bluuebunny/crossref_metadata_2025 huggingface dataset:
Effectiveness of Interventions to Manage Difficulties with Breastfeeding for Mothers of Infants under Six Months with Growth Faltering: A Systematic Review Update
Authors: Mohandas Saranya , Rana Ritu , Sirwani Barkha , Kirubakaran Richard , Puthussery Shuby
Published: February 2023

(1) Background: The current evidence on management of infants under six months (u6m) with growth faltering is limited and of low quality. This review aimed at updating an existing review to inform the WHO guideline update on prevention and management of growth faltering in infants u6m. The objective is to synthesise evidence on interventions to manage breastfeeding difficulties in mothers or caregivers of infants u6m with growth faltering to improve breastfeeding practices and breastmilk intake. (2) Methods: We searched PubMed, CINAHL, and Cochrane Library from December 2018 to December 2021 for experimental studies. Using RoB 2.0 and ROBINS-I tools, we assessed study quality and results were synthesised narratively. Using the GRADE approach, we assessed the quality of evidence for four outcome domains—breastfeeding (critical), anthropometric (important), mortality (important), and morbidity (important). (3) Results: We identified seven studies, conducted among neonates (mainly preterm, n = 14 to 607), and assessed the following interventions: (a) non-nutritive sucking (NNS) on breast (n = 2) and (b) alternative supplemental feeding techniques (n = 5, cup feeding, spoon feeding, supplemental feeding tube device, and syringe feeding), and reported breastfeeding and anthropometric outcomes. None of the studies reported mortality and morbidity outcomes. The reported breastfeeding outcomes included LATCH (Latch, Audible swallowing, Type of nipple, Comfort, Hold) total score, PIBBS (Preterm Infants Breastfeeding Behaviour Scale) total score, EBF (exclusive breastfeeding) at various time points and time to transition to full breastfeeding, and reported anthropometric outcomes included weight gain and weight at different time points. Studies had ‘serious’ indirectness and ‘serious’ to ‘very serious’ risks of bias. From the limited studies we found, NNS on breast compared to NNS on finger may have some benefits on PIBBS total score; NNS on breast compared to NNS on pacifier may have some benefits on EBF at discharge; and cup feeding compared to bottle feeding may have some benefits on EBF at discharge, at three months and at six months. (4) Conclusions: Evidence on the effectiveness of interventions to manage breastfeeding difficulties in mothers or caregivers of infants u6m with growth faltering to improve breastfeeding practices and increase breastmilk intake is ‘limited’ and of ‘low’ to ‘very low’ quality. As the majority of the infants in the included studies were neonates, no new recommendations can be made for infants from one to six months due to lack of evidence in this population. We need more studies targeting infants from one to six months of age. The review was registered with PROSPERO (CRD42022309001).
Evaluation of a Salt-Reduction Consumer Awareness Campaign Targeted at Parents Residing in the State of Victoria, Australia
Authors: Grimes Carley A. , Bolton Kristy A. , Lim Karen , Khokhar Durreajam , Santos Joseph Alvin , Trieu Kathy , Margerison Claire , Reimers Jenny , Armstrong Sian , Bolam Bruce , Rosewarne Emalie , Dunford Elizabeth K. , Jan Stephen , Woodward Mark , Neal Bruce , Nowson Caryl , Webster Jacqui
Published: February 2023

From 2015 to 2020 a state-wide salt-reduction initiative was launched in Victoria, Australia, including an awareness campaign focused on parents with children <18 years of age. To evaluate the impact of the campaign on salt-related knowledge, attitudes and behaviors (KABs) we have assessed trends in salt-related KAB pre- and post-delivery of the campaign in parents, as well as within the wider adult population. Cross-sectional surveys of adults aged 18–65 years were undertaken pre- (2015: n = 821 parents; n = 1527 general sample) and post-campaign (2019: n = 935 parents; n = 1747 general sample). KABs were assessed via an online survey. Data were analyzed with regression models and adjusted for covariates. Among parents, around one-quarter of salt-related KABs shifted in a positive direction, but changes were small: there was a 6% (95% CI 2, 11%) increase in the percentage who knew the main source of salt in the diet and reductions in the percentage who reported placing a salt shaker on the table (−8% (95%CI −12, −3)) and that their child added salt at the table (−5% (95% −9, −0.2)). Among the wider adult sample, even fewer shifts in KAB were observed, with some behaviors worsening at follow-up. These findings indicate that this consumer awareness campaign had minimum impact.
Combinatorial Therapeutic Potential of Stem Cells and Benzimidazol Derivatives for the Reduction of Liver Fibrosis
Authors: Iqbal Maryam , Shams Sulaiman , Rafiq Huma , Khan Momin , Khan Shahid , Sadique Khattak Umer , Afridi Sahib Gul , Bibi Fehmida , Abdulkareem Angham Abdulrhman , Naseer Muhammad Imran
Published: February 2023

