bluuebunny/crossref_metadata_2025 huggingface dataset:
Removal of Pb(II), Zn(II) and Cd(II) ions by insolubilized humic acid
Authors: Khalili F. I. , Alnasra O. A. , Alhnafat F.
Published: December 2023

Humic acid from Tafila soil in Jordan has been extracted and insolubilized. Fourier transform infrared spectroscopy, thermal gravimetric analysis, elemental analysis, X-ray diffraction, scanning electron microscopy, and differential scanning calorimetry were used to characterize the sodium form of Insolubilized Tafila Humic Acid (INaTAHA). Using the batch technique, the adsorption of Pb(II), Cd(II), and Zn(II) by INaTAHA was investigated at various pH values (4.00, 5.00, and 6.00) and temperatures (25.0, 35.0, and 45.0oC). It was observed that INaTAHA has a maximum uptake as follows: Pb(II) > Zn(II) > Cd(II) and the metal ion uptake increased with pH reaching a peak at pH = 6. Kinetic studies results demonstrated that the maximum uptake level requires an equilibrium time of 24 hours for each metal ion fitting the pseudo-second-order model. Langmuir, Freundlich, and Dubinin-Radushkevich adsorption isotherms fitted the metal ion uptake characteristics of INaTAHA. The activation parameters Ea, ΔG‡, ΔH‡, and ΔS‡ were also calculated. The findings show that physisorption is the mode of adsorption. Using the column technique, the uptake percent with the metal ions is as follows: Pb(II) > Zn(II) > Cd(II). Using 1.0 M HNO3 produced the best percent recovery for the metal ions according to desorption studies.
The complex lived experience of schizophrenia diagnosis: A thematic analysis of online forum posts
Authors: Lyons Minna , Gupta Veenu , Blaney Peter Sunny , Ogenyi Appey , Webster Elliott , Brewer Gayle
Published: December 2023

Receiving a diagnosis of schizophrenia can be a life-changing experience with both negative and positive consequences. Previous research has identified important aspects of diagnosis, such as disagreement with the label, diagnostic shifts, stigma, and communication of the diagnosis. There is, however, relatively little research from the lived experience perspective. In this study, we investigated the lived experiences of receiving a schizophrenia diagnosis utilising a popular Reddit discussion forum. We used inductive thematic analysis to consider posts from 105 unique usernames and identified five themes. These were (i) Denial and acceptance; (ii) Stigma of diagnosis; (iii) The process of diagnosis; (iv) Identity and sense of the self; and (v) Receiving, finding, and providing support. Diagnosis is a complex personal experience where the same person can simultaneously accept and reject the diagnostic label. Greater attention is required to the lived experience of this diagnostic journey.
Dexterous learning of the robot hand using machine learning algorithms for object grasping
Authors: Heidari Hamidreza , Saremi Tahereh Ghahri , Saremi Tayebeh Ghahri
Published: December 2023

Grasping is an essential skill that humans possess and replicating or imitating its functionality has been a significant focus in robotics research. Robotic hands by imitating human grasping behavior, can perform versatile grasping tasks and enhance human-robot interactions. Replication of such ability in robots is a challenging problem. To tackle this challenge, deep learning, and computer vision methods are proposed. Through object recognition and transfer learning, these techniques have made robotic grasping more accurate and robot hands can become more autonomous. The main objective of this paper is to implement and compare deep learning and reinforcement learning (RL) methods for achieving a semi-automatic grasp of different objects. This paper proposes a humanoid 5-DoF robot hand designed specifically for grasping tasks. The robotic hand is fabricated using a 3D printer and its fingers are driven by 5 servo motors. In this direction, a pre-trained Convolutional Neural Network (CNN) structure was used to train the robot hand. Additionally, a 5-finger robot hand is simulated in the MuJoCo environment. The RL agent plans and executes appropriate actions in the simulated hand robot and provides positive or negative rewards based on the Q-learning algorithm. Finally, the performance of methods is evaluated on objects. The results demonstrate the RL method achieved a higher grasp accuracy of 95% compared to the CNN method, which achieved a grasp accuracy of 85%. This indicates that the RL method outperformed the CNN method in terms of grasp accuracy for the robot hand and improved results.
Compatibilizing of cotton fabric with hydrophobic drug cover layer for anti-inflammatory performance with the implementation of ibuprofen.
Authors: Kopańska Aneta , Brzeziński Marek , Gonciarz Weronika , Kost Bartłomiej , Draczyński Zbigniew
Published: December 2023

This paper presents active analgesic and anti-inflammatory dressings based on cotton woven material with surface functionalization enabling drug implementation. For this purpose, lactide was polymerized on the surface of cotton textiles to achieve better compatibility with drug-loaded polylactide. Then ibuprofen loaded PLA and PLA-PEG were implemented through the exhausting method. Such material was tested for cytotoxicity (toward L929 mouse fibroblasts) and anti-inflammatory activity (towards human Hs68 fibroblasts) based on the secretion of pro-inflammatory cytokines IL-1β and TNF-α. The results showed that the drug attachment and its performance are influenced by a combination of mercerization, bleaching and polylactide grafting, and the release of ibuprofen depends on drug-loaded layer structure. Moreover, we show that cotton woven fabric with ibuprofen-loaded PLA and PLA-PEG cover layer had anti-inflammatory properties. These new dressings may open possibilities for developing prolonged analgesic and anti-inflammatory materials for wound healing or transdermal drug delivery.
Large-scale mission scheduling for multiple heterogeneous agile earth observation satellites using modified chameleon swarm algorithm
Authors: Zhang Chao , Dong Yunfeng
Published: December 2023

