bluuebunny/crossref_metadata_2025 huggingface dataset:
A New Design Problem in the Formulation of a Special Moment Resisting Connection Device for Preventing Local Buckling
Authors: Benfratello Salvatore , Palizzolo Luigi , Vazzano Santo
Published: December 2021

In the present paper an improved formulation devoted to the optimal design problem of a special moment resisting connection device for steel frames is proposed. This innovative device is called a Limited Resistance Plastic Device (LRPD) and it has been recently proposed and patented by some of the authors. It is thought to be preferably located at the extremes of the beam, connecting the beam end cross section with the relevant column. The typical device is a steel element characterized by symmetry with respect to three orthogonal barycentric planes and constituted by a sequence of three portions with abrupt cross section changes. The main novelty of the present proposal is related to the design of special geometry for the optimal device ensuring that it possesses a reduced resistance with respect to the relevant connected beam element, is characterized by an equivalent bending stiffness equal to the one of the connected beam elements and exhibits full plastic deformations avoiding any local instability phenomenon. The optimal design is formulated as a minimum volume one and is subjected to suitable constraints on the geometry of the device and on its elastic and plastic behavior. The optimization problem is a strongly non-linear programming one and it is solved by adopting an interior-point algorithm that is available in the MATLAB Optimization Toolbox. The numerical simulations are devoted to the most used standard steel profiles (IPE, HE) and the results prove the great reliability of the proposed device. In addition, the relevant elastic and plastic domains of the designed devices are defined, and the expected behavior of the device is verified by appropriate 3D finite element models in the ABAQUS environment.
A Transfer Learning Technique for Inland Chlorophyll-a Concentration Estimation Using Sentinel-3 Imagery
Authors: Syariz Muhammad Aldila , Lin Chao-Hung , Heriza Dewinta , Lasminto Umboro , Sukojo Bangun Muljo , Jaelani Lalu Muhamad
Published: December 2021

Chlorophyll-a (Chla) concentration, which serves as a phytoplankton substitute in inland waters, is one of the leading indicators for water quality. Generally, water samples are analyzed in professional laboratories, and Chla concentrations are measured regularly for the purpose of water quality monitoring. However, limited spatial water sampling and the labor-intensive nature of data collection make global and long-term monitoring difficult. The developments of remote-sensing optical sensors and technologies make the long-term monitoring of Chla concentrations for an entire water body more achievable. Many studies based on machine learning techniques, such as regression and artificial neural network (ANN) methods, have recently been proposed for Chla concentration estimation using optical satellite images. The methods based on machine learning can achieve accurate estimation. However, overfitting problems may arise because the in situ Chla dataset is generally insufficient to train a complicated machine learning model, which makes trained models inapplicable. In this study, an ANN model containing three convolutional and two fully connected layers with 4953 unknown parameters is designed. A transfer learning method, consisting of model pretraining, main-training, and fine-tuning stages, is proposed to ease the problem of insufficient in situ samples. In the model pretraining stage, the ANN model is pretrained and initialized using samples derived from an existing Chla concentration model. The pretrained ANN model is then fine-tuned using the proposed transfer learning technique with in situ samples collected in five different campaigns carried out during early 2019 from Laguna Lake, the Philippines. Before the transfer learning, data augmentation and rebalancing methods are conducted to enrich the variability and to near-uniformly distribute the in situ samples in Chla concentration space, respectively. To estimate the alleviation of model overfitting, the trained ANN model, using an in situ dataset from Laguna Lake, was tested using an in situ dataset from Lake Victoria, Uganda, obtained in 2019, which has a similar trophic state as Laguna Lake. The experimental results from Sentinel-3 imagery indicated that the overfitting problem was significantly alleviated and the trained ANN model outperformed related models in terms of the root-mean-squared error of the estimated Chla concentrations.
Benefits of Advanced Air Mobility for Society and Environment: A Case Study of Ohio
Authors: Dulia Esrat F. , Sabuj Mir S. , Shihab Syed A. M.
Published: December 2021

Advanced Air Mobility (AAM) is an emerging transportation system that will enable the safe and efficient low altitude operations and applications of unmanned aircraft (e.g., passenger transportation and cargo delivery) in the national airspace. This system is currently under active research and development by NASA in collaboration with FAA, other federal partner agencies, industry, and academia to develop its infrastructure, information architecture, software functions, concepts of operation, operations management tools and other functional components. Existing studies have, however, not thoroughly analyzed the net positive impact of AAM on society and environment to justify investments in its infrastructure and implementation. In this work, we fill this gap by evaluating the non-monetary social impact of AAM in the state of Ohio for passengers, patients, farmers, logistics companies and their customers and bridge inspection entities, as well as its environmental impact, by conducting a thorough data-driven quantitative cost–benefit analysis of AAM from the perspective of the state government. To this end, the most relevant and significant benefit and cost factors are identified, monetized, and estimated. Existing ground transportation for the movement of passengers and goods within and across urban areas is considered as the base case. The findings demonstrate that AAM’s benefits are large and varied, far outweighing its costs. Insights on these benefits can help gain community acceptance of AAM, which is critical for successful implementation of AAM. The findings support decision-making for policymakers and provide justification for investments in AAM infrastructure by the government and private sector.
Jan van Eyck’s New York Diptych: A New Reading on the Skeleton of the Great Chasm
Authors: Sugiyama Miyako
Published: December 2021