(1) Background: Liver fibrosis is currently one of the top ten causes of death worldwide. Stem cells transplantation using mesenchymal stem cells (MSCs) is an alternative therapy which is used in the place of organ transplant, due to the incapacity of stem cells to endure oxidative stress in the damage site, thus affecting the healing process. The present study aimed to enhance the therapeutic potential of MSCs using combined therapy, along with the novel synthetic compounds of benzimidazol derivatives. (2) Methods: Eighteen compound series (benzimidazol derivatives) were screened against liver fibrosis using an in vitro CCl4-induced injury model on cultured hepatocytes. IC50 values were calculated on the bases of LDH assay and cell viability assay. (3) Results: Among the eighteen compounds, compounds (10), (14) and (18) were selected on the basis of IC50 value, and compound (10) was the most potent and had the lowest IC50 value in the LDH assay (8.399 ± 0.23 uM) and cell viability assay (4.73 ± 0.37 uM). Next, these compounds were combined with MSCs using an in vitro hepatocytes injury culture and in vivo rat fibrotic model. The effect of the MSCs + compounds treatment on injured hepatocytes was evaluated using LDH assay, cell viability assay, GSH assay and real-time PCR analysis and immuno-staining for caspase-3. Significant reductions in LDH level, caspase-3 and apoptotic marker genes were noted in MSCs + compounds-treated injured hepatocytes. In vivo data also showed the increased homing of the MSCs, along with compounds after transplantation. Real-time PCR analysis and TUNEL assay results also support our study. (4) Conclusions: It was concluded that compounds (10), (14) and (18) can be used in combination with MSCs to reduce liver fibrosis.
Pleiotrophin-Loaded Mesoporous Silica Nanoparticles as a Possible Treatment for Osteoporosis
Authors: Lozano Daniel , Leiva Beatriz , Gómez-Escalonilla Inés , Portal-Núñez Sergio , de Górtazar Arancha , Manzano Miguel , Vallet-Regí María
Published: February 2023

Osteoporosis is the most common type of bone disease. Conventional treatments are based on the use of antiresorptive drugs and/or anabolic agents. However, these treatments have certain limitations, such as a lack of bioavailability or toxicity in non-specific tissues. In this regard, pleiotrophin (PTN) is a protein with potent mitogenic, angiogenic, and chemotactic activity, with implications in tissue repair. On the other hand, mesoporous silica nanoparticles (MSNs) have proven to be an effective inorganic drug-delivery system for biomedical applications. In addition, the surface anchoring of cationic polymers, such as polyethylenimine (PEI), allows for greater cell internalization, increasing treatment efficacy. In order to load and release the PTN to improve its effectiveness, MSNs were successfully internalized in MC3T3-E1 mouse pre-osteoblastic cells and human mesenchymal stem cells. PTN-loaded MSNs significantly increased the viability, mineralization, and gene expression of alkaline phosphatase and Runx2 in comparison with the PTN alone in both cell lines, evidencing its positive effect on osteogenesis and osteoblast differentiation. This proof of concept demonstrates that MSN can take up and release PTN, developing a potent osteogenic and differentiating action in vitro in the absence of an osteogenic differentiation-promoting medium, presenting itself as a possible treatment to improve bone-regeneration and osteoporosis scenarios.
In Vitro Acaricidal Activity of Silver Nanoparticles (AgNPs) against the Poultry Red Mite (Dermanyssus gallinae)
Authors: Sioutas Georgios , Tsouknidas Alexandros , Gelasakis Athanasios I. , Vlachou Afrodite , Kaldeli Alexandra K. , Kouki Maria , Symeonidou Isaia , Papadopoulos Elias
Published: February 2023

Dermanyssus gallinae (PRM) is the most common blood-sucking ectoparasite in laying hens and is resistant against numerous acaricides. Silver nanoparticles (AgNPs) represent an innovative solution against PRM. The current study aimed to assess the in vitro acaricidal activity of AgNPs against PRM and describe their potential mechanism of action. Nanoparticles were produced using a wet chemistry approach. Mites were collected using AviVet traps from 18 poultry farms in Greece. Contact toxicity bioassays were carried out for 24 h with negative controls, 20, 40, 60, or 80 ppm AgNPs. Analysis of variance was used to compare the mortality rates of PRM between the control and treatment groups, while LC50, LC90, and LC99 values were estimated using probit regression analysis for the total farms jointly and separately. Nanoparticles displayed strong acaricidal activity, and mortality rates were significantly different between groups and increased by AgNPs concentration. Overall mean LC50, LC90, and LC99 values were 26.5, 58.8, and 112.3 ppm, respectively. Scanning electron microscopy on mites treated with 80 ppm AgNPs revealed cracks in their exoskeleton and limb detachments, presumably resulting from the interaction between AgNPs and the mites’ chitin. Future studies should focus on assessing AgNPs residues in chicken tissues before moving into field trials.
Cell Proteomic Footprinting: Advances in the Quality of Cellular and Cell-Derived Cancer Vaccines
Authors: Lokhov Petr G. , Balashova Elena E. , Trifonova Oxana P. , Maslov Dmitry L. , Archakov Alexander I.
Published: February 2023

