bluuebunny/crossref_metadata_2025 huggingface dataset:
Utilização do método AQPC como ferramenta qualitativa em restaurantes institucionais
Authors: Araújo Flaviane Dantas de , Lira Natália de Carvalho Cordeiro , Clemente Heleni Aires , Oliveira Vanessa Teixeira de Lima
Published: November 2023

Objetivo: identificar a aplicabilidade do método Avaliação Qualitativa das Preparações do Cardápio – AQPC, como ferramenta de avaliação qualitativa em restaurantes institucionais. Métodos: realizou-se uma busca nos portais eletrônicos do Periódicos CAPES e Google Acadêmico, por meio do descritor AQPC. Os artigos foram selecionados a partir da leitura de dois avaliadores; foram incluídos apenas os artigos científicos publicados no período específico de 2010 a 2021 e que apresentassem a questão norteadora do estudo, excluindo-se os estudos que não estivessem dentro do objetivo do critério de inclusão. Resultados: Dos 1037 artigos estudados, selecionou-se um total de 21 que comtemplaram os critérios de inclusão, sendo eles eficientes com a utilização do método em restaurantes institucionais e, ainda assim, o método evidenciou ser uma ferramenta possível de identificar e solucionar falhas encontradas nos cardápios. Conclusão: Desse modo, é possível concluir que a ferramenta AQPC apresenta uma aplicabilidade útil para avaliação qualitativa de cardápios em restaurantes institucionais, de fácil utilização e de grande importância para instruir e auxiliar o nutricionista no planejamento de cardápios e nas diversas dimensões relacionadas à nutrição.
IDENTIFICATION OF MENTAL HEALTH WORKERS IN LAMONGAN WITH MACHINE LEARNING
Authors: Wardhani Retno , Nafi'iyah Nur
Published: November 2023

COVID-19 has caused a global health crisis, with increasing numbers of people being infected and dying every day. Various countries have tried to control its spread by applying the basic principles of social aggregation and testing. Experts agree that physical and mental health are interrelated and must be managed and balanced. The government must pay attention to balancing physical and mental health during a pandemic. The Ministry of Health has issued a guidebook for Mental Health and Psychosocial Support (DKJPS) during the COVID-19 pandemic. Based on the mental health conditions of the community or medical personnel, we are trying to create a system for mental health analysis for medical professionals based on the results of questionnaires using the machine learning method (Naive Bayes, Decision Tree, k-NN, SVM, Backpropagation, and Logistic Regression). A total of 24 question questionnaires were submitted to respondents. This study aimed to create a machine learning model (Naive Bayes, Decision Tree, k-NN, SVM, Backpropagation, and Logistic Regression) to identify the mental health of medical personnel during the COVID-19 pandemic. The results of this study are machine learning models that have the highest accuracy in identifying health workers' mental health and are 100% SVM.
SSNMR confirms silicate ion substitution in the apatitic structure of 0.8wt% Si hydroxyapatite
Authors: Mafina Marc-Krystelle , Wilson Rory M. , Rees Gregory J. , Gierth Peter , Sullivan Alice C. , Hing Karin A.
Published: November 2023

This study investigates the structural location of silicon present in ‘silicate-substituted’ apatite. It has been hypothesized that silicon is present in the form of silicate groups site-specifically substituted in the hydroxyapatite lattice for phosphate groups, or that there may be an amorphous silicon-rich phase in the vicinity of the grain boundaries. Solid-state nuclear magnetic resonance (SSNMR) spectroscopy was carried out to view the elemental interactions using phosphorus (31P) and silicon (29Si) probes to confirm or refute the presence of silicate groups in relation to phosphate groups in the bulk material structure. The analysis was performed on stoichiometric hydroxyapatite (HA) and silicate-substituted hydroxyapatite (SA) with a nominal silicon content of 0.8wt%, in as-precipitated, calcined (700°C), and sintered (1,250 and 1,300°C, respectively) powder forms. XRD confirmed all forms of powder were phase pure. FTIR confirmed both hydroxyl and phosphate group functionalities in all forms of HA and SA, while silicate group functionality was only observed in all forms of SA. SSNMR using 31P- and 29Si-coupled probes demonstrated that as the crystallinity of the powders increased from the precipitate to the sintered form, the signal associated with the presence of a silicate group in the phosphate environment developed as the crystal structure became more ordered. These results support the hypothesis that in SA containing 0.8wt% silicon, silicate groups are site-specifically substituted in the hydroxyapatite lattice for phosphate groups. This observation may be key to understanding the mechanisms by which the introduction of 0.8wt% silicon enhances bone regeneration in apatitic bone graft substitute materials.
Long-Term Effects of Plastic Mulch in a Sandy-Loam Soil Cultivated with Blueberry in Southern Portugal
Authors: Pedra Fiilipe , Inácio Maria L. , Fareleira Paula , Oliveira Pedro , Pereira Pablo , Carranca Corina
Published: November 2023