The Crucifixion and Last Judgment, or the so-called New York Diptych, is one of the most controversial paintings attributed to Jan van Eyck (ca. 1390–1441) and his workshop. For well over a century, art historians have vigorously discussed its attribution, composition, functional intent, and even its dating. In light of prior scholarship addressing these remarkable panels, this paper focuses on the skeleton represented in the Last Judgment to reveal its iconographical meanings. Specifically, I highlight the inscriptions written on the skeleton’s wings, suggesting that the texts were cited from an All Saints’ Day sermon delivered by the Burgundian abbot Bernard of Clairvaux (1090–1153) who discussed a temporal location for blessed or sinful souls.
Arctic Stratosphere Circulation Changes in the 21st Century in Simulations of INM CM5
Authors: Vargin Pavel N. , Kostrykin Sergey V. , Volodin Evgeni M. , Pogoreltsev Alexander I. , Wei Ke
Published: December 2021

Simulations of Institute of Numerical Mathematics (INM) coupled climate model 5th version for the period from 2015 to 2100 under moderate (SSP2-4.5) and severe (SSP5-8.5) scenarios of greenhouse gases growth are analyzed to investigate changes of Arctic polar stratospheric vortex, planetary wave propagation, Sudden Stratospheric Warming frequency, Final Warming dates, and meridional circulation. Strengthening of wave activity propagation and a stationary planetary wave number 1 in the middle and upper stratosphere, acceleration of meridional circulation, an increase of winter mean polar stratospheric volume (Vpsc) and strengthening of Arctic stratosphere interannual variability after the middle of 21st century, especially under a severe scenario, were revealed. March monthly values of Vpsc in some winters could be about two times more than observed ones in the Arctic stratosphere in the spring of 2011 and 2020, which in turn could lead to large ozone layer destruction. Composite analysis shows that “warm” winters with the least winter mean Vpsc values are characterized by strengthening of wave activity propagation from the troposphere into the stratosphere in December but weaker propagation in January–February in comparison with winters having the largest Vpsc values.
The Modeling Study about Impacts of Emission Control Policies for Chinese 14th Five-Year Plan on PM2.5 and O3 in Yangtze River Delta, China
Authors: Li Zhen , Yu Shaocai , Li Mengying , Chen Xue , Zhang Yibo , Song Zhe , Li Jiali , Jiang Yaping , Liu Weiping , Li Pengfei , Zhang Xiaoye
Published: December 2021

The Chinese government has made great efforts to combat air pollution through the reductions in SO2, NOx and VOCs emissions, as part of its socioeconomic Five-Year Plans (FYPs). China aims to further reduce the emissions of VOCs and NOx by 10% in its upcoming 14th FYP (2021–2025). Here, we used a regional chemical transport model (e.g., WRF/CMAQ) to examine the responses of PM2.5 and O3 to emission control policies of the 14th FYP in the Yangtze River Delta (YRD) region. The simulation results under the 4 emission control scenarios in the 2 winter months in 2025 indicate that the average concentrations of city mean PM2.5 in 41 cities in the YRD were predicted to only decrease by 10% under both S1 and S1_E scenarios, whereas the enhanced emission control scenarios (i.e., S2_E and S3_E) could reduce PM2.5 in each city by more than 20%. The model simulation results for O3 in the 3 summer months in 2025 show that the O3 responses to the emission controls under the S1 and S1_E scenarios show different control effects on O3 concentrations in the YRD with the increase and decrease effects, respectively. The study found that both enhanced emission control scenarios (S2_E and S3_E) could decrease O3 in each city by more than 20% with more reductions in O3 under the S3_E emission control scenario because of its higher control strengths for both NOx and VOCs emissions. It was found that emission reduction policies for controlling high emission sectors of NOx and VOCs such as S2_E and S3_E were more effective for decreasing both PM2.5 and O3 in the YRD. This study shows that O3 controls will benefit from well-designed air pollution control strategies for reasonable control ratios of NOx and VOCs emissions.
Multiscale Interactive Processes Underlying the Heavy Rainstorm Associated with a Landfalling Atmospheric River
Authors: Zhang Zhuang , Liang X. San
Published: December 2021

The heavy precipitation in Northern California—brought about by a landfalling atmospheric river (AR) on 25–27 February 2019—is investigated for an understanding of the underlying dynamical processes. By the peaks in hourly accumulation, this rainstorm can be divided into two stages (Stage I and Stage II). Using a recently developed multiscale analysis methodology, i.e., multiscale window transform (MWT), and the MWT-based theory of canonical transfer, the original fields are reconstructed onto three scale windows, namely, the background flow, synoptic-scale and mesoscale windows, and the interactions among them are henceforth investigated. In both stages, the development of the precipitation is attributed to a vigorous buoyancy conversion and latent heating, and besides, the instability of the background flow. In Stage I, the instability is baroclinic, while in Stage II, it is barotropic. Interestingly, in Stage I, the mesoscale kinetic energy is transferred to the background flow where it is stored, and is released back in Stage II to the mesoscale window again, triggering intense precipitation.
Forensic Tools for Species Identification of Skeletal Remains: Metrics, Statistics, and OsteoID
Authors: Garvin Heather M. , Dunn Rachel , Sholts Sabrina B. , Litten M. Schuyler , Mohamed Merna , Kuttickat Nathan , Skantz Noah
Published: December 2021