In omics sciences, many compounds are measured simultaneously in a sample in a single run. Such analytical performance opens up prospects for improving cellular cancer vaccines and other cell-based immunotherapeutics. This article provides an overview of proteomics technology, known as cell proteomic footprinting. The molecular phenotype of cells is highly variable, and their antigenic profile is affected by many factors, including cell isolation from the tissue, cell cultivation conditions, and storage procedures. This makes the therapeutic properties of cells, including those used in vaccines, unpredictable. Cell proteomic footprinting makes it possible to obtain controlled cell products. Namely, this technology facilitates the cell authentication and quality control of cells regarding their molecular phenotype, which is directly connected with the antigenic properties of cell products. Protocols for cell proteomic footprinting with their crucial moments, footprint processing, and recommendations for the implementation of this technology are described in this paper. The provided footprints in this paper and program source code for their processing contribute to the fast implementation of this technology in the development and manufacturing of cell-based immunotherapeutics.
Production and Utility of Extracellular Vesicles with 3D Culture Methods
Authors: Casajuana Ester Mar , Day Richard M.
Published: February 2023

In recent years, extracellular vesicles (EVs) have emerged as promising biomarkers, cell-free therapeutic agents, and drug delivery carriers. Despite their great clinical potential, poor yield and unscalable production of EVs remain significant challenges. When using 3D culture methods, such as scaffolds and bioreactors, large numbers of cells can be expanded and the cell environment can be manipulated to control the cell phenotype. This has been employed to successfully increase the production of EVs as well as to enhance their therapeutic effects. The physiological relevance of 3D cultures, such as spheroids, has also provided a strategy for understanding the role of EVs in the pathogenesis of several diseases and to evaluate their role as tools to deliver drugs. Additionally, 3D culture methods can encapsulate EVs to achieve more sustained therapeutic effects as well as prevent premature clearance of EVs to enable more localised delivery and concentrated exosome dosage. This review highlights the opportunities and drawbacks of different 3D culture methods and their use in EV research.
Identification and Phylogenetic Analysis of the R2R3-MYB Subfamily in Brassica napus
Authors: Luo Dingfan , Mei Desheng , Wei Wenliang , Liu Jia
Published: February 2023

The R2R3-MYB sub-family proteins are composed of most members of MYB (v-Myb avian myeloblastosis viral oncogene homolog) protein, a plant-specific transcription factor (TF) that is classified into four classes depending on the number of MYB repeats. R2R3-MYB TFs are involved in physiological and biochemical processes. However, the functions of the Brassica napus R2R3-MYB genes are still mainly unknown. In this study, 35 Brassica napus MYB (BnaMYB) genes were screened in the genome of Brassica napus, and details about their physical and chemical characteristics, evolutionary relationships, chromosome locations, gene structures, three-dimensional protein structures, cis-acting promoter elements, and gene duplications were uncovered. The BnaMYB genes have undergone segmental duplications and positive selection pressure, according to evolutionary studies. The same subfamilies have similar intron–exon patterns and motifs, according to the genes’ structure and conserved motifs. Additionally, through cis-element analysis, many drought-responsive and other stress-responsive cis-elements have been found in the promoter regions of the BnaMYB genes. The expression of the BnaMYB gene displays a variety of tissue-specific patterns. Ten lignin-related genes were chosen for drought treatment. Our research screened four genes that showed significant upregulation under drought stress, and thus may be important drought-responsive genes. The findings lay a new foundation for understanding the complex mechanisms of BnaMYB in multiple developmental stages and pathways related to drought stress in rapeseed.
Mechanical Properties of Protein-Based Hydrogels Derived from Binary Protein Mixtures—A Feasibility Study
Authors: Haas Sandra , Hubbuch Jürgen
Published: February 2023

Hydrogels based on natural polymers such as proteins are considered biocompatible and, therefore, represent an interesting class of materials for application in the field of biomedicine and high-performance materials. However, there is a lack of understanding of the proteins which are able to form hydrogel networks by photoinduced dityrosine crosslinking as well as a profound knowledge of the formed network itself and the mechanisms which are responsible for the resulting mechanical properties of such protein-based hydrogels. In this study, casein, bovine serum albumin, α-amylase, and a hydrophobic elastin-like protein were used to prepare binary protein mixtures with defined concentration ratios. After polymerization, the mechanical properties of the resulting homopolymeric and copolymeric hydrogels were determined using rheological methods depending on the protein shares used. In additional uniaxial compression tests, the fracture strain was shown to be independent of the protein shares, while hydrogel toughness and compressive strength were increased for protein-based hydrogels containing casein.
Granular Disulfide-Crosslinked Hyaluronic Hydrogels: A Systematic Study of Reaction Conditions on Thiol Substitution and Injectability Parameters
Authors: Pérez Luis Andrés , Hernández Rebeca , Alonso José María , Pérez-González Raúl , Sáez-Martínez Virginia
Published: February 2023

Granular polymer hydrogels based on dynamic covalent bonds are attracting a great deal of interest for the design of injectable biomaterials. Such materials generally exhibit shear-thinning behavior and properties of self-healing/recovery after the extrusion that can be modulated through the interactions between gel microparticles. Herein, bulk macro-hydrogels based on thiolated-hyaluronic acid were produced by disulphide bond formation using oxygen as oxidant at physiological conditions and gelation kinetics were monitored. Three different thiol substitution degrees (SD%: 65%, 30% and 10%) were selected for hydrogel formation and fully characterized as to their stability in physiological medium and morphology. Then, extrusion fragmentation technique was applied to obtain hyaluronic acid microgels with dynamic disulphide bonds that were subsequently sterilized by autoclaving. The resulting granular hyaluronic hydrogels were able to form stable filaments when extruded through a syringe. Rheological characterization and cytotoxicity tests allowed to assess the potential of these materials as injectable biomaterials. The application of extrusion fragmentation for the formation of granular hyaluronic hydrogels and the understanding of the relation between the autoclaving processes and the resulting particle size and rheological properties should expand the development of injectable materials for biomedical applications.
A Practical Tool for the Assessment of Polymer Biodegradability in Marine Environments Guides the Development of Truly Biodegradable Plastics
Authors: Beiras Ricardo , López-Ibáñez Sara
Published: February 2023

