bluuebunny/crossref_metadata_2025 huggingface dataset:
EFFECTIVENESS OF DEEP LEARNING APPROACH FOR TEXT CLASSIFICATION IN ADAPTIVE LEARNING
Authors: Yuhana Umi Laili , Imamah Imamah , Fatichah Chastine , Santoso Bagus Jati
Published: December 2023

Klasifikasi text sangat bermanfaat dan dibutuhkan diberbagai bidang. Salah satu bidang yang membutuhkan klasifikasi text adalah E-learning yang bersifat adaptive atau disebut sebagai adaptive learning sistem. Adaptive learning sytem adalah sistem pembelajaran online yang dapat memberikan rekomendasi pembelajaran berdasarkan kebutuhan pengguna. Adaptive learning memiliki dua bagian, yaitu modul learning dan modul testing. Modul learning adalah bagian dari sistem yang bertugas untuk memberikan rekomendasi pembelajaran bagi pengguna, sedangkan modul testing bertugas untuk menguji dan memberikan penilaian terhadap hasil pembelajaran yang diperoleh dari modul learning. Materi pembelajaran pada modul learning memerlukan klasifikasi text berdasarkan tingkat kesulitannya untuk memastikan bahwa pengguna dengan level kemampuan rendah juga mendapatkan materi pembelajaran yang mudah, dan rekomendasi ini akan dinamis mengikuti perkembangan kemampuan pengguna. Pada penelitian ini, akan dibahas bagian kecil dari sistem pembelajaran adaptive pada modul learning yaitu tahap klasifikasi text. Dataset yang digunakan dalam penelitian ini adalah mata pelajaran IPA untuk tingkat SMP yang didapatkan dari Ruang Guru dan merupakan salah satu platform E-learning di Indonesia. Metode yang digunakan dalam penelitian ini adalah CNN, RNN dan HAN dengan menggunakan word embedding Word2Vec
E-LEARNING ADOPTION READINESS IN SECONDARY EDUCATION OF DEVELOPED AND DEVELOPING COUNTRIES: A SYSTEMATIC LITERATURE REVIEW
Authors: Nuzulismah Ratu Syafianisa , Santoso Harry Budi , Putra Panca O. Hadi
Published: December 2023

Situation in COVID-19 pandemic forced educational activity to shift from face-to-face to blended learning or to full online learning. This situation becomes a problem in different academic levels, especially secondary education as some teachers and students were not ready. This â€œE-Learning Adoption Readiness in Secondary Education: A Systematic Literature Reviewâ€ article summarized the influencing factors and issues of readiness in adopting e-Learning in high school, including the technologies and communication tools, as the foundation of analysis. The research objective is to identify and compare e-Learning adoption between developed and developing countries during pandemic. This article used Kitchenham and Charter method which extract data research published in databases such as Scopus and Science Direct. This research found distinct gaps between developed and developing countries in the context of e-learning readiness adoption and factors that influenced the said adoption. We conclude that there are still a numbers of basic internal and external factors that need to be considered in e-Learning adoption, especially in developing countries. The implication and recommendation for the adoption during pandemic is hoped to be insightful for future research in the same field, as there are significant differences in developing and developed countries, especially regarding IT literacy.
SEGMENTATION OF LUNG CANCER IMAGE BASED ON CYTOLOGIC EXAMINATION USING THRESHOLDING METHOD
Authors: Widodo Rulisiana , Badriyah Tessy , Syarif Iwan , Sandhika Willy
Published: December 2023