Although nonhuman remains constitute a significant portion of forensic anthropological casework, the potential use of bone metrics to assess the human origin and to classify species of skeletal remains has not been thoroughly investigated. This study aimed to assess the utility of quantitative methods in distinguishing human from nonhuman remains and present additional resources for species identification. Over 50,000 measurements were compiled from humans and 27 nonhuman (mostly North American) species. Decision trees developed from the long bone data can differentiate human from nonhuman remains with over 90% accuracy (>98% accuracy for the human sample), even if all long bones are pooled. Stepwise discriminant function results were slightly lower (>87.4% overall accuracy). The quantitative models can be used to support visual identifications or preliminarily assess forensic significance at scenes. For species classification, bone-specific discriminant functions returned accuracies between 77.7% and 89.1%, but classification results varied highly across species. From the study data, we developed a web tool, OsteoID, for users who can input measurements and be shown photographs of potential bones/species to aid in visual identification. OsteoID also includes supplementary images (e.g., 3D scans), creating an additional resource for forensic anthropologists and others involved in skeletal species identification and comparative osteology.
Small Angle X-ray Scattering Sensing Membrane Composition: The Role of Sphingolipids in Membrane-Amyloid β-Peptide Interaction
Authors: Carrotta Rita , Mangione Maria Rosalia , Librizzi Fabio , Moran Oscar
Published: December 2021

The early impairments appearing in Alzheimer’s disease are related to neuronal membrane damage. Both aberrant Aβ species and specific membrane components play a role in promoting aggregation, deposition, and signaling dysfunction. Ganglioside GM1, present with cholesterol and sphingomyelin in lipid rafts, preferentially interacts with the Aβ peptide. GM1 at physiological conditions clusters in the membrane, the assembly also involves phospholipids, sphingomyelin, and cholesterol. The structure of large unilamellar vesicles (LUV), made of a basic POPC:POPS matrix in a proportion of 9:1, and containing different amounts of GM1 (1%, 3%, and 4% mol/mol) in the presence of 5% mol/mol sphingomyelin and 15% mol/mol cholesterol, was studied using small angle X-ray scattering (SAXS). The effect of the membrane composition on the LUVs–Aβ-peptide interaction, both for Aβ1–40 and Aβ1–42 variants, was, thus, monitored. The presence of GM1 leads to a significant shift of the main peak, towards lower scattering angles, up to 6% of the initial value with SM and 8% without, accompanied by an opposite shift of the first minimum, up to 21% and 24% of the initial value, respectively. The analysis of the SAXS spectra, using a multi-Gaussian model for the electronic density profile, indicated differences in the bilayer of the various compositions. An increase in the membrane thickness, by 16% and 12% when 2% and 3% mol/mol GM1 was present, without and with SM, respectively, was obtained. Furthermore, in these cases, in the presence of Aβ40, a very small decrease of the bilayer thickness, less than 4% and 1%, respectively, was derived, suggesting the inhibiting effect that the presence of sphingomyelin has on the GM1–Aβ interaction.
Fecal Microbiota Dynamics Reveal the Feasibility of Early Weaning of Yak Calves under Conventional Grazing System
Authors: Zhang Jianbo , Wang Peng , Dingkao Renqing , Du Mei , Ahmad Anum Ali , Liang Zeyi , Zheng Juanshan , Shen Jiahao , Yan Ping , Ding Xuezhi
Published: December 2021

Background: The gut microbiota plays an important role in the health and production of animals. However, little information is available on the dynamic variations and comparison of intestinal microbiota in post-weaning yak calves living on the QTP. Methods: We explored the fecal bacterial microbiota succession of yak calves at different months after early weaning (60 d) compared with cattle calves by 16S rRNA gene amplicon sequencing and functional composition prediction. Results: We found no significant difference in blood biochemical parameters related to glucose and lipid metabolism between yaks and calves in different months after weaning. The core fecal bacterial microbiota from both species of calves was dominated by Ruminococcaceae, Rikenellaceae, and Bacteroidaceae. The fecal microbial community has a great alteration within the time after weaning in both cattle and yak calves, but cattle showed a larger change. After five months, the microbiota achieves a stable and concentrated state. This is also similar to the functional profile. Conclusions: Based on the exploration of dynamic changes in the fecal microbiota at an early stage of life, our results illustrated that there were no negative effects of intestinal microbiota succession on yak calves when early weaning was employed.
Stimulation of Neurite Outgrowth Using Autologous NGF Bound at the Surface of a Fibrous Substrate
Authors: Casanova Marta R. , Reis Rui L. , Martins Albino , Neves Nuno M.
Published: December 2021