Environmental persistence is one of the few shortcomings of plastic materials. As a consequence, alternative plastics labeled as compostable are replacing polyolefins in some commercial applications, such as food bags and trash bags. A rapid, high-throughput, and environmentally relevant method to assess the potential biodegradability in marine conditions is used to assess these materials already on the market, as well as novel bio-based polymers still in development. By fitting experimental data to a non-linear logistic model, ultimate biodegradability can be calculated without regard for incubation time. Whereas the commercial products show negligible or very low marine biodegradability, one of the novel materials exceeds the 20% biodegradation threshold relative to fully marine biodegradable PHB after 28 days. In addition, the sensitivity of the method can be enhanced and its duration reduced, at the expense of labor-demanding preconditioning of the microbial inoculum, by increasing the bacterial density in the incubation vessels. In contrast, pre-exposure of the inoculum to plastic, either in laboratory or field conditions, does not enhance the performance of the test.
WZB117 Decorated Metformin-Carboxymethyl Chitosan Nanoparticles for Targeting Breast Cancer Metabolism
Authors: De Anindita , Wadhwani Ashish , Sauraj  , Roychowdhury Parikshit , Kang Ji Hee , Ko Young Tag , Kuppusamy Gowthamarajan
Published: February 2023

The “Warburg effect” provides a novel method for treating cancer cell metabolism. Overexpression of glucose transporter 1 (GLUT1), activation of AMP-activated protein kinase (AMPK), and downregulation of mammalian target of rapamycin (mTOR) have been identified as biomarkers of abnormal cancer cell metabolism. Metformin (MET) is an effective therapy for breast cancer (BC), but its efficacy is largely reliant on the concentration of glucose at the tumor site. We propose a WZB117 (a GLUT1 inhibitor)-OCMC (O-carboxymethyl-chitosan)-MET combo strategy for simultaneous GLUT1 and mTOR targeting for alteration of BC metabolism. WZB117 conjugated polymeric nanoparticles were 225.67 ± 11.5 nm in size, with a PDI of 0.113 ± 0.16, and an encapsulation of 72.78 6.4%. OCMC pH-dependently and selectively releases MET at the tumor site. MET targets the mTOR pathway in cancer cells, and WZB117 targets BCL2 to alter GLUT1 at the cancer site. WZB117-OCMC-MET overcomes the limitations of MET monotherapy by targeting mTOR and BCL2 synergistically. WZB117-OCMC-MET activates AMPK and suppresses mTOR in a Western blot experiment, indicating growth-inhibitory and apoptotic characteristics. AO/EB and the cell cycle enhance cellular internalization as compared to MET alone. WZB117-OCMC-MET affects cancer cells’ metabolism and is a promising BC therapeutic strategy.
Home First: Stability and Opportunity in Out-of-Home Care
Authors: Segal Steven P.
Published: February 2023

In this report, the concept of “Home First” is introduced for those children who require long-term, non-kin placements. The term “Home First” connotes a placement engendering stability and continuity; this concept is introduced in conjunction with an evaluation of the historical, theoretical, and empirical evidence surrounding different forms of out-of-home placement, including group-care placements and foster family care. In light of these observations and studies, this report will argue that stability is a major factor, perhaps a necessary if not a sufficient condition, in successful child development. It will argue for the initiation of a new focus on the creation of long-term positive and stable residential placements within the out-of-home care system and show that such placements can and have contributed to the development of healthy, happy, and successful adulthoods. This report offers a bio-psycho-social perspective on child development in out-of-home care. It provides a brief overview of the multiple bio-psycho-social theoretical perspectives that inform us on the necessary role of stability in growth and development and the contribution of instability to dysfunction. This report considers stability in out-of-home care in relation to its associated outcomes and those factors believed to enhance or detract from these outcomes. It reviews the history of substitutive care provision for children and youth and the role of the “stability objective” in that history. Finally, it looks at how child welfare system priorities have influenced stability, and it offers some suggestions for ensuring more stable growth and development in child placement provision.
Investigating the Stability of the Hill of the Acropolis of Athens, Greece, Using Fuzzy Logic and Remote Sensing Techniques
Authors: Loupasakis Constantinos , Tsangaratos Paraskevas , Gatsios Theodoros , Eleftheriou Vasiliki , Parcharidis Issaak , Soupios Panteleimon
Published: February 2023