The large-scale mission scheduling problem for multiple heterogeneous agile earth observation satellites is generally considered an extremely complex NP problem, which usually requires a large amount of computing resources to obtain the optimal solution or near-optimal solution. In order to solve the problem, the original chameleon swarm algorithm (CSA) is chosen to be modified from four aspects to improve its computational efficiency and global search ability. Specifically, the multi-population mechanism is introduced into the hunting prey of the modified chameleon swarm algorithm (MCSA), where the search strategies of three sub-populations and two different emergency response strategies are designed. The conflict elimination strategy based on heuristic rules is designed for the invalid solutions generated during the iteration process. Besides, the screening mechanism and the improved coding method are introduced into the MCSA based on the existing references. The results show that compared with the original CSA and two other existing referenced modified algorithms, the MCSA has significant advantages in both the computational efficiency and the global search ability, which verified the effectiveness of MCSA.
Mendelian Randomization Study: Genetic Prediction of Blood Metabolites and the Risk of Endometrial Cancer
Authors: Ting Qiu , She Haoqing , zhenbo ouyang
Published: December 2023

Background: Metabolic dysregulation is a hallmark of cancer. However, evidence of a causal relationship between circulating metabolites and the promotion or prevention of colorectal cancer (CRC) is still lacking. We conducted a two-sample Mendelian Randomization (MR) analysis to assess the causal relationship between 1,400 genetically proxied blood metabolites and endometrial cancer.
Methods: We extracted metabolite level data from 8,299 participants in the Canadian Longitudinal Study on Aging (CLSA) and conducted a genome-wide association study (GWAS). This study involved 1,091 metabolites and 309 metabolite ratios. We utilized the ebi-a-GCST006464 dataset from the GWAS Catalog database for endometrial cancer. This dataset covered the European population, with 12,906 cases of endometrial cancer and 108,979 controls for preliminary analysis. The primary method for causal analysis was the Inverse Variance Weighted (IVW) method, supplemented by M-R-Egger and weighted median analysis. To validate the robustness, heterogeneity, and pleiotropy of the results, we conducted comprehensive sensitivity analyses, including the Cochran Q test, MR-Egger intercept test, radial MR, and leave-one-out analysis. For the final identification of metabolites, we also performed linkage disequilibrium score regression and colocalization analysis.
Results: The results of this study indicated significant associations between nine metabolites and endometrial cancer. These include: 5alpha-androstan-3alpha,17beta-diol monosulfate (1) levels (Odds Ratio [OR] 1.15, 95% Confidence Interval [CI]: 1.09-1.20, p=1.34×10−8), 5alpha-androstan-3beta,17beta-diol monosulfate (2) levels (OR 1.18, 95% CI: 1.08-1.29, p=6.46×10−7), Androstenediol (3beta,17beta) disulfate (1) levels (OR 1.23, 95% CI: 1.12-1.36, p=3.01×10−5), Hexadecanedioate (C16-DC) levels (OR 1.12, 95% CI: 1.06-1.19, p=8.43×10−5), 1-linoleoyl-GPG (18:2) levels (OR 1.13, 95% CI: 1.06-1.21, p=0.0001), Adenosine 5'-diphosphate (ADP) to pantothenate ratio (OR 1.18, 95% CI: 1.08-1.29, p=0.0001), Octadecenedioylcarnitine (C18:1-DC) levels (OR 1.11, 95% CI: 1.05-1.17, p=0.0001), Glutarate (C5-DC) levels (OR 1.18, 95% CI: 1.08-1.28, p=0.0003), X-22509 levels (OR 1.15, 95% CI: 1.06-1.24, p=0.0003).
Conclusion: The results of this study reveal potential causal relationships between nine circulating metabolites and endometrial cancer, offering new insights into the biological mechanisms of endometrial cancer. These findings, derived from integrating genomics and metabolomics approaches, not only enhance our understanding of the pathogenesis of endometrial cancer but also have significant implications for the screening, prevention, and treatment strategies of endometrial cancer.
Cyclic Redundancy Check Assisted Successive Cancellation List Polar Code for MIMO-PLC Systems
Authors: Mengistu Fikreselam Gared , Alem Tigabu
Published: December 2023

Due to the use of the current power line network, Power Line Communication (PLC) technology has recently received a lot of attention. Because power lines are designed to transfer electric power at low frequencies, they are not appropriate for high-speed data transmission. The main problem with PLC is Impulsive Noise (IN). In PLC, the Multiple Input Multiple Output (MIMO) approach is used to reduce the impact of IN. To prevent the occurrence of a higher level of channel impulsiveness, MIMO’s success in reducing IN is insufficient. It’s necessary to use further IN reduction techniques. In this study, cyclic redundancy check assisted successive cancellation list (CRCSCL) polar coding and the minimum mean square error (MMSE) detector techniques are combined to reduce the IN effect in MIMO-PLC systems with various antenna configurations. By comparing various degrees of channel impulsiveness, the Bit Error Rate (BER) performance under the Middleton Class A (MCA) and Bernoulli Gaussian (BG) IN models is examined. The obtained findings show that, in comparison to the BG model, the suggested IN mitigation under the MCA noise model requires a low Signal to Noise Power Ratio (SNR) value. Similar to this, the results show that more MIMO-PLC configurations, a higher level of channel impulsiveness in the MCA of the impulsive index (A), a higher Gaussian to IN average power ratio (Γ), and a lower occurrence of IN probability (P) over the BG would all enhance MIMO-PLC system performance.
Exploring Indicators of Natural Recovery from Alcohol and Drug Use Problems: Findings from the Life in Recovery Survey in Flanders
Authors: De Meyer Florian , Zerrouk El-Amine , Ruysscher Clara , Vanderplasschen Wouter
Published: December 2023