Peripheral nerve injury still remains a major clinical challenge, since the available solutions lead to dysfunctional nerve regeneration. Even though autologous nerve grafts are the gold standard, tissue engineered nerve guidance grafts are valid alternatives. Nerve growth factor (NGF) is the most potent neurotrophic factor. The development of a nerve guidance graft able to locally potentiate the interaction between injured neurons and autologous NGF would be a safer and more effective alternative to grafts that just release NGF. Herein, a biofunctional electrospun fibrous mesh (eFM) was developed through the selective retrieval of NGF from rat blood plasma. The neurite outgrowth induced by the eFM-NGF systems was assessed by culturing rat pheochromocytoma (PC12) cells for 7 days, without medium supplementation. The biological results showed that this NGF delivery system stimulates neuronal differentiation, enhancing the neurite growth more than the control condition.
Lipoprotein(a)—The Crossroads of Atherosclerosis, Atherothrombosis and Inflammation
Authors: Ugovšek Sabina , Šebeštjen Miran
Published: December 2021

Increased lipoprotein(a) (Lp(a)) levels are an independent predictor of coronary artery disease (CAD), degenerative aortic stenosis (DAS), and heart failure independent of CAD and DAS. Lp(a) levels are genetically determinated in an autosomal dominant mode, with great intra- and inter-ethnic diversity. Most variations in Lp(a) levels arise from genetic variations of the gene that encodes the apolipoprotein(a) component of Lp(a), the LPA gene. LPA is located on the long arm of chromosome 6, within region 6q2.6–2.7. Lp(a) levels increase cardiovascular risk through several unrelated mechanisms. Lp(a) quantitatively carries all of the atherogenic risk of low-density lipoprotein cholesterol, although it is even more prone to oxidation and penetration through endothelia to promote the production of foam cells. The thrombogenic properties of Lp(a) result from the homology between apolipoprotein(a) and plasminogen, which compete for the same binding sites on endothelial cells to inhibit fibrinolysis and promote intravascular thrombosis. LPA has up to 70% homology with the human plasminogen gene. Oxidized phospholipids promote differentiation of pro-inflammatory macrophages that secrete pro-inflammatory cytokines (e. g., interleukin (IL)-1β, IL-6, IL-8, tumor necrosis factor-α). The aim of this review is to define which of these mechanisms of Lp(a) is predominant in different groups of patients.
The Limitation of the Combination of Transition State Theory and Thermodynamics for the Reactions of Proteins and Nucleic Acids
Authors: Shimamoto Nobuo
Published: December 2021

When a reaction is accompanied by a change with the speed close to or slower than the reaction rate, a circulating reaction flow can exist among the reaction states in the macroscopic stationary state. If the accompanying change were at equilibrium in the timescale of the relevant reaction, the transition-state theory would hold to eliminate the flow.
Gallic Acid Derivatives Propyl Gallate and Epigallocatechin Gallate Reduce rRNA Transcription via Induction of KDM2A Activation
Authors: Tanaka Yuji , Tsuneoka Makoto
Published: December 2021

We previously reported that lysine-demethylase 2A (KDM2A), a Jumonji-C histone demethylase, is activated by gallic acid to reduce H3K36me2 levels in the rRNA gene promoter and consequently inhibit rRNA transcription and cell proliferation in the breast cancer cell line MCF-7. Gallic acid activates AMP-activated protein kinase (AMPK) and increases reactive oxygen species (ROS) production to activate KDM2A. Esters of gallic acid, propyl gallate (PG) and epigallocatechin gallate (EGCG), and other chemicals, reduce cancer cell proliferation. However, whether these compounds activate KDM2A has yet to be tested. In this study, we found that PG and EGCG decreased rRNA transcription and cell proliferation through KDM2A in MCF-7 cells. The activation of both AMPK and ROS production by PG or EGCG was required to activate KDM2A. Of note, while the elevation of ROS production by PG or EGCG was limited in time, it was sufficient to activate KDM2A. Importantly, the inhibition of rRNA transcription and cell proliferation by gallic acid, PG, or EGCG was specifically observed in MCF-7 cells, whereas it was not observed in non-tumorigenic MCF10A cells. Altogether, these results suggest that the derivatization of gallic acid may be used to obtain new compounds with anti-cancer activity.
Plant-Based Green Synthesis of Nanoparticles: Production, Characterization and Applications
Authors: Hano Christophe , Abbasi Bilal Haider
Published: December 2021

Nanotechnology is a fast-expanding and multidisciplinary field with many applications in science and technology [...]
Exosomal microRNA Differential Expression in Plasma of Young Adults with Chronic Mild Traumatic Brain Injury and Healthy Control
Authors: Vorn Rany , Suarez Maiko , White Jacob C. , Martin Carina A. , Kim Hyung-Suk , Lai Chen , Yun Si-Jung , Gill Jessica M. , Lee Hyunhwa
Published: December 2021

Chronic mild traumatic brain injury (mTBI) has long-term consequences, such as neurological disability, but its pathophysiological mechanism is unknown. Exosomal microRNAs (exomiRNAs) may be important mediators of molecular and cellular changes involved in persistent symptoms after mTBI. We profiled exosomal microRNAs (exomiRNAs) in plasma from young adults with or without a chronic mTBI to decipher the underlying mechanisms of its long-lasting symptoms after mTBI. We identified 25 significantly dysregulated exomiRNAs in the chronic mTBI group (n = 29, with 4.48 mean years since the last injury) compared to controls (n = 11). These miRNAs are associated with pathways of neurological disease, organismal injury and abnormalities, and psychological disease. Dysregulation of these plasma exomiRNAs in chronic mTBI may indicate that neuronal inflammation can last long after the injury and result in enduring and persistent post-injury symptoms. These findings are useful for diagnosing and treating chronic mTBIs.
COVID-19 and Post-Acute COVID-19 Syndrome: From Pathophysiology to Novel Translational Applications
Authors: Ambrosino Pasquale , Lanzillo Anna , Maniscalco Mauro
Published: December 2021