The main objective of this study was to investigate the stability of the Acropolis Hill, Greece, by developing a Rock Instability Model (RIM) based on fuzzy logic and remote sensing techniques. RIM aimed to identify locations on the rock formations of the Acropolis Hill that will potentially have instability issues due to the action of geomorphological factors, weathering and erosive processes. Six factors including lithology, slope angle, density of discontinuities, density of faults, density of surface runoff elements, and the orientation of the stratigraphy of the geological formations in relation to the orientation of the slope were considered as the most appropriate for implementing the proposed novel approach, with each variable classified and weighted by a fuzzy simple additive weighting method. Lithology and slope angle were considered the most significant variables that contributed to the overall stability of the Acropolis Hill. The outcomes of the RIM model were verified by remote sensing data and field observation, showing an agreement and high accuracy. From the satellite data analysis, it was concluded that for the entire Acropolis Hill, minor displacement rates were recorded, probably because of the extensive mitigation measures and consolidation works established in the recent past. Overall, the study highlighted the ability of the proposed methodology to be used as an alternative investigation tool in rock instability-related assessments valuable to land use planning and development, helping reduce the anticipated losses in highly susceptible zones.
Lidar Profiling of Aerosol Vertical Distribution in the Urbanized French Alpine Valley of Annecy and Impact of a Saharan Dust Transport Event
Authors: Chazette Patrick , Totems Julien
Published: February 2023

The vertical aerosol layering of the troposphere is poorly documented in mountainous regions, particularly in the Alpine valleys, which are influenced by valley and mountain winds. To improve our knowledge of particulate matter trapped in the Annecy valley, synergetic measurements performed by a ground-based meteorological Raman lidar and a Rayleigh-Mie lidar aboard an ultralight aircraft were implemented as part of the Lacustrine-Water vApor Isotope inVentory Experiment (L-WAIVE) over Lake Annecy. These observations were complemented by satellite observations and Lagrangian modeling. The vertical profiles of aerosol optical properties (e.g., aerosol extinction coefficient (AEC), lidar ratio (LR), particle linear depolarization ratio (PDR)) are derived from lidar measurements at 355 nm during the period between 13 and 22 June 2019. The background aerosol content with an aerosol optical thickness (AOT) of 0.10 ± 0.05, corresponding to local–regional conditions influenced by anthropogenic pollution, has been characterized over the entirety of Lake Annecy thanks to the mobile ultralight payload. The aerosol optical properties are shown to be particularly variable over time in the atmospheric column, with mean LRs (PDRs) varying between 40 ± 8 and 115 ± 15 sr (2 ± 1 and 35 ± 2%). Those conditions can be disturbed by air masses that have recirculated over the valley, as well as by contributions from neighboring valleys. We have observed an important disruption in the atmospheric aerosol profiles by the arrival of an exceptionally dry air mass (RH ~ 30%), containing aerosols identified as coming from the Great Western Erg (AOT ~ 0.5, LR = 65 ± 10 sr, PDR = 20–35%) in the Sahara. These desert dust particles are shown to influence the entire atmospheric column in the Annecy valley. Such an experimental approach, coupling upward and downward lidar and spaceborne observation/Lagrangian modelling, was shown to be of significant interest for the long-term monitoring of the evolution of aerosol loads over deep valleys. It allows a better understanding of the influence of dust storms in the presence of severe convective weather processes.
Seasonal Comparison of the Wildfire Emissions in Southern African Region during the Strong ENSO Events of 2010/11 and 2015/16 Using Trend Analysis and Anomaly Detection
Authors: Shikwambana Lerato , Kganyago Mahlatse
Published: February 2023

This study investigates the wildfire biomass-burning emission levels during strong El Niño–southern oscillation (ENSO) events of 2010–2011 (characterized by a strong La Niña event) and 2015–2016 (characterized by a strong El Niño event) over the southern African region. Specifically, the biomass-burning parameters of black carbon (BC), carbon monoxide (CO) and sulfur dioxide (SO2) were investigated. Of interest in the current study was the strong El Niño (2015–2016) and La Niña (2010–2011) events during the main fire seasons in southern Africa, i.e., June–July–August (JJA) and September–October–November (SON). Furthermore, the study looks at how meteorological parameters (temperature and precipitation) are influenced by the two strong ENSO events. The sequential Mann–Kendall (SQMK) test is used to study the long-term trends of the emission and meteorological parameters. Anomaly detection on the long-term emission trends and meteorological parameters are performed using the seasonal and trend decomposition loess (STL) and generalized extreme studentized deviate (GESD). Overall, the results show higher emission levels of SO2, CO, and BC during the JJA season compared to the SON season. The SQMK results show an increasing trend of SO2, CO, and BC over time, indicating an increase in the amount of biomass burning. The GESD showed significant anomalies for BC, SO2, and CO emanating from the two strong El Niño and La Niña events. On the other hand, no significant anomalies were detected for temperature and precipitation. The results in this study highlight the significant effect of strong ENSO events on wildfire emissions, thus retrospectively showing the potential effect of future events, especially in the context of climate change.
Lightweight Landslide Detection Network for Emergency Scenarios
Authors: Ge Xuming , Zhao Qian , Wang Bin , Chen Min
Published: February 2023