Introduction. Research has established natural recovery (NR) as an important pathway to substance use recovery. Studies investigating correlates of NR have focused mainly on demographic and substance use variables rather than life circumstances. This study seeks to better understand the phenomenon of natural recovery by (i) validating the international scientific literature concerning demographic and substance use indicators of NR in Flanders and (ii) assessing the additional explanatory power of recovery strengths and barriers during active addiction, controlling for demographic and substance use covariates.
Methods. A total of 343 participants in recovery from alcohol or drug use problems (≥ 3 months) completed an online cross-sectional survey in Flanders.
Results. A higher education level, lower severity of dependence, and cannabis use as the main problem substance (vs. alcohol) were statistically significant (p < 0.05) indicators of NR. A second logistic regression model was used to add scores for the number of barriers and strengths associated with active addiction, and the results showed that barriers, but not strengths, were significantly different. When barrier items were individually tested, having untreated emotional or mental health problems, having a driver’s license revoked and damaging property were statistically significant. The most commonly reported reason for not entering treatment was not experiencing the need to do so.
Conclusion. The results highlight the importance of a holistic approach to recovery support across multiple life domains, within and beyond the scope of treatment. Limitations and research opportunities are discussed.
Ambivalent and heavy burdened wanderers on a road less travelled: A meta- ethnography on end-of-life care experiences in rural areas
Authors: Breivik Elisabet , Ervik Bente , Kitzmüller Gabriele
Published: December 2023

Background: As the population ages, more people will be diagnosed with cancer, and they will live longer due to receiving better treatment and optimized palliative care. Family members will be expected to take on more responsibilities related to providing palliative care at home. Several countries have expressed their vision of making home death an option, but such a vision can be more challenging in rural areas. There is a lack of synthesized research providing an in-depth understanding of rural family caregiving for people with cancer at the end of life. Thus, the purpose of this study was to synthesize and reinterpret the findings from qualitative research on rural family caregivers of adult cancer patients in the final stages of life.
Methods: We conducted a meta-ethnography following Noblit and Hare’s approach. A systematic literature search of four databases and extensive manual searches were completed in April 2022. The final sample included twelve studies from six different countries published in 2011-2022.
Results: Based on the translation and synthesis of the included studies, four themes were developed (1) providing family care at the end of life in rural areas - a challenging endeavour; (2) the heavy responsibility of rural caregiving - a lonesome experience; (3) working on and behind the scenes; and (4) the strong and weak spots of community connectedness in rural areas. An overarching metaphor, namely, “ambivalent and heavy burdened wanderers on a road less travelled”, provides a deeper understanding of the meaning of rural family caregiving at the end of life.
Conclusions: This study provides valuable insights into end-of-life cancer care for rural families. It is crucial to prepare family carers for the demanding role of palliative caregiving in rural areas. To address the long distances and poor access related to specialized health care services, outpatient palliative teams tailored to the families’ individual needs should be provided. In addition, more telehealth services, palliative units, or beds in local nursing facilities may reduce the number of exhausting trips that need to be made by caregivers and patients. The further education of health care workers providing palliative care in rural areas is needed.
Trial registration: The study was registered in PROSPERO
Ensemble convolutional neural network modeling based on a cost-sensitive approach
Authors: Wang Bo , Wang Nan
Published: December 2023

Addressing imbalanced data is one of the most significant challenges in machine learning. This research introduces the Cost-sensitive AdaBoost-CNN, a novel machine-learning approach that combines the strengths of cost-sensitive techniques, adaptive boosting, and convolutional neural networks. This method mitigates the misclassification of underrepresented categories in imbalanced data classification. Building on traditional AdaBoost, our approach integrates the principles of cost-sensitive normalization into the AdaBoost algorithm. This study further validated the approach using Fashion-Mnist and CIFAR-10 datasets. The proposed method consistently outperformed the standard AdaBoost-CNN, Integration Tree, AdaBoost-SVM, and other methods, especially for underrepresented class samples. A comparative experiment involving AdaBoost-CNN and classical neural networks, such as Lenet-5 and Alexnet, was also conducted on the PneumoniaMnist medical image dataset. The proposed method exhibited superior accuracy in classifying minority sample data such as specific patient categories. Additionally, on the multi-category retinal disease OCTMnist dataset, the approach demonstrated significant improvements in Recall, F1-Score, G-mean, and P-mean metrics, especially for the 'drusen' sample data when compared to AdaBoost-CNN.
Weed pressure management through tillage and weed control approaches in rice under resource conserving agriculture
Authors: Meher Sunita , Tiwari Nitish , Chitale Shrikant , Saha Sanjoy , Mahapatra Ashirbachan
Published: December 2023