In late 2019, the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) gave rise to a public health emergency, culminating in the declaration of a pandemic in March 2020 [...]
The Fornix May Play a Key Role in Korsakoff’s Amnesia Secondary to Subcallosal Artery Infarction
Authors: Hayashi Masataka , Fujimoto Ayataka , Enoki Hideo , Niimi Keiko , Inenaga Chikanori , Sato Keishiro , Homma Kazunari , Arakawa Tomoya , Okanishi Tohru
Published: December 2021

Background: Subcallosal artery infarction injures the fornix and anterior corpus callosum and sometimes causes Korsakoff’s amnesia. We hypothesized that Korsakoff’s amnesia might be caused by fornix dysfunction rather than anterior corpus callosum dysfunction in subcallosal artery infarction. Methods: A systematic review approach was applied to search PubMed and Google Scholar for articles to compare patients who had both bilateral fornix and corpus callosum infarction due to subcallosal artery territory ischemia (vascular event group; V group) with patients who had undergone anterior corpus callosotomy (callosotomy group; C group). Results: The V group comprised 10 patients (mean age, 63 years; median, 69 years; standard deviation (SD), 14.5 years; 5 males, 5 females). The C group comprised 6 patients (mean age, 23.7 years; median, 20 years; SD, 7.3 years; 3 males, 3 females). Six of 10 patients (60%) with subcallosal artery infarction exhibited Korsakoff’s amnesia. One patient showed neither confabulation nor amnesia. Conversely, no amnesia episodes were seen in any patients from the C group (p = 0.034). Conclusion: Fornix injury, rather than anterior corpus callosum injury, might be the major cause of Korsakoff’s amnesia in patients with subcallosal artery infarction.
Effect of Heating Rate on the Photocatalytic Activity of Ag–TiO2 Nanocomposites by One-Step Process via Aerosol Routes
Authors: Kusdianto Kusdianto , Hudandini Meditha , Jiang Dianping , Kubo Masaru , Shimada Manabu
Published: December 2021

Ag–TiO2 nanocomposite films, based of Ag and TiO2 nanoparticles, were fabricated in a one-step aerosol route employing the simultaneous plasma-enhanced chemical vapor deposition and physical vapor deposition systems. The as-fabricated films were subjected to different heating rates (3 to 60 °C/min) with a constant annealing temperature of 600 °C to observe the significant changes in the properties (e.g., nanoparticle size, crystalline size, crystallite phase, surface area) toward the photocatalytic performance. The photocatalytic activity was evaluated by the measurement of the degradation of a methylene blue aqueous solution under UV light irradiation, and the results revealed that it gradually increased with the increase in the heating rate, caused by the increased Brunauer–Emmett–Teller (BET) specific surface area and total pore volume.
Hydrothermal Synthesis of CuO/RuO2/MWCNT Nanocomposites with Morphological Variants for High Efficient Supercapacitors
Authors: Chung Yi-Chen , Julistian Ade , Saravanan Lakshmanan , Chen Peng-Ren , Xu Bai-Cheng , Xie Pei-Jie , Lo An-Ya
Published: December 2021

In this study, we develop the optimum composition of copper oxide/ruthenium oxide and multi-walled carbon nanotubes (CuO/RuO2/MWCNTs) ternary nanocomposite via a hydrothermal method as an efficient electrode material for supercapacitor applications. The ratio between CuO and RuO2 varied to improve the electrochemical performance of the electrode. The synthesized nanocomposites are analyzed by high-resolution scanning electron microscopy (HR-SEM), thermo gravimetric analyzer (TGA) and electrochemical impedance spectroscopy (EIS). Furthermore, the elemental composition is analyzed by energy dispersive X-ray (EDX) spectroscopy and the specific capacitance was analyzed by cyclic voltammetry (CV) and galvanostatic charge–discharge (GCD) methods. The electrochemical investigations is conducted in a three-electrode system and the sample is attached on a stainless steel plate as the working electrode; platinum wire works as the counter electrode and Ag/AgCl electrode as the reference electrode, adopting 3 M (NH4)2SO4 as the electrolyte. The resultant of CuO/RuO2/MWCNT nanocomposite with 7 wt% Cu and 20 wt% Ru was found to perform the highest specific capacitance of 461.59 F/g in a current density of 1 A/g.
Altered Ca2+ Homeostasis in Red Blood Cells of Polycythemia Vera Patients Following Disturbed Organelle Sorting during Terminal Erythropoiesis
Authors: Buks Ralfs , Dagher Tracy , Rotordam Maria , Monedero Alonso David , Cochet Sylvie , Gautier Emilie-Fleur , Chafey Philippe , Cassinat Bruno , Kiladjian Jean-Jacques , Becker Nadine , Plo Isabelle , Egée Stéphane , El Nemer Wassim
Published: December 2021