Abstract: Agriculture uses plastic products for containers, packaging, tunnels, drip irrigation tub-ing, mulches. Large amounts of plastics are used as mulches on the soil surface for vegetable pro-duction (tomato, cucumber, watermelon, strawberry, vine) to reduce the weed competition, in-crease water and fertilizer use efficiency and enhance crop yield. Portugal uses around 4,500 t/year of polyethylene plastic to cover approximately 23,000 ha of agricultural land and only a small amount is recovered for recycling or secondary uses because of dirt with soil, vegetation, pesticide and fertilizers. Cleaning and decontaminating polyethylene mulch are costly and commercial technology is often not accessible nor economically viable in the current economic Portuguese situation. Most plastic mulch is composed of polyethylene that degrades slowly and produces a large quantity of residues in soil with negative impact in the environment. In the present study, the effects of long-term cultivation of blueberry using green 100% high density polyethylene mulch, in the south Portugal were evaluated for soil chemical and biological changes. High density green plastic mulch did not contaminate the topsoil with di(2-ethylhexyl) phthalate and heavy metals, buttotal nitrogen and organic carbon concentrations, electric conductivity and microbial activity were reduced in the planting row compared with bare soil, without mulching. Further-more, the presence of plastic mulch did not affect negatively the presence of nematodes, and the Rhabditida (bacterial feeders) increased in the planting and covered row.
Locus of Control and Self‐Directed Learning Readiness of Nursing Students during the COVID‐19 Pandemic: A Cross‐Sectional Study from Saudi Arabia
Authors: Alkorashy Hanan A. , Alotaibi Hanan A.
Published: November 2023

Background: Coronavirus disease (COVID-19) has caused one of the worst global pandemics in recent decades. It has disrupted education systems worldwide, leading to a forced shift from traditional face-to-face to blended or fully distanced learning, requiring a higher level of student readiness for self-directed learning (SDL) and a more internal locus of control (LOC). Objective: This study explored the relationship between locus of control and level of readiness for SDL among Saudi nursing students and whether the COVID-19 pandemic has impacted this relationship. Methods: a cross-sectional correlational descriptive study was conducted to survey 277 Saudi nursing students enrolled in the bachelor program in one of the reputable universities in Saudi Arabia. An E-questionnaire containing two scales, the Self-Directed Learning Readiness Scale for Nursing Education, and the Locus of Control Scale, was used to collect data in addition to the selected participants’ characteristics. Results: Nursing students had a moderate-to-low level of readiness for SDL (mean = 144.0), and the majority had an external LOC. There was a significant association between locus of control and level of readiness for self-directed learning (r = 0.19*, p = 0.001), and the internal locus of control was more significantly associated with self-directed learning (r = 0.22*, p = 0.0001) than with external locus of control. Conclusion: The study findings indicate a propensity of respondents towards an external locus of control, whereas the majority of the respondents reported low to moderate levels of readiness across all dimensions of self-directed learning. This study was not registered.
Effect of Hole Size on Open Hole Tensile (OHT) and Flexural Strength (OHF) of Aramid-Basalt Fibre Reinforced Polymer Composites
Authors: Fernandes Oshin , Dutta Jyoti , Pai Yogeesha , G T Mahesha , Baliga Ravishanker
Published: November 2023

The open hole tensile and flexural test of composites holds immense importance in aerospace and structural engineering. These tests provide critical insights into how composites perform under real-world conditions, allowing for the development of materials that meet rigorous standards, thereby ensuring the safety and durability of aircraft and other applications. This study investigates the influence of hole size on the open hole tensile (OHT) and flexural properties (OHF) of plane woven aramid/epoxy (AFRP), basalt/epoxy (BFRP), and aramid-basalt/epoxy (ABFRP) sandwiched laminates. Specimens with three different hole sizes viz., 4 mm, 6 mm, 8 mm were prepared and tested according to ASTM D5766 and ASTM D7264 for OHT and OHF performance respectively. Results indicated that the hybridization of aramid-basalt layers in a sandwich lay up significantly improved the mechanical performance when compared to only aramid laminate. However, with the increase in hole size the mechanical properties declined irrespective of the material. Basalt fibres showed higher hole sensitivity under tensile loading due to its brittle fracture mechanism while aramid fibres exhibited higher hole sensitivity under flexural loading which can be attributed to its the poor compressive strength. The effect of hole size on the damage mechanism has also been highlighted through scanning electron microscope (SEM). Major failure modes observed are delamination around the hole edges, ductile and brittle fibre fractures, and delamination.
Fabrication of Pullulan/Polyvinyl Alcohol Core-Shell Nanofibers for Cancer Treatment and Drug Delivery
Authors: Tören Elçin , Khan Muhammad , Militky Jirí , Mazari Adnan Ahmed , Wiener Jakub
Published: November 2023

This article discusses the fabrication of pullulan/polyvinyl alcohol (PVA) and PVA blends as carrier polymers for drug delivery. This study utilized coaxial electrospinning to encapsulate doxorubicin (DOX), a common anticancer drug, within nanofibers, which helped mitigate the adverse effects of DOX on normal cells. The study also demonstrated that the coaxial electrospinning technique using PVA/pullulan cores was effective in inhibiting the attachment and proliferation of HeLa cells, a type of cervical cancer cell. The use of pullulan/PVA and PVA blends as carrier polymers in conjunction with coaxial electrospinning could provide a safe and effective drug delivery system for the treatment of cervical and other solid malignancies. The study concluded that nanofibers showed promising results in inhibiting the growth of HeLa cells, indicating their potential as safe and effective drug delivery systems for treating cervical cancer and other solid malignant tumors.
Machine Learning Models for Prediction of Gender Based on Lumbar Vertebral Morphometry
Authors: Diac Madalina Maria , Toma Gina Madalina , Damian Simona Irina , Fotache Marin , Romanov Nicolai , Tabian Daniel , Sechel Gabriela , Scripcaru Andrei , Hancianu Monica , Iliescu Diana Bulgaru
Published: November 2023