The present investigation was conducted during three seasons i.e. Kharif seasons in 2019 and 2020 at research cum instruction farm, at Indira Gandhi Krishi Vishwavidyalaya, Raipur (C.G.), where adequate facilities for irrigation and drainage exist. The soil of the experimental field was silty clay in texture. The soil was neutral in reaction (6.86) with normal electrical conductivity (0.349). It had low nitrogen, medium phosphorus and high potassium contents.The experiment was laid out in split plot design with five tillage practices (main plot) i.e. two conventional transplanted rice CT (TPR), one conventional direct-seeded rice CT (DSR), one zero tillage (ZT) and one zero tillage with residues (ZT + R), and three weed management practices (sub-plot) treatments replicated thrice. The test varieties taken was “IGKV R1” sown as per the treatments with recommended dose of fertilizers. The outcomes explicated that among tillage practices, transplanted system of establishment i.e. CT (TPR)-CT-CT proved to be most beneficial in terms of significant economic produce, lowest weed pressure but ZT + R-ZT + R-ZT + R proved with about comparable yield i.e. only 8.39% lesser yield and about 19% lesser weed control efficiency (WCE) than transplanted system i.e. CT (TPR)-CT-CT. Moreover, the yield in zero tillage system increased in second year of trial unlike in CT (TPR)-CT-CT. Hence, long term trial of ZT + R-ZT + R-ZT + R is more eco-friendly and sustainable. Among weed management practices, IWM i.e. oxadiargyl 80 g ha− 1 PE fb hand weeding at 25 DAS/T proved to be registered highest value of all the parameters taken for study. Moreover, it registered 47% higher grain yield than weedy check and 12% higher weed control efficiency (WCE) than recommended herbicides treatment i.e. pyrazosulfuron 20 g ha− 1 fb penoxsulam 22.5 g ha− 1 PoE.
Real world experience of Brolucizumab in recurrent macular oedema in Retinal Vein Occlusions : 12 months follow up
Authors: Narnaware Shilpi H. , Bawankule Prashant , Raje Dhananjay , Jagdhane Prerna , Nagdeve Rakesh
Published: December 2023

Purpose : To evaluate real world outcome in recurrent macular oedema secondary to retinal vein occlusion in relation to anatomical success , visual outcomes and safety of intravitreal brolucizumab injection at 1 year.
Methods : Prospective, randomized study between July 2022 to June 2023 on 17 eyes of 32 patients. Patients were divided into Group 1 : BRVO with ME , Group 2 : CRVO with ME. BCVA, CMT, and number of injections at 1 year were evaluated. From beginning patients were treated on PRN basis.
Results: Study included 17 eyes with a mean age of 63.65 (SD: 10.68) years, and among these, 7 (41.2% ) were diagnosed with BRVO and 10 (58.8%) with CRVO. There was statistically significant improvement BCVA at 12 months in both the categories (P < 0.0001). Mean CMT also reduced significantly in both categories at 12 months (P < 0.0001). Median number of injections required was 2.0, while mean interval between two injections was 4.06 (SD: 1.91) months.
Conclusion: In real-world scenario, with 1 year follow up , brolucizumab is found to be efficacious and safe with less need injections and more interval free period in management of recurrent ME due to RVO’s
Box Behnken Desing for the Optimization of the Antimicrobial Substance Production by Lactic Acid Bacteria
Authors: Altuntas Evrim Gunes , Sevim Busra , Celik Asena Aslihan , Kaymaz Ozlem
Published: December 2023

In this research, we employed a 3-factor Box-Behnken experimental design (BBD), which falls within the category of response surface methods. The objective was to ascertain the optimal conditions for the production of antimicrobial substances by lactic acid bacteria (LAB). We utilized the MINITAB 19 trial version software package (MINITAB Statistical Software, State College, Pennsylvania, USA) for our data analysis. Throughout our analyses, a significance level of α=0.05 was maintained. The experimental parameters encompassed three variables: temperature, incubation time, and substrate concentration. Three levels of temperature were applied in the experiments: 30°C, 35°C, and 37°C. Incubation times were set at 24 hours, 48 hours, and 72 hours, while substrate (glucose) concentrations were established at 1%, 2%, and 3%. In addition to these variables, LAB isolates included in the trials were isolates coded as F2, 40, 50, O2 and Pediococcus pentosaceus ATCC 43201, which was the reference bacteria. Optimal conditions for bacteria coded as O2 and 40 could not be determined using the BBD method. We observed that the production of antimicrobial substances by F2 bacteria was influenced by the incubation period, with the most effective production occurring after an incubation period exceeding 70 hours. Similarly, P. pentosaceus ATCC 43201 exhibited optimal antimicrobial substance production after an incubation period exceeding 70 hours. Bacteria coded as 50 displayed varying antimicrobial activity in response to all three model parameters. The highest antimicrobial substance production was achieved at a temperature of 37°C, an incubation period of 72 hours, and a substrate concentration of 2% in the environment. These results from our trial suggest that the antimicrobial effectiveness of LAB generally increases beyond the logarithmic phase in the growth curve. This observation aligns with the notion that bacteria tend to exhibit a more competitive nature as environmental factors become more limiting, which is often associated with the production of secondary metabolites.
Artificial intelligence classifies and predicts the outcome of primary CNS and nodal large B-cell lymphomas
Authors: Alentorn Agusti , Barillot Noemie , Verdin Isaias Hernández , Rosa Lucas Rincón de la , Velasco Roser , Drieux Fanny , Veresezan Elena-Liana , Mathon Bertrand , Kirasic Eva , Vidal Noemí , González-Barca Eva , Esteller Fina Climent , López Patricia , Abada Yah-se , Heming Michael , zu Hörste Gerd Meyer , Grauer Olivier , Garff-Tavernier Magali Le , Davi Frédéric , Pons-Escoda Albert , Nichelli Lucia , Choquet Sylvain , Jardin Fabrice , Houillier Caroline , MOKHTARI Karima , Hoang-Xuan Khe
Published: December 2023