Over 95% of Polycythemia Vera (PV) patients carry the V617F mutation in the tyrosine kinase Janus kinase 2 (JAK2), resulting in uncontrolled erythroid proliferation and a high risk of thrombosis. Using mass spectrometry, we analyzed the RBC membrane proteome and showed elevated levels of multiple Ca2+ binding proteins as well as endoplasmic-reticulum-residing proteins in PV RBC membranes compared with RBC membranes from healthy individuals. In this study, we investigated the impact of JAK2V617F on (1) calcium homeostasis and RBC ion channel activity and (2) protein expression and sorting during terminal erythroid differentiation. Our data from automated patch-clamp show modified calcium homeostasis in PV RBCs and cell lines expressing JAK2V617F, with a functional impact on the activity of the Gárdos channel that could contribute to cellular dehydration. We show that JAK2V617F could play a role in organelle retention during the enucleation step of erythroid differentiation, resulting in modified whole cell proteome in reticulocytes and RBCs in PV patients. Given the central role that calcium plays in the regulation of signaling pathways, our study opens new perspectives to exploring the relationship between JAK2V617F, calcium homeostasis, and cellular abnormalities in myeloproliferative neoplasms, including cellular interactions in the bloodstream in relation to thrombotic events.
Emerging Lysosomal Functions for Photoreceptor Cell Homeostasis and Survival
Authors: Santo Manuela , Conte Ivan
Published: December 2021

Lysosomes are membrane-bound cell organelles that respond to nutrient changes and are implicated in cell homeostasis and clearance mechanisms, allowing effective adaptation to specific cellular needs. The relevance of the lysosome has been elucidated in a number of different contexts. Of these, the retina represents an interesting scenario to appreciate the various functions of this organelle in both physiological and pathological conditions. Growing evidence suggests a role for lysosome-related mechanisms in retinal degeneration. Abnormal lysosomal activation or inhibition has dramatic consequences on photoreceptor cell homeostasis and impacts extensive cellular function, which in turn affects vision. Based on these findings, a series of therapeutic methods targeting lysosomal processes could offer treatment for blindness conditions. Here, we review the recent findings on membrane trafficking, subcellular organization, mechanisms by which lysosome/autophagy pathway impairment affects photoreceptor cell homeostasis and the recent advances on developing efficient lysosomal-based therapies for retinal disorders.
Prediction of Trained Panel Sensory Scores for Beef with Non-Invasive Raman Spectroscopy
Authors: Cafferky Jamie , Cama-Moncunill Raquel , Sweeney Torres , Allen Paul , Cromie Andrew , Hamill Ruth M.
Published: December 2021

The objective of this study was to investigate Raman spectroscopy as a tool for the prediction of sensory quality in beef. Raman spectra were collected from M. longissimus thoracis et lumborum (LTL) muscle on a thawed steak frozen 48 h post-mortem. Another steak was removed from the muscle and aged for 14 days before being assessed for 12 sensory traits by a trained panel. The most accurate coefficients of determination of cross validation (R2CV) calibrated within the current study were for the trained sensory panel textural scores; particularly tenderness (0.46), chewiness (0.43), stringiness (0.35) and difficulty to swallow (0.33), with practical predictions also achieved for metallic flavour (0.52), fatty after-effect (0.44) and juiciness (0.36). In general, the application of mathematical spectral pre-treatments to Raman spectra improved the predictive accuracy of chemometric models developed. This study provides calibrations for valuable quality traits derived from a trained sensory panel in a non-destructive manner, using Raman spectra collected at a time-point compatible with meat management systems.
Formula Development of Red Palm (Elaeis guineensis) Fruit Extract Loaded with Solid Lipid Nanoparticles Containing Creams and Its Anti-Aging Efficacy in Healthy Volunteers
Authors: Plyduang Thipapun , Atipairin Apichart , Sae Yoon Attawadee , Sermkaew Namfa , Sakdiset Pajaree , Sawatdee Somchai
Published: December 2021

Palm fruits (Elaeis guineensis) comprise antioxidants that can be used as skin care agents. This study developed a cosmeceutical cream containing E. guineensis extract, loaded with solid lipid nanoparticles (SLNs), and assessed its efficacy on female volunteers. The E. guineensis extract exhibited a good antioxidant activity with high levels of vitamin E, β-carotene, and palmitic acid. Day and night creams containing E. guineensis fruit extract, loaded with SLNs, were formulated and exhibited acceptable physical characteristics and good stability. Subsequently, their clinical efficacy and safety were evaluated on female volunteers. Both creams were non-irritating and had good cutaneous compatibility. Skin hydration, transepidermal water loss (TEWL), skin elasticity, melanin index, and skin texture were measured before and 30 min after the first application, as well as after 7, 14, and 30 days of daily application. A satisfactory survey was implemented using a questionnaire, and volunteer satisfaction scores were high for the product’s performance. Overall, the results showed that skin hydration, TEWL, cutaneous elasticity, and melanin index were improved, compared to the baseline data, after 30 days. Thus, the formulated facial day and night creams made the skin moist, reduced wrinkles, increased elasticity, and cleared the skin to the consumers’ satisfaction.
Part-of-Speech Tagging with Rule-Based Data Preprocessing and Transformer
Authors: Li Hongwei , Mao Hongyan , Wang Jingzi
Published: December 2021

