage of rainy season images is an essential factor in reconstructing time series based on different sensors. In addition, the relationship between environmental factors and algal blooms was analyzed. The results show that wind speed and air temperature were the main meteorological factors controlling the interannual variation in algal blooms in Lake Dianchi. Water quality factors such as nutrients have less of an influence on the variation in algal blooms because the algal growth demand has been met. Environmental management measures taken by local governments have led to improvements in the lake’s trophic state, and continued strengthening of environmental pollution control is expected to curb the algal blooms in Lake Dianchi. This study provides a long-term record of algal blooms in Lake Dianchi, which provides essential reference information for a comprehensive understanding of the development process of algal blooms in Lake Dianchi and its sustainable development.
Interpreting Sentinel-1 SAR Backscatter Signals of Snowpack Surface Melt/Freeze, Warming, and Ripening, through Field Measurements and Physically-Based SnowModel
Authors: Lund Jewell , Forster Richard R. , Deeb Elias J. , Liston Glen E. , Skiles S. McKenzie , Marshall Hans-Peter
Published: August 2022

The transition of a cold winter snowpack to one that is ripe and contributing to runoff is crucial to gauge for water resource management, but is highly variable in space and time. Snow surface melt/freeze cycles, associated with diurnal fluctuations in radiative inputs, are hallmarks of this transition. C-band synthetic aperture radar (SAR) reliably detects meltwater in the snowpack. Sentinel-1 (S1) C-band SAR offers consistent acquisition patterns that allow for diurnal investigations of melting snow. We used over 50 snow pit observations from 2020 in Grand Mesa, Colorado, USA, to track temperature and wetness in the snowpack as a function of depth and time during snowpack phases of warming, ripening, and runoff. We also ran the physically-based SnowModel, which provided a spatially and temporally continuous independent indication of snowpack conditions. Snowpack phases were identified and corroborated by comparing field measurements with SnowModel outputs. Knowledge of snowpack warming, ripening, and runoff phases was used to interpret diurnal changes in S1 backscatter values. Both field measurements and SnowModel simulations suggested that S1 SAR was not sensitive to the initial snowpack warming phase on Grand Mesa. In the ripening and runoff phases, the diurnal cycle in S1 SAR co-polarized backscatter was affected by both surface melt/freeze as well as the conditions of the snowpack underneath (ripening or ripe). The ripening phase was associated with significant increases in morning backscatter values, likely due to volume scattering from surface melt/freeze crusts, as well as significant decreases in evening backscatter values associated with snowmelt. During the runoff phase, both morning and evening backscatter decreased compared to reference values. These unique S1 diurnal signatures, and their interpretations using field measurements and SnowModel outputs, highlight the capacities and limitations of S1 SAR to understand snow surface states and bulk phases, which may offer runoff forecasting or energy balance model validation or parameterization, especially useful in remote or sparsely-gauged alpine basins.
Temporally-Consistent Annual Land Cover from Landsat Time Series in the Southern Cone of South America
Authors: Graesser Jordan , Stanimirova Radost , Tarrio Katelyn , Copati Esteban J. , Volante José N. , Verón Santiago R. , Banchero Santiago , Elena Hernan , Abelleyra Diego de , Friedl Mark A.
Published: August 2022

The impact of land cover change across the planet continues to necessitate accurate methods to detect and monitor evolving processes from satellite imagery. In this context, regional and global land cover mapping over time has largely treated time as independent and addressed temporal map consistency as a post-classification endeavor. However, we argue that time can be better modeled as codependent during the model classification stage to produce more consistent land cover estimates over long time periods and gradual change events. To produce temporally-dependent land cover estimates—meaning land cover is predicted over time in connected sequences as opposed to predictions made for a given time period without consideration of past land cover—we use structured learning with conditional random fields (CRFs), coupled with a land cover augmentation method to produce time series training data and bi-weekly Landsat imagery over 20 years (1999–2018) across the Southern Cone region of South America. A CRF accounts for the natural dependencies of land change processes. As a result, it is able to produce land cover estimates over time that better reflect real change and stability by reducing pixel-level annual noise. Using CRF, we produced a twenty-year dataset of land cover over the region, depicting key change processes such as cropland expansion and tree cover loss at the Landsat scale. The augmentation and CRF approach introduced here provides a more temporally consistent land cover product over traditional mapping methods.
Hierarchical Analysis Process for Belief Management in Internet of Drones
Authors: Gharrad Hana , Jabeur Nafaâ , Yasar Ansar Ul-Haque
Published: August 2022