Primary Central Nervous System Lymphoma (PCNSL) is a particular extra-nodal subtype of large B-cell lymphoma (LBCL) with dismal prognosis. We propose a novel approach using digital pathology to classify PCNSL, assessing the presence of MYD88 L265P mutation and predicting the outcome of PCNSL and LBCL using hematoxylin-eosin (H&E) immunohistochemistry (IHC) samples. We have used different datasets with LBCL and PCNSL for training and validation of our findings with more than 400 patients. The classification with deep learning using H&E to categorize the four molecular clusters in PCNSL showed a median Area Under the Receiver Operating Characteristic Curve (AUROC) of 0.9 [interquartile range, IQR 0.85-0.93]. The spatial transcriptomics and single cell RNAseq analysis showed a high degree of intra-tumoral heterogeneity. In addition, all the partial least squares (PLS) Cox models with cell radiomics or combining cell radiomics with clinical features achieved a C-index higher than 0.9 in all datasets. We were able to correctly classify the four molecular groups obtained with multi-omics approaches only with deep learning applied to H&E samples. These results may facilitate the routine clinical use of this artificial intelligence approach to progressively ease the implementation of precision medicine in LBCL and PCNSL.
A Shoreline Extraction Method Based on Double-Loop Network Framework
Authors: Li Xuanpeng , Cao Hengshuo , Li Jinming , Li Guangyu , Zhao Lin
Published: December 2023

Satellite remote sensing-based shoreline extraction can provide great supports for scientific planning and utilization of coastal zones, marine ecological protection, and efficient shoreline management. In this paper, based on the designed double-loop network framework, we propose an adaptive image segmentation algorithm to achieve end-to-end shoreline extraction. Specifically, by considering triple constraints, a label reassignment module is firstly designed to enabling the extraction network with self-supervised learning ability for adaptive segmentation. Secondly, a data stream attention scheme is constructed to guide the network’s learning directionally, which could enhance the robustness and convergence speed of the double-loop network. Finally, a series of experiments are carried out to validate the effectiveness and feasibility of our proposed work.
L-proline.H2SO4 catalyzed synthesis of novel coumarin-based spiroindolino-3,4-dihydropyrimidin-2(1H)-ones: In-vitro cytotoxic assays and molecular docking study
Authors: Mezhubeinuo Mezhubeinuo , Mohanta Rahul , Bordoloi Hemanta , Verma Akalesh Kumar , Bez Ghanashyam
Published: December 2023

Development of environmentally benign catalyst system, especially those derived from readily available nature’s pool, in multicomponent synthesis consolidates multiple facets of green chemistry. Here, an L-proline derived green acid catalyst in the form of L-proline×H2SO4 was developed and employed for multicomponent synthesis of coumarin-based spiroindolino-3,4-dihydropyrimidin-2(1H)-ones from the reaction of 4-hydroxycoumarin, isatin and urea/thiourea. In this process, molecular building blocks having diverse biological activities such as antitumor, anti-inflammatory, and antitubercular activity were converged into a single molecular framework. Preliminary cytotoxicity studies showed that a couple of compounds (M5 and M6) have good cytotoxicity (40-50%) against in Dalton's Lymphoma (DL) cells, while demonstrating minimal cytotoxicity (10-12%) for normal non-cancerous cell line. Molecular docking simulations for the compounds M6 and M3, the compounds with heist and least cytotoxicity respectively, against Eg5 or Kinesin spindle protein (KSP) revealed the nature of interactions, estimated binding energy, and inhibition constants (Ki) of the compounds with KSP to corroborate with the experimental in-vitro cytotoxicity.
Screening of Ligninolytic Fungi and Optimization of Pretreatment Process for Bioethanol Production from Empty Palm Oil Bunches (OPEFB)
Authors: Firsty Ina Monica , Setyaningsih Ratna , Sugiwati Sri , Das Atanu Kumar , Maryana Roni
Published: December 2023

The high fuel demand causes depletion of non-renewable energy. Fuel substitution such as bioethanol need to be discuss as an alternative to gasoline. Second-generation bioethanol utilizes lignocellulosic biomass. Empty Palm Oil Bunches (OPEFB) is one of the abundant sources of lignocellulosic biomass in Indonesia, that can be potentially converted into bioethanol. This study was conducted to determine the most effective fungal pretreatment on lignin and cellulose content, and measuring enzyme activity. Optimization of temperature, pH, and substrate concentration were carried out using RSM. Trametes versicolor, Pycnoporus cinnabarinus (white-rot fungi), and Aspergillus niger, Aspergillus terreus, Trichoderma harzianum, Trichoderma viride (brown rot and soft rot fungi) were examined in this study. Fungal pretreatment was conduted by adding the fungal suspension to OPEFB, then incubated at 28°C for 14 days. This showed that A. niger had the highest ability to degrade lignin (7.58 ± 1,5%) and increase cellulose (33.56%). The highest laccase and MnP activities were produced by P. cinnabarinus (9,26 and 123.81 U/ml). The highest LiP activity was produced by A.niger (3276,8 U/ml). XRD analysis resulting in reducing CCI in pretreated sampel. Optimization of pretreatment using A.niger which produce highest lignin removal obtained at 30 oC, pH 5, and 7 grams OPEFB (14.21 ± 0.50%). At 25 oC, the highest cellulose content was obtained (53.08%). The pretreated sample using A. niger was hydrolyzed with enzymes, resulting in 1.09 g (36.30%) of reducing sugar at 48 hours at 50 oC, by DNS method. Saccharomyces cerevisiae were used for fermentation, resulting in ethanol of 0.56%.
Plant Disease Management: A Fine-Tuned Enhanced CNN Approach with Mobile App Integration for Early Detection and Classification
Authors: Iftikhar Mudassir , Kandhro Irfan Ali , Kausar Neha , Kehar Asadullah , Uddin Mueen , Dandoush Abdulhalim
Published: December 2023