Landslides are geological disasters that can cause serious severe damage to properties and lead to the loss of human lives. The application of deep learning technology to optical remote sensing images can help in the detection of landslide areas. Traditional landslide detection models usually have complex structural designs to ensure accuracy. However, this complexity leads to slow detection, and these models often do not satisfy the rapid response required for the emergency monitoring of landslides. Therefore, we designed a lightweight landslide target detection network based on a CenterNet and a ResNet50 network. We replaced the BottleNeck in the backbone network of ResNet50 with a Ghost-BottleNeck structure to reduce the number of parameters in the model. We also introduced an attention mechanism module based on channel attention and spatial attention between the adjacent GhostModule modules to rich the landslide features. We introduced a lightweight multiscale fusion method in the decoding process that presented a cross-layer sampling operation for the encoding process based on Feature Pyramid Network. To down-sample from a low resolution to a high resolution and up-sample from a high resolution to a low resolution, thus skipping the medium-resolution levels in the path. We added the feature maps obtained in the previous step to the feature fusion. The Conv module that adjusts the number of channels in the multiscale feature fusion operation was replaced with the GhostModule to achieve lightweight capability. At the end of the network, we introduced a state-of-the-art Yolov5x as a teacher network for feature-based knowledge distillation to further improve the accuracy of our student network. We used challenging datasets including multiple targets and multiscale landslides in the western mountains of Sichuan, China (e.g., Danba, Jiuzhaigou, Wenchuan, and Maoxian) to evaluate the proposed lightweight landslide detection network. The experimental results show that our model satisfied landslide emergency requirements in terms of both accuracy and speed; the parameter size of the proposed lightweight model is 18.7 MB, namely, 14.6% of the size of the original CenterNet containing the ResNet50 network. The single image detection time is 52 ms—twice as fast as the original model. The detection accuracy is 76.25%, namely, 12% higher than that of the original model.
A Reinforcement Learning Handover Parameter Adaptation Method Based on LSTM-Aided Digital Twin for UDN
Authors: He Jiao , Xiang Tianqi , Wang Yixin , Ruan Huiyuan , Zhang Xin
Published: February 2023

Adaptation of handover parameters in ultra-dense networks has always been one of the key issues in optimizing network performance. Aiming at the optimization goal of effective handover ratio, this paper proposes a deep Q-learning (DQN) method that dynamically selects handover parameters according to wireless signal fading conditions. This approach seeks good backward compatibility. In order to enhance the efficiency and performance of the DQN method, Long Short Term Memory (LSTM) is used to build a digital twin and assist the DQN algorithm to achieve a more efficient search. Simulation experiments prove that the enhanced method has a faster convergence speed than the ordinary DQN method, and at the same time, achieves an average effective handover ratio increase of 2.7%. Moreover, in different wireless signal fading intervals, the method proposed in this paper has achieved better performance.
Design of MIR Dispersive Spectrograph System with Uncooled Microbolometer
Authors: Sunongbua Pattarapong , Aekram Suwan , Lertsiriyothin Weerasak
Published: February 2023

To make the mid-infrared (MIR) dispersive spectrograph a practical tool in industrial food processing lines, we designed a dispersive spectrograph system with an uncooled microbolometer focal plane array (FPA) detector for MIR spectral acquisition. To precisely regulate the angle of a rotatable grating to acquire the MIR spectrum, the spectral resolution and spatial resolution of the system were rigorously controlled to improve system performance. In the reflectance operation mode of the MIR dispersive spectrograph, the uncooled microbolometer FPA detector offered a maximum spectral resolution of 12 nm for the MIR, when a 300 grooves/mm blazed grating was used. Utilizing an optical parametric oscillator (OPO) pulse laser source, the wavelengths of the first-order diffraction were validated, and the system’s spectral resolution limit was determined. As a line-scanning source, a Globar broadband source was installed, and the USAF 1951 Resolution Calculator was used to establish the spatial resolution of the imaging spectrograph. Using NI LabView, the logical operational technique for controlling the MIR dispersive spectrograph was encoded into system firmware. The GUI and test results are thoroughly described.
Assessment of Various Multimodal Fusion Approaches Using Synthetic Aperture Radar (SAR) and Electro-Optical (EO) Imagery for Vehicle Classification via Neural Networks
Authors: Narayanan Ram M. , Wood Noah S. , Lewis Benjamin P.
Published: February 2023

Multimodal fusion approaches that combine data from dissimilar sensors can better exploit human-like reasoning and strategies for situational awareness. The performance of a six-layer convolutional neural network (CNN) and an 18-layer ResNet architecture are compared for a variety of fusion methods using synthetic aperture radar (SAR) and electro-optical (EO) imagery to classify military targets. The dataset used is the Synthetic and Measured Paired Labeled Experiment (SAMPLE) dataset, using both original measured SAR data and synthetic EO data. We compare the classification performance of both networks using the data modalities individually, feature level fusion, decision level fusion, and using a novel fusion method based on the three RGB-input channels of a residual neural network (ResNet). In the proposed input channel fusion method, the SAR and the EO imagery are separately fed to each of the three input channels, while the third channel is fed a zero vector. It is found that the input channel fusion method using ResNet was able to consistently perform to a higher classification accuracy in every equivalent scenario.
FPGA-Based Vehicle Detection and Tracking Accelerator
Authors: Zhai Jiaqi , Li Bin , Lv Shunsen , Zhou Qinglei
Published: February 2023