Group awareness is playing a major role in the efficiency of mission planning and decision-making processes, particularly those involving spatially distributed collaborative entities. The performance of this concept has remarkably increased with the advent of the Internet of Things (IoT). Indeed, a myriad of innovative devices are being extensively deployed to collaboratively recognize and track events, objects, and activities of interest. A wide range of IoT-based approaches have focused on representing and managing shared information through formal operators for group awareness. However, despite their proven results, these approaches are still refrained by the inaccuracy of information being shared between the collaborating distributed entities. In order to address this issue, we propose in this paper a new belief-management-based model for a collaborative Internet of Drones (IoD). The proposed model allows drones to decide the most appropriate operators to apply in order to manage the uncertainty of perceived or received information in different situations. This model uses Hierarchical Analysis Process (AHP) with Subjective Logic (SL) to represent and combine opinions of different sources. We focus on purely collaborative drone networks where the group awareness will also be provided as service to collaborating entities.
Brain Decoding of Multiple Subjects for Estimating Visual Information Based on a Probabilistic Generative Model
Authors: Higashi Takaaki , Maeda Keisuke , Ogawa Takahiro , Haseyama Miki
Published: August 2022

Brain decoding is a process of decoding human cognitive contents from brain activities. However, improving the accuracy of brain decoding remains difficult due to the unique characteristics of the brain, such as the small sample size and high dimensionality of brain activities. Therefore, this paper proposes a method that effectively uses multi-subject brain activities to improve brain decoding accuracy. Specifically, we distinguish between the shared information common to multi-subject brain activities and the individual information based on each subject’s brain activities, and both types of information are used to decode human visual cognition. Both types of information are extracted as features belonging to a latent space using a probabilistic generative model. In the experiment, an publicly available dataset and five subjects were used, and the estimation accuracy was validated on the basis of a confidence score ranging from 0 to 1, and a large value indicates superiority. The proposed method achieved a confidence score of 0.867 for the best subject and an average of 0.813 for the five subjects, which was the best compared to other methods. The experimental results show that the proposed method can accurately decode visual cognition compared with other existing methods in which the shared information is not distinguished from the individual information.
Investigating Wrist-Based Acceleration Summary Measures across Different Sample Rates towards 24-Hour Physical Activity and Sleep Profile Assessment
Authors: Tsanas Athanasios
Published: August 2022

Wrist-worn wearable sensors have attracted considerable research interest because of their potential in providing continuous, longitudinal, non-invasive measurements, leading to insights into Physical Activity (PA), sleep, and circadian variability. Three key practical considerations for research-grade wearables are as follows: (a) choosing an appropriate sample rate, (b) summarizing raw three-dimensional accelerometry data for further processing (accelerometry summary measures), and (c) accurately estimating PA levels and sleep towards understanding participants’ 24-hour profiles. We used the CAPTURE-24 dataset, where 148 participants concurrently wore a wrist-worn three-dimensional accelerometer and a wearable camera over approximately 24 h to obtain minute-by-minute labels: sleep; and sedentary light, moderate, and vigorous PA. We propose a new acceleration summary measure, the Rate of Change Acceleration Movement (ROCAM), and compare its performance against three established approaches summarizing three-dimensional acceleration data towards replicating the minute-by-minute labels. Moreover, we compare findings where the acceleration data was sampled at 10, 25, 50, and 100 Hz. We demonstrate the competitive advantage of ROCAM towards estimating the five labels (80.2% accuracy) and building 24-hour profiles where the sample rate of 10 Hz is fully sufficient. Collectively, these findings provide insights facilitating the deployment of large-scale longitudinal actigraphy data processing towards 24-hour PA and sleep-profile assessment.
How Does Added Mass Affect the Gait of Middle-Aged Adults? An Assessment Using Statistical Parametric Mapping
Authors: Vijayan Vinayak , Fang Shanpu , Reissman Timothy , Reissman Megan E. , Kinney Allison L.
Published: August 2022