Identifying skeletal remains has been and will remain a challenge for forensic doctors and forensic anthropologists, especially in disasters with multiple victims or skeletal remains in an advanced stage of decomposition. This study proposes a machine learning method to determine gender starting from morphometric analysis of L1-L5 lumbar vertebrae in a modern Romanian population. The purpose of the present study was to observe whether by using the ML method there is a good predictability of gender in forensic identification based on parameters obtained from the metric analysis of the lumbar spine specific to the Romanian population. This paper offers two models of ML, RF and XGB, each with its own characteristics, and presenting different performance, random forest having the best. For both, we used two metrics (accuracy and roc_auc), the latter being the most used to highlight model performance. The L1-L5 lumbar vertebrae exhibit sexual dimorphism and can be used in gender estimation. Machine learning is more accurate in determining gender than discriminatory function analysis.
CRISPR as Genome Editing Technique in Fruit Trees Breeding
Authors: Martín-Valmaseda Marina , Devin Sama Rahimi , Ortuño-Hernández Germán , Pérez-Caselles Cristian , Mahdavi Sayyed Mohammad Ehsan , Bujdoso Geza , Salazar Juan Alfonso , Martínez-Gómez Pedro , Alburquerque Nuria
Published: November 2023

The methods used to introduce CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats)/Cas-mediated genome editing into fruit species, as well as the impacts of the application of this technology to activate and knock out of target genes in different fruit trees species including tree development, yield, fruit quality, and tolerance to biotic and abiotic stresses have been firstly described in this review. The application of this gene editing technology could allow the development of new generations of fruit crops with improved traits by targeting different genetic segments or even could facilitate the introduction of traits in elite cultivars without changing other traits. However, at this moment, the scarcity of efficient regeneration and transformation protocols in some species, the fact that many of those procedures are the genotype-dependent or the convenience of segregating the transgenic parts of the CRISPR system represent the main handicaps limiting the potential of genetic editing techniques for fruit trees. Finally, latest news on the legislation and regulations about the use of plants modified through CRISPR/Cas systems has been also discussed.
Structure Overview of Herpesvirus Tegument Proteins
Authors: He Hui-Ping , Gao Song
Published: November 2023

Herpesviridae is a family of enveloped double-stranded DNA viruses that cause a wide range of diseases in hosts. Among the various components of herpesvirus particles, tegument proteins residing between the envelop and nucleocapsid play crucial roles in viral replication, immune evasion, and modulation of host cellular pathways. Understanding the three-dimensional structure of herpesvirus tegument proteins help to reveal the molecular mechanism underlying the crosstalk with other viral and cellular components, and thus is crucial for the investigation of their biological and pathological functions. In this review, we summarize the current knowledge of the structural features of herpesvirus tegument proteins, highlighting the structure-based functional implications, including the potential as targets for antiviral drug development.
Study of Concrete Reinforcement with the Addition of Pozolanica against the Penetration of Chlorites through Electrochemical Impedance Spectroscopy
Authors: Domínguez Anilé Ossorio , Filho Romildo Dias Toledo , Gomes José Antônio da Cunha Ponciano , Silva Ralph dos Santos , Alencar Eduardo , Barbosa da Silva Adriana
Published: November 2023

The present work analyzes the behavior in terms of corrosion resistance of three reinforced concrete formulations over a period of 1 year. The samples were accompanied by creating a monitoring methodology using the Electrochemical Impedance Spectroscopy (EIE) technique, working only with the real component over time. Three mixtures were used, one conventional without pozzolanic addition (REF) and two others with pozzolanic additions, rice husk ash (RCA) and metakaolin (MK). Prototypes were created and exposed to the action of a 165g/l NaCl sodium chloride solution. The characterization of the materials was carried out by determining the chloride diffusion profile (ASTM 1556), analyzing images using tomography and with the support of analytical techniques such as x-ray fluorescence and x-ray diffraction. The monitoring methodology using the EIE demonstrated the positive effect of the insertion of pozzolans, rice husk ash (RCA) and metakaolin (MK), by delaying the process of chloride diffusion in the concrete, resulting in greater resistance to corrosion. The EIE also showed that the active mineral addition in concrete, of aluminum-silicic composition (MK), had a predominant protective effect on the steel//concrete interface against the attack of chloride ions.
Generalized SmartScan: An Intelligent LPBF Scan Sequence Optimization Approach for 3D Part Geometries
Authors: He Chuan , Bugdayci Bircan , Okwudire Chinedum
Published: November 2023