Part-of-Speech (POS) tagging is one of the most important tasks in the field of natural language processing (NLP). POS tagging for a word depends not only on the word itself but also on its position, its surrounding words, and their POS tags. POS tagging can be an upstream task for other NLP tasks, further improving their performance. Therefore, it is important to improve the accuracy of POS tagging. In POS tagging, bidirectional Long Short-Term Memory (Bi-LSTM) is commonly used and achieves good performance. However, Bi-LSTM is not as powerful as Transformer in leveraging contextual information, since Bi-LSTM simply concatenates the contextual information from left-to-right and right-to-left. In this study, we propose a novel approach for POS tagging to improve the accuracy. For each token, all possible POS tags are obtained without considering context, and then rules are applied to prune out these possible POS tags, which we call rule-based data preprocessing. In this way, the number of possible POS tags of most tokens can be reduced to one, and they are considered to be correctly tagged. Finally, POS tags of the remaining tokens are masked, and a model based on Transformer is used to only predict the masked POS tags, which enables it to leverage bidirectional contexts. Our experimental result shows that our approach leads to better performance than other methods using Bi-LSTM.
Development of a Digitally Controlled Inductive Power Transfer System with Post-Regulation for Variable Load Demand
Authors: Stoyka Kateryna , Vitale Antonio , Costarella Massimo , Avella Alfonso , Pucciarelli Mario , Visconti Paolo
Published: December 2021

Inductive Power Transfer (IPT) is an emerging technology enabling a contactless charging process in manifold applications such as electric vehicles, wearable and portable devices, or biomedical applications. Such technology can be profitably used to develop enhanced electronic solutions in the framework of smart cities, homes and smart workplaces. This paper presents the development and realization of a series–series compensated IPT System (IPTS) followed by a post-regulator implemented by means of a DC–DC converter. Such a system is modeled through a first harmonic approximation method, and a sensitivity analysis of the IPTS performance is carried out with respect to the variations of the primary inverter switching frequency and phase-shift angle. As an element of novelty of this work, the bias points are determined which allow the efficiency maximization while ensuring system controllability. An enhanced dynamic modeling of the system is then performed by means of a coupled mode theory, including the inverter phase-shift modulation and extending its validity to whatever operating frequency. A digital control of the post-regulator is implemented by means of a commercial low-cost microcontroller enabling the output voltage regulation under both fixed and variable load conditions through a voltage mode control technique. An IPTS prototype is eventually realized, which is able to correctly perform the output voltage regulation at the desired nominal value of 12 V for static resistive loads in the range [5, 24] Ω, yielding the output power in the range [6, 28.8] W and the experimental efficiencies going from 72.1% (for 24 Ω) to 91.7% (for 5 Ω). The developed system can also be effectively used to deliver up to 35 W output power to variable loads, as demonstrated during the battery charging test. Finally, an excellent output voltage regulation is ascertained for load transients between 5 Ω and 24 Ω, with limited over- and undershoot amplitudes (less than 3% of the nominal output voltage), thus enabling the use of the proposed system for both fixed and variable loads in the framework of smart homes and workplaces applications.
Embedded Memories for Cryogenic Applications
Authors: Garzón Esteban , Teman Adam , Lanuzza Marco
Published: December 2021

The ever-growing interest in cryogenic applications has prompted the investigation for energy-efficient and high-density memory technologies that are able to operate efficiently at extremely low temperatures. This work analyzes three appealing embedded memory technologies under cooling—from room temperature (300 K) down to cryogenic levels (77 K). As the temperature goes down to 77 K, six-transistor static random-access memory (6T-SRAM) presents slight improvements for static noise margin (SNM) during hold and read operations, while suffering from lower (−16%) write SNM. Gain-cell embedded DRAM (GC-eDRAM) shows significant benefits under these conditions, with read voltage margins and data retention time improved by about 2× and 900×, respectively. Non-volatile spin-transfer torque magnetic random access memory (STT-MRAM) based on single- or double-barrier magnetic tunnel junctions (MTJs) exhibit higher read voltage sensing margins (36% and 48%, respectively), at the cost of longer write access time (1.45× and 2.1×, respectively). The above characteristics make the considered memory technologies to be attractive candidates not only for high-performance computing, but also enable the possibility to bridge the gap from room-temperature to the realm of cryogenic applications that operate down to liquid helium temperatures and below.
Study of Thermal Stress Fluctuations at the Die-Attach Solder Interface Using the Finite Element Method
Authors: Yan Luchun , Yao Jiawen , Dai Yu , Zhang Shanshan , Bai Wangmin , Gao Kewei , Yang Huisheng , Wang Yanbin
Published: December 2021