To improve exoskeleton designs, it is crucial to understand the effects of the placement of such added mass on a broad spectrum of users. Most prior studies on the effects of added mass on gait have analyzed young adults using discrete point analysis. This study quantifies the changes in gait characteristics of young and middle-aged adults in response to added mass across the whole gait cycle using statistical parametric mapping. Fourteen middle-aged and fourteen younger adults walked during 60 s treadmill trials under nine different loading conditions. The conditions represented full-factorial combinations of low (+3.6 lb), medium (+5.4 lb), and high (+10.8 lb) mass amounts at the thighs and pelvis. Joint kinematics, kinetics and muscle activations were evaluated. The young and middle-aged adults had different responses to added mass. Under pelvis loading, middle-aged adults did not adopt the same kinematic responses as younger adults. With thigh loading, middle-aged adults generally increased knee joint muscle activity around heel strike, which could have a negative impact on joint loading. Overall, as age may impact the user’s response to an exoskeleton, designers should aim to include sensors to directly monitor user response and adaptive control approaches that account for these differences.
Road-Scene Parsing Based on Attentional Prototype-Matching
Authors: Chen Xiaoyu , Wang Chuan , Lu Jun , Bai Lianfa , Han Jing
Published: August 2022

Road-scene parsing is complex and changeable; the interferences in the background destroy the visual structure in the image data, increasing the difficulty of target detection. The key to addressing road-scene parsing is to amplify the feature differences between the targets, as well as those between the targets and the background. This paper proposes a novel scene-parsing network, Attentional Prototype-Matching Network (APMNet), to segment targets by matching candidate features with target prototypes regressed from labeled road-scene data. To obtain reliable target prototypes, we designed the Sample-Selection and the Class-Repellence Algorithm in the prototype-regression progress. Also, we built the class-to-class and target-to-background attention mechanisms to increase feature recognizability based on the target’s visual characteristics and spatial-target distribution. Experiments conducted on two road-scene datasets, CamVid and Cityscapes, demonstrate that our approach effectively improves the representation of targets and achieves impressive results compared with other approaches.
AtAwAR Translate: Attention-Aware Language Translation Application in Augmented Reality for Mobile Phones
Authors: Vortmann Lisa-Marie , Weidenbach Pascal , Putze Felix
Published: August 2022

As lightweight, low-cost EEG headsets emerge, the feasibility of consumer-oriented brain–computer interfaces (BCI) increases. The combination of portable smartphones and easy-to-use EEG dry electrode headbands offers intriguing new applications and methods of human–computer interaction. In previous research, augmented reality (AR) scenarios have been identified to profit from additional user state information—such as that provided by a BCI. In this work, we implemented a system that integrates user attentional state awareness into a smartphone application for an AR written language translator. The attentional state of the user is classified in terms of internally and externally directed attention by using the Muse 2 electroencephalography headband with four frontal electrodes. The classification results are used to adapt the behavior of the translation app, which uses the smartphone’s camera to display translated text as augmented reality elements. We present the first mobile BCI system that uses a smartphone and a low-cost EEG device with few electrodes to provide attention awareness to an AR application. Our case study with 12 participants did not fully support the assumption that the BCI improves usability. However, we are able to show that the classification accuracy and ease of setup are promising paths toward mobile consumer-oriented BCI usage. For future studies, other use cases, applications, and adaptations will be tested for this setup to explore the usability.
Examining the Suitability of NetFlow Features in Detecting IoT Network Intrusions
Authors: Awad Mohammed , Fraihat Salam , Salameh Khouloud , Al Redhaei Aneesa
Published: August 2022

The past few years have witnessed a substantial increase in cyberattacks on Internet of Things (IoT) devices and their networks. Such attacks pose a significant threat to organizational security and user privacy. Utilizing Machine Learning (ML) in Intrusion Detection Systems (NIDS) has proven advantageous in countering novel zero-day attacks. However, the performance of such systems relies on several factors, one of which is prediction time. Processing speed in anomaly-based NIDS depends on a few elements, including the number of features fed to the ML model. NetFlow, a networking industry-standard protocol, offers many features that can be used to predict malicious attacks accurately. This paper examines NetFlow features and assesses their suitability in classifying network traffic. Our paper presents a model that detects attacks with (98–100%) accuracy using as few as 13 features. This study was conducted using a large dataset of over 16 million records released in 2021.
A Variable Kinematic Multifield Model for the Lamb Wave Propagation Analysis in Smart Panels
Authors: Najd Jamal , Zappino Enrico , Carrera Erasmo , Harizi Walid , Aboura Zoheir
Published: August 2022