Laser powder bed fusion (LPBF) is an additive manufacturing technique that is gaining popularity for producing metallic parts in various industries. However, parts produced by LPBF are prone to residual stress, deformation, cracks and other quality defects due to uneven temperature distribution during the LPBF process. To address this issue, in prior work, the authors have proposed SmartScan, a method for determining laser scan sequence in LPBF using a model-based and optimization-driven approach, rather than using heuristics, and applied it to simple 2D geometries. This paper presents a generalized SmartScan methodology that is applicable to arbitrary 3D geometries. This is achieved by: (1) expanding the thermal model and optimization approach used in SmartScan to multiple layers; (2) enabling SmartScan to process shapes with arbitrary contours and infill patterns within each layer and (3) providing SmartScan with global foresight to make it less myopic in its optimization. Sample 3D parts are printed using the proposed generalized SmartScan and compared to those printed using standard heuristic scan sequences. Reductions of up to 93% in temperature inhomogeneity, 87% in residual stress, and 26% in maximum deformation were observed, without significantly sacrificing print speed. However, SmartScan was found to cause minor (<5%) to significant (up to 20%) increases in surface roughness compared to the heuristic approaches, depending on the scan pattern used.
Validation of GSMaP Data in Depicting Precipitation Climatology and Climate Variability in China
Authors: Wang Zunya , Li Qingquan
Published: November 2023

In this analysis, we assess the performance of GSMaP-GNRT6 data in capturing precipitation climatology and climate variability across China from 2001 to 2020. The evaluation involves comparing four precipitation indices of accumulated precipitation, the number of rainy days, rainstorm days, and precipitation maximum with the daily precipitation data from 2419 stations in China. The findings reveal that the GSMaP data effectively captures the overall spatial distribution of annual, summer, and monthly precipitation. However, it exhibits minor limitations in accurately depicting the spatial distribution of the number of rainy days from July to September and the precipitation maximum during wintertime in eastern China. While the GSMaP data depicts a coherent annual cycle consistent with the station observations, a general underestimation is observed. Notably, the GSMaP data presents a much smoother annual cycle in precipitation maximum. Regarding accumulated precipitation, the number of rainstorm days, and precipitation maximum, the GSMaP data shows an almost consistent interannual variation and increasing trends, aligning with station observations. However, it is noteworthy that the magnitude of the increasing trend based on the GSMaP data is greater, especially entering the early 21st century. Conversely, a significant discrepancy in the annual variation and an almost opposite changing trend are noticed in the number of rainy days between the GSMaP data and station observations.
The Concept of Child-Centered Care in Healthcare: A Scoping Review
Authors: Carter Bernie , Young Sarah , Ford Karen , Campbell Steven
Published: November 2023

Although child-centred care is increasingly referred to within the nursing literature, a clear definition of child-centred care and clarity around the concept is yet to be achieved. The objectives of this review were to examine: 1) What constitutes the concept of child-centred care in healthcare? 2) How has the concept of child-centred care developed? 3) What is the applicability of child-centred care and what are its limitations? and 4) How does the concept of child-centred care benefit and inform children’s healthcare? In total, 2984 papers were imported for screening, following removal of duplicates and screening, 21 papers were included in the scoping review.The findings suggest that child-centred care is an emerging, ambiguous, poorly defined concept; no clear consensus exists about what constitutes child-centred care. Although it seems antithetical to argue against child-centred care, little robust evidence was identified that demonstrates the impact of, and benefit from, child-centred care. If child-centred care is to be a sustainable, convincing model to guide practice and compete with other models of care it needs to establish robust evidence of its effectiveness, impact on children and their families as well as the wider impacts on the healthcare system.
Screening of Diploid Wild Potatoes Pollen Traits under Heat Stress
Authors: Nicolao Rodrigo , Bashir Ikram , Castro Caroline Marques , Heiden Gustavo
Published: November 2023

Screening of pollen traits in diploid wild potatoes (Solanum sect. Petota, Solanaceae) is desirable to develop heat-tolerant potato (S. tuberosum) cultivars. To accomplish this goal requires exploring potato genetic resources that are conserved in genebanks. The goal of this study was to assess pollen viability and 2n pollen production of the diploid potato wild relatives under heat stress condition. We assessed pollen viability and size of nine potato accessions conserved at the Embrapa Potato Gene Bank, including S. chacoense (BRA 00167447-2, BRA 00167017-3, BRA 00167023-1, BRA 00167028-0), S. commersonii (BRA00167007-4, BRA00167420-9, BRA00183760-8), and S. malmeanum (BRA 00183755-8), along with a control accession from the cultivated species S. tuberosum (BRA 00167251-8). The plant accessions were cultivated in different growth chambers, simulating both control temperature (ranging from 14 to 27°C) and supraoptimal temperature conditions (ranging from 24 to 34°C). At heat stress, the accessions BRA 00167251-8 did not bloom, and BRA 00167023-1 did not produce pollen. The remaining accessions did not exhibit a significant reduction in pollen viability as the temperature increased. Pollen viability at the control temperature had the lowest value in BRA-00167420-9 (S. commersonii) with 68.5% and the highest in BRA 00183755-8 (S. malmeanum) with 100%. At the supraoptimal temperature the lowest value was in BRA 00167420-9 (S. commersonii) with 54.5% and the highest in BRA 00183755-8 (S. malmeanum). The average of pollen size was 20 μm in all wild potato genotypes, and the increase of temperature did not lead to 2n pollen production. Estimated Genotypic Coefficient of Variation (GCV) was lower than Phenotypic Coefficient of Variation (PCV) for pollen viability. The observed heritability values ranged from 58.82% in BRA00167007-4 to 91.32% in BRA 00183755-8. Our results highlight the genetic variability available in wild potato germplasm concerning pollen viability under heat stress. Furthermore, these first insights offer valuable guidance for ongoing and future endeavors in diploid potato breeding.
Memory Recovery Effect of New Bioactive Innovative Combination in Rats with Experimental Dementia
Authors: Tancheva Lyubka , Kalfin Reni , Minchev Borislav , Uzunova Diamara , Tasheva Krasimira , Tsvetanova Elina , Georgieva Almira , Alexandrova Albena , Stefanova Miroslava , Solak Ayten , Lazarova Maria , Hodzhev Yordan , Grigorova Valentina , Yarkov Dobri , Petkova-Kirova Polina
Published: November 2023