Farmers face a daunting challenge in meeting the escalating demands of a rapidly growing population for agricultural products, while plant diseases continue to exact a devastating toll on food production. Despite investing billions of dollars in disease management, agriculturists often struggle to achieve effective disease control without the support of advanced technology. The article explores a deep learning-based approach for disease detection. Specifically, it employs a Convolutional Neural Network (CNN) architecture for the detection. For the automated detection of plant disease, using plant images. This paper presents a new model for the early detection of plant detection based on processing plant images. And compare the in-depth performance analysis of hyper parameters in the context of plant disease detection by focusing on three distinct crops: (Apple, Corn, and Potato). Moreover, the data augmentation impact is analyzed. To enhance accessibility for farmers, our model is seamlessly integrated with a mobile application. The experimental results show the efficiency of our fine-tuned enhanced CNN model (E-CNN) achieving 98.17% accuracy on fungal classes. This research endeavors to pave the way for more effective plant disease management and ultimately to improve agricultural productivity in the face of mounting global challenges.
Effective electrode preparation to prevent crevice in steel electrodes
Authors: Frontini María Alejandra , Vazquez Marcela , Valcarce María Beatriz
Published: December 2023

Crevice corrosion is hard to avoid when the corrosion resistance of steel electrodes needs to be evaluated, particularly when chloride ions are present in the electrolyte. This problem is recurrent when studying the performance of construction steel in concrete pore simulating solutions that aim to replicate a marine exposure. Other steel applications in aggressive environments face the same problem. This study describes a simple pre-treatment implemented on the steel bars before the electrodes were constructed, which successfully helps to minimize the risk of electrodes showing crevice after an electrochemical evaluation in the anodic potential range. The effectiveness of this acidic pre-treatment can be evaluated electrochemically in alkaline solutions. Polarization curves, electrochemical impedance spectroscopy and voltammograms on electrodes with and without the pre-treatment demonstrate the advantages of implementing the pre-treatment.
Exploring the mutualistic symbiotic mechanism of industrial transfer between China and the countries along the "Belt and Road"
Authors: hu haisheng
Published: December 2023

The construction of a "Community of Shared Future for Mankind" requires a concept of mutual benefit and coexistence. The implementation of the "Belt and Road" initiative cannot be separated from the strategy of industrial transfer. Whether the industrial transfer between China and the countries along the "Belt and Road" can achieve the mutual benefit and coexistence of bilateral industries is related to the quality and stability of the joint construction of the "Belt and Road". It can also provide empirical evidence to respond to some countries' doubts about the motives of the "Belt and Road" initiative. This article analyzes the mutual benefit and coexistence effects and their mechanisms of industrial transfer between China and countries along the "Belt and Road" from three dimensions of the mutual benefit and coexistence relationship: integration, interaction, and coordination. It uses the EORA world input-output data from 2003 to 2021 for empirical verification. The research results show that the overall level of industrial mutual benefit and coexistence between China and the countries along the "Belt and Road" continues to improve, but the differences between different industries and regions are significant; the industrial transfer between China and the countries along the "Belt and Road" can promote the mutual benefit and coexistence of bilateral industries. This promotion is mainly achieved by strengthening regional value chain cooperation and improving the level of industrial agglomeration. The mutual benefit and coexistence effects of industrial transfer between China and the countries along the "Belt and Road" vary in regions, industries, and time periods. The effects are more significant with the industrial transfer from developed countries along the route, the industrial transfer from medium and high-tech industries, and the industrial transfer after the initiative proposed. The research of this article provides important implications for deepening the industrial transfer between China and the countries along the "Belt and Road" and constructing a system of regional value chain cooperation with mutual benefit and coexistence.
In-silico Investigation by Molecular Docking, DFT and Pharmacokinetic Studies of Some Synthesized 1,8-Naphthyridine Derivatives as Prospective Anti-Breast Cancer Agents
Authors: Magit Nangnom Dachung , Umar Abdullahi Bello , Magit Nathaniel Dachung
Published: December 2023