The present paper assessed the use of variable kinematic two-dimensional elements in the dynamic analysis of Lamb waves propagation in an isotropic plate with piezo-patches. The multi-field finite element model used in this work was based on the Carrera Unified Formulation which offers a versatile application enabling the model to apply the desired order theory. The used variable kinematic model allowed for the kinematic model to vary in space, thereby providing the possibility to implement a classical plate model in collaboration with a refined kinematic model in selected areas where higher order kinematics are needed. The propagation of the symmetric (S0) and the antisymmetric (A0) fundamental lamb waves in an isotropic strip was considered in both mechanical and piezo-elastic plate models. The convergence of the models was discussed for different kinematics approaches, under different mesh refinement, and under different time steps. The results were compared to the exact solution proposed in the literature in order to assess and further determine the effects of the different parameters used when dynamically modeling a Lamb wave propagating in such material. It was shown that the higher order kinematic models delivered a higher accuracy of the propagating wave evaluated using the corresponding Time Of Flight (TOF). Upon using the appropriate mesh refinement of 2000 elements and sufficient time steps of 4000 steps, the error between the TOF obtained analytically and numerically using a high order kinematics was found to be less than 1% for both types of fundamental Lamb waves S0 and A0. Node-dependent kinematics models were also exploited in wave propagation to decrease the computational cost and to study their effect on the accuracy of the obtained results. The obtained results show, in both the mechanical and the piezo-electric models, that a reduction in the computational cost of up to 50% can be easily attained using such models while maintaining an error inferior to 1%.
Combined Feature Extraction and Random Forest for Laser Self-Mixing Vibration Measurement without Determining Feedback Intensity
Authors: Liang Hongwei , Chen Minghu , Jiang Chunlei , Kan Lingling , Shao Keyong
Published: August 2022

To measure the vibration of a target by laser self-mixing interference (SMI), we propose a method that combines feature extraction and random forest (RF) without determining the feedback strength (C). First, the temporal, spectral, and statistical features of the SMI signal are extracted to characterize the original SMI signal. Secondly, these interpretable features are fed into the pretrained RF model to directly predict the amplitude and frequency (A and f) of the vibrating target, recovering the periodic vibration of the target. The results show that the combination of RF and feature extraction yields a fit of more than 0.94 for simple and quick measurement of A and f of unsmooth planar vibrations, regardless of the feedback intensity and the misalignment of the retromirror. Without a complex optical stage, this method can quickly recover arbitrary periodic vibrations from SMI signals without C, which provides a novel method for quickly implementing vibration measurements.
Development and Validation of a Sensitive HPLC Assay for Determination of Sparfloxacin According to the European Medicines Agency Guideline
Authors: López Cristina , Díez Raquel , Rodríguez José M. , Sierra Matilde , García Juan J. , Fernández Nélida , Diez M. José , Sahagún Ana M.
Published: August 2022

Sparfloxacin, a synthetic antibiotic belonging to the third-generation fluoroquinolones, has numerous pharmacokinetic and microbiological advantages which can make it an excellent candidate for the treatment of infections in sheep. The objective of this study was to develop and validate an analytical HPLC method to quantify sparfloxacin in sheep plasma, following the recommendations set out in the Guideline on Bioanalytical Method Validation of the European Union (EMEA/CHMP/EWP/192217/2009). The HPLC mobile phase consisted of acetonitrile and monopotassium phosphate buffer (1.36 g/L) 49:51 (v/v). Genabilic acid was used as internal standard. Mean retention times for sparfloxacin and genabilic acid were 2.6 and 5.8 min, respectively. The method met all specifications of the EMA guideline, being selective and linear in the range of 0.2–10 µg/mL (R2 ≥ 0.99). Within-run precision ranged between 0.00 and 0.88%, with an accuracy of 90.3–118.0% for the lower limit of quantitation (LLOQ). The LLOQ was 0.2 µg/mL, and no interference from the biological matrix was found. The stability of sparfloxacin in the biological matrix was demonstrated under different storage conditions. Therefore, the method can be used to determine sparfloxacin concentrations in sheep plasma in different types of studies.
Post-Intervention Reconstruction and the Responsibility to Rebuild
Authors: Stathopoulos Athanasios
Published: August 2022

This article examines the relationship between the responsibility to rebuild and post-intervention reconstruction. It aims to determine whether the current interpretation of the responsibility to rebuild is the appropriate framework for attaining the goals of post-intervention reconstruction. The article argues that, despite the urgent need for a post-intervention strategy in the aftermath of humanitarian interventions, the responsibility to rebuild, as it is currently being framed, can end up undermining the goals of post-conflict reconstruction by dissuading states from participating in atrocity prevention, inadvertently increasing atrocity crimes and delegitimizing military humanitarian interventions. The analysis identifies the need for the responsibility to rebuild to incorporate an increased respect for post bellum proportionality and self-determination.