Alzheimer’s disease manifests itself as a complex pathological condition with neuroinflammation, oxidative stress and cholinergic dysfunction being a few of the many pathological changes. Due to the complexity of the disease current therapeutic strategies aim at a multitargeted approach often relying on a combination of sub-stances with versatile and complementary effects. In the present study, unique combination of α-lipoic acid, citicoline, extracts of leaves from olive tree and green tea, Vitamin D3, selenium and an immune supporting complex was tested in a scopolamine-induced dementia in rats. Using behavioral and biochemical methods we assessed the effects of this combination on learning and memory, and elucidated the mechanisms under-lying its effects. Our results showed that as compared to the components, experimental combination was most efficient in improving short- and long-term memory assessed by the step-through method as well as spatial memory, assessed by T-maze and Barnes maze underlying decrease in AChE activity and LPO, in-creases in SOD activity in cortex; activities of catalase and GPx, levels of BDNF and pCREB in the hippocam-pus. No significant histopathological changes or blood parameter changes were detected, making the experi-mental combination an effective and safe candidate in a multitargeted treatment of AD.
Chondroitin Sulfate/Dermatan Sulfate Hybrid Chains from Swim Bladder: Isolation, Structural Analysis, and Anticoagulant Activity
Authors: Yao Yue , Tang Hao , Ma Haiqiong , Liu Zidong , Huang Jinwen , Yang Xiufen , Zhao Longyan , Yuan Qingxia
Published: November 2023

Glycosaminoglycans (GAGs) with unique structures from marine animals show intriguing pharmacological activities and negligible biological risks, providing more options for us to explore safer agents. Swim bladder is a tonic food and folk medicine, and its GAGs show good anticoag-ulant activity. In this study, two GAGs SJG-1.0 and GMG-1.0 have been extracted and isolated from the swim bladder of Sphyraena jello and Gadus morhua. The physicochemical properties, pre-cise structural characteristics, and anticoagulant activities of these GAGs were determined. The analysis results of the SJG-1.0 and GMG-1.0 showed that they were chondroitin sulfate (CS)/dermatan sulfate (DS) hybrid chains with molecular weights of 109.32 kDa and 123.13 kDa, respectively. They were mainly composed of the repeating disaccharide unit of -{IdoA-α1,3-GalNAc4S-β1,4-}- (DS-A). The DS-B disaccharide unit of -{IdoA2S-α1,3-GalNAc4S-β1,4-}- also existed in both SJG-1.0 and GMG-1.0. SJG-1.0 had a higher proportion of CS-O disaccharide unit -{-GlcA-β1,3-GalNAc-β1,4-}-, while GMG-1.0 contained higher proportion of CS-E disaccha-ride unit -{-GlcA-β1,3-GalNAc4S6S-β1,4-}-. The disaccharide compositions of the GAGs varied in a species-specific manner. Anticoagulant activity assay revealed that both SJG-1.0 and GMG-1.0 had potent anticoagulant activity, which can significantly prolong activated partial thrombosis time. GMG-1.0 also can prolong the thrombin time. SJG-1.0 showed no intrinsic tenase inhibition ac-tivity, while GMG-1.0 can obviously inhibit intrinsic tenase with EC50 of 58 nM. Their significantly different anticoagulant activities may be due to their different disaccharide structural units and proportions. These findings suggested that the swim bladder CS/DS hybrid chains with well-defined structure may be safer anticoagulants with low bleeding risk.
Fabrication of Lignin/Pbat Biodegradable Plastics Films via Reactive Extrusion and Their Thermal, Mechanical and Water Absorption Properties
Authors: Dong Yanyan , Gao Weichang , Luo Zhenbao , Cai Heqing , Richel Aurore , Liu Jialei , Zhang Yining , Zhen Zhichao , He Wenqing , Liu Qi
Published: November 2023