Cancer, which has been identified as the second leading causes of health-related mortalities worldwide, is a disease in which some cells of the human body grow uncontrollably and spread to other parts of the body. The resistance of cancer (especially breast cancer) cells to known treatments as well as the adverse side effects associated with current anti-breast cancer drugs necessitates the discovery of novel and potent drug candidates. In this study, in-silico approaches such as DFT studies, Molecular Docking simulation and pharmacokinetic property predictions were used to examine the potency of seventeen (17) previously synthesized novel derivatives of 1,8-naphthyridine as potent anti-breast cancer agents using the Tamoxifen Standard drug (an FDA approved drug for the treatment of breast cancer) as reference. From the molecular docking studies, most of the compounds were found to have better binding energy to the human estrogen receptor (PDB ID: 1ERR) than the control drug (Tamoxifen, Mol. Dock score = −137.807, Re-rank score = −106.527 Kcalmol-1). Compounds C3 and C13 (with Mol. Dock scores -147.054 and -147.819 Kcalmol-1 respectively), which had superior docking scores than the standard drug, were found to be stable based of DFT studies. The predicted drug-likeness and pharmacokinetics properties of these two compounds were also found to be within the acceptable optimal requirements for drug development. Based on the results therefore, compounds C3 and C13 are proposed as potent anti-breast cancer drug candidates with better anti-breast Cancer capacity than the tamoxifen standard drug.
Cy-1, a major QTL for tomato leaf curl New Delhi virus resistance, harbors a gene encoding a DFDGD-Class RNA-dependent RNA polymerase in cucumber (Cucumis sativus)
Authors: Koeda Sota , Yamamoto Chihiro , Yamamoto Hiroto , Fujishiro Kohei , Mori Ryoma , Okamoto Momoka , Nagano Atsushi J. , Mashiko Takaaki
Published: December 2023

Background
Tomato leaf curl New Delhi virus (ToLCNDV) (family Geminiviridae, genus Begomovirus) is a significant threat to cucumber (Cucumis sativus) production in many regions. Previous studies have reported the genetic mapping of loci related to ToLCNDV resistance, but no resistance genes have been identified.
Results
We conducted map-based cloning of the ToLCNDV resistance gene in cucumber accession No.44. Agroinfiltration and graft-inoculation analyses confirmed the resistance of No.44 to ToLCNDV isolates from the Mediterranean and Asian countries. Initial mapping involving two rounds of phenotyping with two independent F2 populations generated by crossing the begomovirus-susceptible cultivar SHF and No.44 consistently detected major quantitative trait loci (QTLs) on chromosomes 1 and 2 that confer resistance to ToLCNDV. Fine-mapping of Cy-1, the dominant QTL on chromosome 1, using F3 populations narrowed the candidate region to a 209-kb genomic segment harboring 24 predicted genes. Among these genes, DFDGD-class RNA-dependent RNA polymerase (CsRDR3), an ortholog of Ty-1/Ty-3 of tomato and Pepy-2 of capsicum, was found to be a strong candidate conferring ToLCNDV resistance. The CsRDR3 sequence of No.44 contained multiple amino acid substitutions; the promoter region of CsRDR3 in No.44 had a large deletion; and the CsRDR3 transcript levels were greater in No.44 than in SHF. Virus-induced gene silencing (VIGS) of CsRDR3 using two chromosome segment substitution lines harboring chromosome 1 segments derived from No.44 compromised resistance to ToLCNDV.
Conclusions
Forward and reverse genetic approaches identified CsRDR3, which encodes a DFDGD-class RNA-dependent RNA polymerase, as the gene responsible for ToLCNDV resistance at the major QTL Cy-1 on chromosome 1 in cucumber. Marker-assisted breeding of ToLCNDV resistance in cucumber will be expedited by using No.44 and the DNA markers developed in this study.
Günter Eich, 1907–1972
Authors: Hoffmann Hans Peter
Published: December 2023

Günter Eich (1907–1972) zählt zu den bekanntesten und vor allem in den 50er und 60er Jahren nachhaltig rezipierten Dichtern, Hörspielautoren und Übersetzern der Nachkriegszeit. Der posthum 1976 erschienene gelbe Suhrkamp-Band mit dem Titel "Aus dem Chinesischen", in dem Eichs Anfang der 50er Jahre erschienene Übersetzungen versammelt sind, dürfte seine relativ weite Verbreitung und Bekanntheit dem Ruhm des Dichters verdanken.
Vacuum-field-induced state mixing
Authors: Fernández de la Pradilla Diego , Moreno Esteban , Feist Johannes
Published: December 2023

By engineering the electromagnetic vacuum field, the induced Casimir-Polder shift (also known as Lamb shift) and spontaneous emission rates of individual atomic levels can be controlled. When the strength of these effects becomes comparable to the energy difference between two previously uncoupled atomic states, an environment-induced interaction between these states appears after tracing over the environment. This interaction has been previously studied for degenerate levels and simple geometries involving infinite, perfectly conducting half-spaces or free space. Here, we generalize these studies by developing a convenient description that permits the analysis of these non-diagonal perturbations to the atomic Hamiltonian in terms of an accurate non-Hermitian Hamiltonian. Applying this theory to a hydrogen atom close to a dielectric nanoparticle, we show strong vacuum-field-induced state mixing that leads to drastic modifications in both the energies and decay rates compared to conventional diagonal perturbation theory. In particular, contrary to the expected Purcell enhancement, we find a surprising decrease of decay rates within a considerable range of atom-nanoparticle separations. Furthermore, we quantify the large degree of mixing of the unperturbed eigenstates due to the non-diagonal perturbation. Our work opens new quantum state manipulation possibilities in emitters with closely spaced energy levels.
Social norms moderating the attitude-intention relationship in adopting sustainable products
Authors: Anand Aastha , Sharma Meghna
Published: December 2023