A convolutional neural network-based multiobject detection and tracking algorithm can be applied to vehicle detection and traffic flow statistics, thus enabling smart transportation. Aiming at the problems of the high computational complexity of multiobject detection and tracking algorithms, a large number of model parameters, and difficulty in achieving high throughput with a low power consumption in edge devices, we design and implement a low-power, low-latency, high-precision, and configurable vehicle detector based on a field programmable gate array (FPGA) with YOLOv3 (You-Only-Look-Once-version3), YOLOv3-tiny CNNs (Convolutional Neural Networks), and the Deepsort algorithm. First, we use a dynamic threshold structured pruning method based on a scaling factor to significantly compress the detection model size on the premise that the accuracy does not decrease. Second, a dynamic 16-bit fixed-point quantization algorithm is used to quantify the network parameters to reduce the memory occupation of the network model. Furthermore, we generate a reidentification (RE-ID) dataset from the UA-DETRAC dataset and train the appearance feature extraction network on the Deepsort algorithm to improve the vehicles’ tracking performance. Finally, we implement hardware optimization techniques such as memory interlayer multiplexing, parameter rearrangement, ping-pong buffering, multichannel transfer, pipelining, Im2col+GEMM, and Winograd algorithms to improve resource utilization and computational efficiency. The experimental results demonstrate that the compressed YOLOv3 and YOLOv3-tiny network models decrease in size by 85.7% and 98.2%, respectively. The dual-module parallel acceleration meets the demand of the 6-way parallel video stream vehicle detection with the peak throughput at 168.72 fps.
Research on Impact of IoT on Warehouse Management
Authors: Jarašūnienė Aldona , Čižiūnienė Kristina , Čereška Audrius
Published: February 2023

Automation and digitisation are the driving force of the Industrial Revolution 4.0. Industrial revolutions led to the mass production of goods, which increased the need for modern warehouses. Every year, the operation of warehouses becomes increasingly more complicated due to the increasing abundance of goods, thus the usual warehouse management strategies are no longer suitable. In order to cope with huge product flows, modern innovations should be used more extensively to manage these processes. Successful management will help provide quality service to rapidly changing business sectors. The Internet of Things (IoT) is a technology designed to process large amounts of data with maximum efficiency in real time. This technology can facilitate the implementation of smart identification, tracking, tracing, and management using radio frequency identification (RFID), infrared sensors, global positioning systems (GPS), laser scanners, and other detection tools. Such innovations as IoT have made a significant impact on warehousing operations. The aim of IoT is to perform administrative work, i.e., to efficiently manage warehouse data. IoT can be used to monitor and track goods, forecast demand trends, manage inventory, and perform other warehouse operations in real time. The key elements of a warehouse are sales and customer satisfaction. Implementing IoT improves financial performance, work productivity, and customer satisfaction. However, innovation requires additional investment in, for instance, implementation and maintenance. It is necessary to investigate how warehouse elements such as inventory accuracy or order processing time are affected by the internet of things in companies of different sizes. Research on the impact of IoT on warehouse management focuses on IoT advantages, disadvantages, mitigation risks, and the use of IoT in warehouses. The aim of this work is to research the impact of IoT on warehouse management in companies of different sizes and to determine whether the costs and benefits of IoT differ in the same scenario. As a result, the conceptual model for the adoption of IoT measures in warehouse companies was created, and its suitability was assessed by experts.
A Systematic Review of In-Vehicle Physiological Indices and Sensor Technology for Driver Mental Workload Monitoring
Authors: Sriranga Ashwini Kanakapura , Lu Qian , Birrell Stewart
Published: February 2023

The concept of vehicle automation ceases to seem futuristic with the current advancement of the automotive industry. With the introduction of conditional automated vehicles, drivers are no longer expected to focus only on driving activities but are still required to stay alert to resume control. However, fluctuations in driving demands are known to alter the driver’s mental workload (MWL), which might affect the driver’s vehicle take-over capabilities. Driver mental workload can be specified as the driver’s capacity for information processing for task performance. This paper summarizes the literature that relates to analysing driver mental workload through various in-vehicle physiological sensors focusing on cardiovascular and respiratory measures. The review highlights the type of study, hardware, method of analysis, test variable, and results of studies that have used physiological indices for MWL analysis in the automotive context.
Beef Quality Classification with Reduced E-Nose Data Features According to Beef Cut Types
Authors: Feyzioglu Ahmet , Taspinar Yavuz Selim
Published: February 2023

Ensuring safe food supplies has recently become a serious problem all over the world. Controlling the quality, spoilage, and standing time for products with a short shelf life is a quite difficult problem. However, electronic noses can make all these controls possible. In this study, which aims to develop a different approach to the solution of this problem, electronic nose data obtained from 12 different beef cuts were classified. In the dataset, there are four classes (1: excellent, 2: good, 3: acceptable, and 4: spoiled) indicating beef quality. The classifications were performed separately for each cut and all cut shapes. The ANOVA method was used to determine the active features in the dataset with data for 12 features. The same classification processes were carried out by using the three active features selected by the ANOVA method. Three different machine learning methods, Artificial Neural Network, K Nearest Neighbor, and Logistic Regression, which are frequently used in the literature, were used in classifications. In the experimental studies, a classification accuracy of 100% was obtained as a result of the classification performed with ANN using the data obtained by combining all the tables in the dataset.
Video-based Goniometer Applications for Measuring Knee Joint Angles during Walking in Neurological Patients: A Validity, Reliability and Usability Study
Authors: Parati Monica , Gallotta Matteo , De Maria Beatrice , Pirola Annalisa , Morini Matteo , Longoni Luca , Ambrosini Emilia , Ferriero Giorgio , Ferrante Simona
Published: February 2023