Biodegradable and renewable plastic films have been regarded as promising alternative green materials to achieve the substitution polythene (PE)films to reduce plastic pollution. Poly (butylene adipate-co-terephthalate) (PBAT) is a kind of biodegradable polyester, which is widely used in the production of biodegradable mulching films. However, the high cost of PBAT limited it applications. Thus, lignin, one of the most abundant biomass resources was incorporated into PBAT matrix in the present work. A series of Lignin/PBAT biodegradable plastics films with different Lignin/PBAT weight ratios (0.00 %-5.00 %) were successfully fabricated using twin screw and twin roll extruders. The chemical compositions, morphologies, thermal stabilities, mechanical properties, and barrier properties of samples were characterized by XRD, FTIR, TG/DSC, mechanical testing machine, and WVTR, respectively. Results show that the corporation of lignin into PBAT matrix could lead to improved thermal stabilities, mechanical properties and barrier properties of films even after Xenon lamp aging process, especially when Lignin/PBAT weight ratio is 1.00 % in the present work. This work provides a very promising approach for fabrication of biodegradable plastics films with low cost, enhanced mechanical properties and barrier properties, the as-prepared samples may have potential applications in agricultural or food packaging materials.
Data Prediction in Datasets of Internet of Things with Recurrent Neural Networks
Authors: Kniess Janine , Oliveira Samuel Silva de
Published: November 2023

The emergence of the Internet of Things (IoT) has led to the deployment of various types of sensors in many application fields, including environment monitoring, smart cities, health, industries, and others. The increasing number of connected devices has led to the creation of massive quantities of data that need to be analyzed. Typically, this data is ordered by time, as a time series. In this context, this paper presents a time series prediction model based on Recurrent Neural Networks in order to predict one step ahead. Result obtained through five Internet of Things monitoring datasets, showed that the Recurrent Neural Network obtained better performance that the prediction methods, ARIMA and SVM.
A Novel Index of Agricultural Drought Measurement: Soil Moisture and Evapotranspiration Revealed Drought Index (SERDI)
Authors: hamarash hushiar , RASUL Azad , HAMAD Rahel
Published: November 2023

Droughts are a common occurrence in various climates and are primarily caused by a prolonged decrease in rainfall. Several factors contribute to droughts, including temperature, wind speed, relative humidity, rainfall timing, amount, and intensity during the growing season. The objective of this study is to establish a new index, named soil moisture and evapotranspiration revealed drought index (SERDI), for displaying dry and wet conditions based on combining both soil moisture and evapotranspiration (Penman-Monteith) to improve drought early warning and its severity globally. For validation of the SERDI with other indices such as LST, VHI, NDVI, and NDWI, different ways used such as R-square, RMSE, MAPE, and P-value to estimate the accuracy, variability of data, the forecast conditions, and how the significance of data. The results showed that the low RMSE and high r2 were found between SERDI with LST and VHI. In contrast, the low R- square and high RMSE were between SERDI with NDVI and NDWI in most of the semi-arid areas. Furthermore, most of the semi-arid areas from Iran, Iraq, Syria, Jordan, and Israel experienced moderate and severe dry conditions, except some parts of these regions had normal conditions in Iran and Syria. The SERDI analysis revealed a strong correlation between (LST) and a moderate correlation with (VHI) across all study areas. However, the relationship between other indices, like (NDWI) and (NDVI), varied depending on the regions. To conclude, SERDI can be used globally for detecting drought based on soil moisture and evapotranspiration.
Hybrid Approach Using Physical Insights and Data Science for Stuck-Pipe Prediction
Authors: Kaneko Tatsuya , Inoue Tomoya , Nakagawa Yujin , Wada Ryota , Abe Shungo , Yasutake Gota , Fujita Kazuhiro
Published: November 2023

Early detection of stuck-pipe incidents is crucial because of the enormous costs of recovering from such incidents. Previous studies have leaned significantly toward a physics-based or data science approach. However, both approaches have challenges, such as the uncertainty of the physics-based model and the lack of data in the data science approach. In this study, we propose a hybrid approach using physical insights and data science and discuss the possibility of stuck-pipe prediction.

The proposed method comprises two steps. In the first step, a data-driven model with physical insights is trained using the historical data of the in-situ well to estimate some of the drilling variables. In the second step, the risk of stuck-pipe occurrence (hereafter referred to as sticking risk) is calculated based on the historical and current measured data and the estimation of the trained model. This approach is expected to overcome the limitations of the previous methods as it allows the construction of a detection model tuned to the in-situ well. In the case studies, models for estimating the topdrive torque and standpipe pressure were constructed. The performance of the models is discussed using actual drilling data from drilling fields, including 21 stuck-pipe incidents during drilling operations.

The proposed method was first examined using short-term output. The output confirmed that the sticking risk increased shortly (up to 20 hours) before the stuck-pipe incident occurred in 15 cases. This increase in sticking risk was consistent with physical considerations. Subsequently, this study examined the long-term output over several months; this was rarely done in previous studies. Even within this long-term output, some cases had good performance with only a few false alarms, while others had problems with many false alarms. For cases of low performance, several model improvements, such as adding mud information or making the learning and threshold-setting methods more robust to outliers, were found to have the potential to improve performance.