Rapid economic growth, global consumption patterns, and prevailing human practices are primary contributors to environmental degradation. This study aims to understand the moderating role played by social norms in shaping consumer attitudes and their intention to buy sustainable personal care products. Psychosocial factors related to the environment, including environmental orientation, environmental knowledge, and perceived environmental responsibility, were taken as independent variables. The research population includes urban educated consumers in the region of Delhi, the capital of India. The survey instrument was shared among 390 participants via e-mail, Google Groups, and other social networking sites. The data from 238 respondents using the convenience sampling technique were collected, and AMOS structural equation modeling (Version 23.0) was used for analysis. The results validate the role of social norms as a moderator in the association between attitude (β = 0.186, p < 0.05) and intentions (β = 0.215 at p < 0.05) to acquire sustainable personal care products. The results also indicated a positive relationship between consumer attitude and purchase intention (β = 0.301, p < 0.01). The findings suggest a positive correlation between an individual’s environmental orientation, knowledge and responsibility, and inclination toward sustainable personal care products. The study shows a significant positive impact of environmental orientation on attitude toward sustainable personal care products (β = 0.332, p < 0.01). Also, a positive association between environmental knowledge and attitude (β = 0.291, p < 0.01) and perceived environmental responsibility (β = 0.227, p < 0.05) was observed.
Análisis de instrumentos de investigación para medir la competencia digital del alumnado de Educación Primaria
Authors: García Marchán Alba
Published: December 2023

Se presenta una investigación cuyo objetivo es analizar instrumentos que midan el nivel de competencia digital del alumnado de la etapa de Educación Primaria. Se ha seguido una metodología cualitativa y un método exploratorio y analítico. Tras una búsqueda de artículos en revistas científicas atendiendo a diversos criterios, se han seleccionado un total de 13 artículos, de los cuales serán analizados los instrumentos que utilizan para medir la competencia digital de los estudiantes. Los resultados obtenidos han permitido  analizar dichos instrumentos en función de su validez, el número de ítems que contienen, el estándar de competencia digital utilizado, la fecha de realización, la fiabilidad que presenta (medida a través de Alfa de Chronbach o el juicio de expertos) y si, en dicho artículo, se dispone del instrumento en su totalidad. Después de este análisis y de comparar los instrumentos entre sí, se concluye cual es el mejor atendiendo a los criterios establecidos. Conocer el nivel de competencia digital de los alumnos en la etapa de Educación Primaria es esencial para dar una mayor respuesta en el proceso de enseñanza-aprendizaje vinculado a las Nuevas Tecnologías.
Integración de las redes sociales a la formación de profesionales de la Ingeniería civil
Authors: Astudillo Torres Martha Patricia
Published: December 2023

El advenimiento de las redes sociales en el ámbito educativo ha sido objeto de estudio destacado debido a su inminente presencia en la vida de los estudiantes universitarios, quienes las utilizan en diversos aspectos. Por ello, esta investigación tiene por objetivo analizar la integración de las redes sociales TikTok e Instagram a las prácticas pedagógicas de asignaturas relacionadas con las Humanidades y la Epistemología de la Ciencia, en la carrera de Ingeniería Civil en una universidad pública mexicana. La metodología aplicada es la Investigación-Acción Participativa, a través de la observación participante, el grupo focal y el análisis de contenido, como técnicas de recolección de información. Los principales hallazgos y conclusiones indican que las redes sociales mencionadas brindaron un gran apoyo al desarrollo de conocimientos en los estudiantes, gracias a la interactividad que estas tecnologías ofrecen; sin embargo, se destaca que el elemento clave para lograr un proceso educativo exitoso radica en el establecimiento de un modelo didáctico que incluya directrices claras y específicas por parte de los educadores para el uso de estas redes sociales en la enseñanza y el aprendizaje; esto incluye la orientación y la supervisión activa que garantice un uso adecuado y responsable de estas plataformas.
Data ecosystems in education: opportunities and challenges
Authors: Castañeda Linda , Gourlay Lesley
Published: December 2023

The integration of ecosystems that promote the massive use of data and the large-scale processing of this data into educational processes represent an unprecedented social challenge. This change, which we could consider paradigmatic, has been promoted by various factors which mutually magnify each other's effects.

In recent years the massive collection and storage of data has intensified through ubiquitous technologies, which co-exist with human actors. In addition, we have witnessed an increase in the intentional processing power of this data at a speed unimaginable a few years ago (through the application of Artificial Intelligence, hereafter AI) . This has turned many aspects of our lives into data, from which value is extracted by third parties through processes of datafication. Concurrently, the public at large - including the educational sector - has been promised educational ‘personalisation’, a concept derived directly from other industrial production scenarios where AI is already in use, and every experience is datafied. In addition, a rapidly growing economic sector - the EdTech industry - has emerged with a capacity to monetise the educational sphere at a global level, extracting not only profits from its present and future actions with private or institutional clients, but also generating income based on capturing the motivation of their users and achieving significant levels of social and political influence. All of the above is magnified by the proliferation of the use of online platforms and tools in educational spaces (such as learning analytics and online exam proctoring), accelerated by the demand for online educaiton resulting from ‘lockdowns’ during the CoVid-19 pandemic.

This special issue aims to bring together articles that problematise the challenges and unintended effects that new mechanisms and dynamics fuelled by these data-driven technologies have introduced into education. This call aims to encourage researchers and practitioners to share studies, research, debates and academically well-founded reflections that propose critical visions. This aims to provide those who are interested in education (either as teachers, academic faculty, researchers or managers ) deeper analyses, to allow us to understand the current educational and technological landscape, and to foster a revaluation of relevant educational issues that should be part of our work in the coming years.