Solder joints in electronic packages are frequently exposed to thermal cycling in both real-life applications and accelerated thermal cycling tests. Cyclic temperature leads the solder joints to be subjected to cyclic mechanical loading and often accelerates the cracking failure of the solder joints. The cause of stress generated in thermal cycling is usually attributed to the coefficients of thermal expansion (CTE) mismatch of the assembly materials. In a die-attach structure consisting of multiple layers of materials, the effect of their CTE mismatch on the thermal stress at a critical location can be very complex. In this study, we investigated the influence of different materials in a die-attach structure on the stress at the chip–solder interface with the finite element method. The die-attach structure included a SiC chip, a SAC solder layer and a DBC substrate. Three models covering different modeling scopes (i.e., model I, chip–solder layer; model II, chip–solder layer and copper layer; and model III, chip–solder layer and DBC substrate) were developed. The 25–150 °C cyclic temperature loading was applied to the die-attach structure, and the change of stress at the chip–solder interface was calculated. The results of model I showed that the chip–solder CTE mismatch, as the only stress source, led to a periodic and monotonic stress change in the temperature cycling. Compared to the stress curve of model I, an extra stress recovery peak appeared in both model II and model III during the ramp-up of temperature. It was demonstrated that the CTE mismatch between the solder and copper layer (or DBC substrate) not only affected the maximum stress at the chip–solder interface, but also caused the stress recovery peak. Thus, the combined effect of assembly materials in the die-attach structure should be considered when exploring the joint thermal stresses.
Dielectric Resonators Antennas Potential Unleashed by 3D Printing Technology: A Practical Application in the IoT Framework
Authors: Chietera Francesco Paolo , Colella Riccardo , Catarinucci Luca
Published: December 2021

One of the most promising and exciting research fields of the last decade is that of 3D-printed antennas, as proven by the increasing number of related scientific papers. More specifically, the most common and cost-effective 3D printing technologies, which have become more and more widespread in recent years, are particularly suitable for the development of dielectric resonator antennas (DRAs), which are very interesting types of antennas exhibiting good gain, excellent efficiency, and potentially very small size. After a brief survey on how additive manufacturing (AM) can be used in 3D printing of antennas and how much the manufacturing process of DRAs can benefit from those technologies, a specific example, consisting of a wideband antenna operating at 2.4 GHz and 3.8 GHz, was deeply analyzed, realized, and tested. The obtained prototype exhibited compact size (60 × 60 × 16 mm3, considering the whole antenna) and a good agreement between measured and simulated S11, with a fractional bandwidth of 46%. Simulated gain and efficiency were also quite good, with values of 5.45 dBi and 6.38 dBi for the gain and 91% and 90% for the efficiency, respectively, at 2.45 GHz and 3.6 GHz.
A Dual Source Switched-Capacitor Multilevel Inverter with Reduced Device Count
Authors: Fahad Mohammad , Tariq Mohd , Faizan Mohammad , Ali Atib , Sarwar Adil , Dehghani Tafti Hossein , Ahmad Shafiq , Shah Noor Mohamed Adamali
Published: December 2021

Implementing voltage boost multilevel inverter topologies for PV and fuel cell energy sources is highly advantageous. Switched-capacitor multilevel inverters (SCMLI) have a step-up feature with low device requirements and can remove the need for high gain dc-dc converters leading to reduced overall system bulk. This work proposes a dual input SCMLI to achieve an output of nineteen levels while using a low number of components and high boosting factor and self-balancing of capacitor voltages. A comprehensive analysis of the proposed structure is presented, focusing on component requirements, cost and dynamic performance. The efficiency and loss distribution during operation is also provided. The operation and real-time performance of the SCMLI have been verified by simulation. Experimental results further validate the simulation results.
Real-Time Nanoscopic Rider Safety System for Smart and Green Mobility Based upon Varied Infrastructure Parameters
Authors: Malik Faheem Ahmed , Dala Laurent , Busawon Krishna
Published: December 2021

To create a safe bicycle infrastructure system, this article develops an intelligent embedded learning system using a combination of deep neural networks. The learning system is used as a case study in the Northumbria region in England’s northeast. It is made up of three components: (a) input data unit, (b) knowledge processing unit, and (c) output unit. It is demonstrated that various infrastructure characteristics influence bikers’ safe interactions, which is used to estimate the riskiest age and gender rider groups. Two accurate prediction models are built, with a male accuracy of 88 per cent and a female accuracy of 95 per cent. The findings concluded that different infrastructures pose varying levels of risk to users of different ages and genders. Certain aspects of the infrastructure are hazardous to all bikers. However, the cyclist’s characteristics determine the level of risk that any infrastructure feature presents. Following validation, the built learning system is interoperable under various scenarios, including current heterogeneous and future semi-autonomous and autonomous transportation systems. The results contribute towards understanding the risk variation of various infrastructure types. The study’s findings will help to improve safety and lead to the construction of a sustainable integrated cycling transportation system.
Dis-Cover AI Minds to Preserve Human Knowledge
Authors: Ranaldi Leonardo , Fallucchi Francesca , Zanzotto Fabio Massimo
Published: December 2021

Modern AI technologies make use of statistical learners that lead to self-empiricist logic, which, unlike human minds, use learned non-symbolic representations. Nevertheless, it seems that it is not the right way to progress in AI. The structure of symbols—the operations by which the intellectual solution is realized—and the search for strategic reference points evoke important issues in the analysis of AI. Studying how knowledge can be represented through methods of theoretical generalization and empirical observation is only the latest step in a long process of evolution. For many years, humans, seeing language as innate, have carried out symbolic theories. Everything seems to have skipped ahead with the advent of Machine Learning. In this paper, after a long analysis of history, the rule-based and the learning-based vision, we would investigate the syntax as possible meeting point between the different learning theories. Finally, we propose a new vision of knowledge in AI models based on a combination of rules, learning, and human knowledge.