The novelty of our research lies in creating a broad framework for the stuck-pipe prediction by using both physical insights and data science methods. The proposed hybrid approach demonstrated the potential to reduce false alarms and improve interpretability compared with previous methods. The framework is highly extensible, and further performance improvements can be expected in the future.
A System to Detect Oilwell Anomalies Using Deep Learning and Decision Diagram Dual Approach
Authors: Aranha P. E. , Lopes L. G. O. , Paranhos Sobrinho E. S. , Oliveira I. M. N. , de Araújo J. P. N. , Santos B. B. , Lima Junior E. T. , da Silva T. B. , Vieira T. M. A. , Lira W. W. M. , Policarpo N. A. , Sampaio M. A.
Published: November 2023

Detecting unexpected events is a field of interest in oil and gas companies to improve operational safety and reduce costs associated with nonproductive time (NPT) and failure repair. This work presents a system for real-time monitoring of unwanted events using the production sensor data from oil wells. It uses a combination of long short-term memory (LSTM) autoencoder and a rule-based analytic approach to perform the detection of anomalies from sensor data. Initial studies are conducted to determine the behavior and correlations of pressure and temperature values for the most common combinations of well valve states. The proposed methodology uses pressure and temperature sensor data, from which a decision diagram (DD) classifies the well status, and this response is applied to the training of neural networks devoted to anomaly detection. Data sets related to several operations in wells located at different oil fields are used to train and validate the dual approach presented. The combination of the two techniques enables the deep neural network to evolve constantly through the normal data collected by the analytical method. The developed system exhibits high accuracy, with true positive detection rates exceeding 90% in the early stages of anomalies identified in both simulated and actual well production scenarios. It was implemented in more than 20 floating production, storage, and offloading (FPSO) vessels, monitoring more than 250 production/injection subsea wells, and can be applied both in real-time operation and in testing scenarios.
Identification of Potential Therapeutic Target SPP1 and Related RNA Regulatory Pathway in Keloid Based on Bioinformatics Analysis
Authors: Xie Ruxin , Yun Jiao , Li Chenyu , Zhang Shiwei , Zhong Ai , Wu Junliang , Cen Ying , Chen Junjie
Published: November 2023

Objective
To explore the complex mechanisms of keloid, new approaches have been developed by different strategies. However, conventional treatment did not significantly reduce the recurrence rate. This study aimed to identify new biomarkers and mechanisms for keloid progression through bioinformatics analyses.
Methods
In our study, microarray datasets for keloid were downloaded from the GEO database. Differentially expressed genes (DEGs) were identified by R software. Multiple bioinformatics tools were used to identify hub genes, and reverse predict upstream miRNAs and lncRNA molecules of target hub genes. Finally, the total RNA-sequencing technique and miRNA microarray were combined to validate the identified genes.
Results
Thirty-one DEGs were screened out and the upregulated hub gene SPP1 was finally identified, which was consistent with our RNA-sequencing analysis results and validation dataset. In addition, a ceRNA network of mRNA (SPP1)-miRNA (miR-181a-5p)-lncRNA (NEAT1, MALAT1, LINC00667, NORAD, XIST and MIR4458HG) was identified by the bioinformatics databases. The results of our miRNA microarray showed that miR-181a-5p was upregulated in keloid, also we found that the lncRNA NEAT1 could affect keloid progression by retrieving the relevant literature.
Conclusions
We speculate that SPP1 is a potential candidate biomarker and therapeutic target for patients with keloid, and NEAT1/miR-181a-5p/SPP1 might be the RNA regulatory pathway that regulates keloid formation.
Conditioning of agro-industrial residues for producing enzymes, additives and chemical precursors
Authors: Rivero Mayola García , Venegas Isabel de la Luz Membrillo , Trujillo María Aurora Martínez
Published: November 2023

Purpose Show how the most common conditioning treatments of lignocellulosic agricultural residues determine the performance of specific biological processes and after a review propose a final use for the resulting residues.
Methods Conditioning treatments such as drying and size reduction for prickly pear peels, or soaking and ultrasound for pineapple peels were applied before using these materials in a solid state-culture or an enzymatic saccharification, respectively. A detailed analysis about the fate of those solids obtained after solidstate culture on prickly pear peels or saccharification of pineapple peels was done to propose the integral use of these materials in the bioprocess performance.
Results In a solid-state culture using 1.84 mm particles of sun-dried prickly pear peels, Aspergillus niger produced eight-fold more xylanases and twice more laccases than those obtained on 1.09 mm wave-dried particles. Conversely, the highest enzymatic saccharification yields of pineapple peels were obtained with unconditioned peels, which means an advantage for the economy and operation of the process. The resulting residual composites can have several fates. Conclusion Agricultural residues are a potential material for obtaining biotechnological products, and some of the conditioning treatments are not necessary to use them in a bioprocess. These residues can have an integral use along the bioprocess development.
A Voyage from Imitation to Real – Knowledge-Enabled Generationof Semantically Annotated Datasets and Deep Learning Techniquesfor Robot Vision Impacts
Authors: Alam Mansoor , Parasad Mukesh , Mustapha Jawahir Che , Su'ud Mazliham Mohd , Sultana Saima
Published: November 2023

Computer vision technologies have fascinated substantial concern to visionary mission duringrecent years. At the edge of industry 4.0, Artificial intelligence comprehend Robotics andcomputer vision. Which briskly results as novel innovations, thematic invention and esteemedresearch at numerous fields of technology. To enclose the most recent research of Robot vision,the current study is designed. The coverage arena of this study is span over, but not limitedto Robot vision Datasets, Deep learning tools and techniques and labeling toolkits for visiondatasets. The features targeted through these data-driven approaches are highly robust than theirmanually engineered counterparts. The research study covers the most recent, state of the art andin-fashion researches debuted to Robot vision.
Unleashing the Power of Indirect Attacks against Trust Prediction via Preferential Path
Authors: Bu Yu , Zhu Yulin , Geng Longling , Zhou Kai
Published: November 2023