Easy-to-use evaluation of Range Of Motion (ROM) during walking is necessary to make decisions during neurological rehabilitation programs and during follow-up visits in clinical and remote settings. This study discussed goniometer applications (DrGoniometer and Angles - Video Goniometer) that measure knee joint ROM during walking through smartphone cameras. The primary aim of the study is to test the inter-rater and intra-rater reliability of the collected measurements as well as their concurrent validity with an electro-goniometer. The secondary aim is to evaluate the usability of the two mobile applications. A total of 22 patients with Parkinson’s disease (18 males, age 72 (8) years), 22 post-stroke patients (17 males, age 61 (13) years), and as many healthy volunteers (8 males, age 45 (5) years) underwent knee joint ROM evaluations during walking. Clinicians and inexperienced examiners used the two mobile applications to calculate the ROM, and then rated their perceived usability through the System Usability Scale (SUS). Intraclass correlation coefficients (ICC) and correlation coefficients (corr) were calculated. Both applications showed good reliability (ICC > 0.69) and validity (corr > 0.61), and acceptable usability (SUS > 68). Smartphone-based video goniometers could be used to assess the knee ROM during walking in neurological patients, because of their acceptable degree of reliability, validity and usability.
Examination of Condensation Liquid Formation in Istanbul Natural Gas Distribution Network
Authors: Aytaş Eyüp Numan , Akkaya Ali Volkan
Published: February 2023

In this study, the formation of natural gas liquid in gas distribution lines, particularly at regional stations, service boxes, customer installations, and gas meters, was investigated. The study aims to address the problems associated with natural gas liquid formation, such as interruption of supply and decreased efficiency of combustion devices. The indirect measurement of the hydrocarbon dew point was analyzed using C6+ chromatograph data, and the model based on directly measured C6+ data were converted into C6/C7/C8 data by four different methods. As distinct from studies in the literature, this study experimentally determines the distribution of heavy hydrocarbons from C9 to C19 based on indirect methods for acquiring C8+ data and direct measurement of C6+ data. The hydrocarbon dew point temperature was calculated using the Peng–Robinson (PR) and Soave–Redlich–Kwong (SRK) equations of state. The results of the analysis performed on two city gate stations showed that the critical temperatures were 4.21 °C at a pressure of 10.81 bar and 8.27 °C at a pressure of 11.25 bar, respectively. These values were obtained from a model designed to determine the dew point temperature in the area where natural gas liquid formation was most prevalent. The experimental analysis and indirect measurements indicated the occurrence of a two-phase gas–liquid formation.
Multi-Task Classification of Physical Activity and Acute Psychological Stress for Advanced Diabetes Treatment
Authors: Abdel-Latif Mahmoud , Askari Mohammad Reza , Rashid Mudassir M. , Park Minsun , Sharp Lisa , Quinn Laurie , Cinar Ali
Published: February 2023

Wearable sensor data can be integrated and interpreted to improve the treatment of chronic conditions, such as diabetes, by enabling adjustments in treatment decisions based on physical activity and psychological stress assessments. The challenges in using biological analytes to frequently detect physical activity (PA) and acute psychological stress (APS) in daily life necessitate the use of data from noninvasive sensors in wearable devices, such as wristbands. We developed a recurrent multi-task deep neural network (NN) with long-short-term-memory architecture to integrate data from multiple sensors (blood volume pulse, skin temperature, galvanic skin response, three-axis accelerometers) and simultaneously detect and classify the type of PA, namely, sedentary state, treadmill run, stationary bike, and APS, such as non-stress, emotional anxiety stress, mental stress, and estimate the energy expenditure (EE). The objective was to assess the feasibility of using the multi-task recurrent NN (RNN) rather than independent RNNs for detection and classification of AP and APS. The multi-task RNN achieves comparable performance to independent RNNs, with the multi-task RNN having F1 scores of 98.00% for PA and 98.97% for APS, and a root mean square error (RMSE) of 0.728 calhr.kg for EE estimation for testing data. The independent RNNs have F1 scores of 99.64% for PA and 98.83% for APS, and an RMSE of 0.666 calhr.kg for EE estimation. The results indicate that a multi-task RNN can effectively interpret the signals from wearable sensors. Additionally, we developed individual and multi-task extreme gradient boosting (XGBoost) for separate and simultaneous classification of PA types and APS types. Multi-task XGBoost achieved F1 scores of 99.89% and 98.31% for the classification of PA types and APS types, respectively, while the independent XGBoost achieved F1 scores of 99.68% and 96.77%, respectively. The results indicate that both multi-task RNN and XGBoost can be used for the detection and classification of PA and APS without loss of performance with respect to individual separate classification systems. People with diabetes can achieve better outcomes and quality of life by including physical activity and psychological stress assessments in treatment decision-making.