In the realm of network security, adversarial attacks pose a significant threat, prompting research into innovative strategies for enhancing both attack and defense mechanisms. This paper presents a novel exploration into the enhancement of adversarial attacks on Fairness and Goodness Algorithm (FGA) and Review to Reviewer (REV2), focusing on trust prediction within signed graphs. In contrast to traditional time-based dynamics, the trust propagation in FGA and REV2 is grounded on iterative processes. Through meticulous analysis of network structures, this research uncovers the strong ties and weak ties within FGA. Additionally , it reveals the existence of preferential paths in REV2, which significantly influence the spread of information during algorithm iterations. Leveraging these revelations, we introduce a novel approach known as vicinage-attack designed to bolster adversarial attacks by strategically targeting edges along these influential pathways. The significance of this work lies in identifying adversarial perturbation patterns that impact trust prediction on signed graphs, shedding light on their pervasive influence. Our findings not only contribute to the advancement of adver-sarial attack techniques but also lay the foundation for a deeper understanding of trust propagation patterns. By elucidating the propagation bias within FGA and REV2, this research offers new insights for both network security strategies and adversarial mitigation techniques in trust prediction.
Clinical and neuropsychological variables associated with subjective cognitive decline and its progression
Authors: Villino-Rodríguez Rafael , Ríos-Rivera Mirla M. , Imaz-Aguayo Laura , Espinoza-Vinces Christian , Pérez-Prol Cristina , Montoya-Murillo Genoveva , Arrondo Carlota , Riverol Mario
Published: November 2023

Background and Objectives:
This study aimed to compare clinical and neuropsychological variables between patients with subjective cognitive decline (SCD) and healthy controls in a memory clinic, while identifying variables associated with progression to mild cognitive impairment (MCI) or dementia.
Methods:
We retrospectively analysed data from 945 patients with SCD and 68 healthy controls (HCs) who visited the Clínica Universidad de Navarra memory clinic between 2001 and 2017. Among them, 450 participants were followed up longitudinally in at least one visit until January 2020. All patients underwent medical interviews, laboratory tests, neuropsychological assessments (during the first interview and follow-ups) and brain magnetic resonance imaging. Of the 945 participants, 131 progressed to MCI or dementia due to Alzheimer’s disease. The neuropsychological assessment encompassed the following domains: cognitive functions (i.e. global cognition, episodic visual and verbal memory, executive functions, phonetic fluency, cognitive flexibility, interference and language), neuropsychiatric symptoms and functional status. All variables were adjusted for age, sex and education.
Results:
Participants with subjective cognitive decline were younger and had higher education than HCs. Additionally, they presented more vascular risk factors. Age at diagnosis, years of education and the presence of hypercholesterolemia were among the demographic variables that were positively associated with the development of MCI or dementia. In the neuropsychological assessment, individuals with SCD showed worse results in global cognition, verbal memory and semantic and phonetic fluency and exhibited more depressive symptoms. Moreover, exhibiting worse performance on tests evaluating episodic verbal memory was found to be correlated with an elevated likelihood of transitioning to MCI and dementia.
Discussion:
The development of SCD and its progression to MCI or dementia is a multifaceted process involving clinical and neuropsychological factors. Younger age and increased vascular risk factors are characteristics of individuals with SCD. Neuropsychologically, they tend to display weaker performance in global cognition, fluency tasks, verbal memory and executive functions. Several variables were identified as potential indicators of disease progression. These include age at diagnosis, hypercholesterolemia and poorer results in tests measuring semantic fluency, verbal and visual memory and executive functions.
Risk factors for and developmental relation of delayed oral nutrition in infants with congenital diaphragmatic hernia
Authors: Yamamichi Taku , Imanishi Yousuke , Sakai Takaaki , Yoshida Mina , Takayama Keita , Uga Naoko , Umeda Satoshi , Usui Noriaki
Published: November 2023

Purpose: To identify risk factors for delayed oral nutrition in infants with a congenital diaphragmatic hernia (CDH) and its impact on developmental delay at 18 months of age.
Methods: This retrospective single-center cohort study compared the clinical parameters in patients with isolated CDH born and treated at our hospital between 2006 and 2020. We evaluated clinical features significantly related to delayed oral nutrition (defined as taking ≥30 days from weaning from mechanical ventilation to weaning from tube feeding)
Results: Twenty-six of the 80 cases had delayed oral nutrition. Univariate analyses showed significant differences. Multivariate analyses were performed on the three items of preterm delivery, defect size (over 50% to nearly entire defect), and ventilation for ≥9 days. We identified the latter two items as independent risk factors. The adjusted odds ratios were 4.65 (95% confidence interval, 1.27–7.03) and 6.02 (1.65–21.90), respectively. Delayed oral nutrition was related to a significantly higher probability of developmental delay at 18 months (crude odds ratio 4.16, 1.19–14.5).
Conclusion: In patients with CDH, a large defect and ventilatory management over 9 days are independent risk factors for delayed oral nutrition, which is a potent predictor of developmental delay that requires active developmental care.