Lung cancer is the most dangerous cases which mostly attacks the man with the biggest causes of smoking. This cancer threatens the second largest death after heart attack, lung cancer cases increase significantly every year in various countries. Several methods have been established to detect lung cancer, including Computed Tomography of the thorax, sputum examination and cytology examination. The most decisive examination is through cytologic examination of the pleural fluid. However, the current state of biopsy performed by doctors does not always get a lot of specimens, making it difficult to determine the presence of cancer cells in the lungs. Cytological examination through the pleural fluid has difficulty in detecting cell images. The image of pleural fluid that has a high density between cells will produce an image with low detail, while an image with a low density will produce an image with high detail. Image segmentation is an important part in determining the cellular anatomy of pleural fluid to characterize images with cancer or normal categories. We propose the methodology of research by using group images to separate objects from other objects by highlighting important parts using image segmentation on pleural fluid of patients suspected of having lung cancer. Thresholding method used to see the comparison is Adaptive Thresholding, binary thresholding and Otsu Thresholding. The classification results of the three methods show a high accuracy of 99% on binary thresholding, then 97% accuracy on otsu thresholding and the lowest accuracy of 96% on adaptive thresholding, the three methods are considered to increase in proportion to the addition of the epoch parameter.
APPLICATION OF MULTISTAGE CLUSTERING FOR MAPPING ECONOMIC POTENTIAL IN EAST JAVA PROVINCE
Authors: Susetyoko Ronny , Satriyanto Edi , Fadliana Alfi , Syahfitra Muhammad
Published: December 2023

This study aims to map the economic potential in East Java Province based on GRDP according to business field category. Multistage clustering is a method developed for outlier data and datasets with large variance. Multistage clustering is a combination of Ordering Points to Identify the Clustering Structure (OPTICS) and K-Means. The first stage was grouped using OPTICS. The outlier data resulting from the clustering stage is used as a dataset in the second stage using K-Means. The performance of this method is compared with several other methods, namely: K-Means, DBSCAN â€“ K-Means, Agglomerative, Fuzzy C-Means (FCM), Possibilistic C-Means (PCM), and Fuzzy Possibilistic C-Means (FPCM) based on the characteristics of the Silhouette score and Davies-Bouldin score. Multistage clustering was chosen as the best method with a Silhouette score of 0.442 and Davies-Bouldin score of 0.388. With the Elbow method and the two metrics, the optimum number of clusters is 8 clusters. The results of this mapping method, the City of Surabaya forms a separate cluster which has the highest economic potential in 15 categories of business fields. Next Gresik, Pasuruan, Sidoarjo, and Probolinggo have the second highest economic potential with 10 categories of business fields ranking in the top 3.
The role of autonomy in defining the working model on perceived psychological safety
Authors: Guimarães Milena da Silva , Fialho Pedro , Moliner Carolina , Andrade Monique Delfim
Published: December 2023

According to Baert et al. (2020), the potential impacts of teleworking arrangements may include difficulty in career progression and decreased interactions with employers and colleagues. Atkinson (2022) discusses the risks and effects associated with remote work, emphasizing whether it is forced or adopted by choice. This way, it is important to ensure that teleworking is aligned with internal environments, such as well-being and psychological safety. Psychological safety is defined by Edmondson (1999) as “a shared belief held by members of a team that the team is safe for interpersonal risk-taking”. This study aimed to analyze how the interaction between teleworking arrangements and autonomy on perceived psychological safety can be a key element for organizations. The methodology consisted of quantitative data collected through a questionnaire answered by 506 workers. The variables considered in this study are the type of working model (in-person, remote, and hybrid), the level of individual autonomy in defining the working model, and psychological safety. Results showed that the higher the level of virtuality the higher the level of psychological safety. Moreover, in the case of remote and hybrid work, psychological safety was higher when the organizations decided to adopt these working models than when it was decided voluntarily by the employees. This research suggests that remote working models may have a positive influence on the perceived psychological safety of organizations, especially when organizations commit to the remote working model. We conclude by discussing the consequences of this study, including its limitations and possibilities for further research.
Pop the bubbles and let the current: Mechanochemistry of micron and nano-sized openings in dielectric layers
Authors: Birant Gizem , Rossi Christian , Czech Jan , Marchal Wouter , Brammertz Guy , Aernouts Tom , Colombara Diego , Wild Jessica , Vermang Bart
Published: December 2023

Thin or ultra-thin dielectric layers have been widely used in various applications such as capacitors, piezo-electrics, and solar cells. This study explains the mechanism and chemistry of creating nano- and micron-sized openings in atomic-layer-deposited aluminum oxide-based dielectric layers using the alkali metal salt selenization technique. The necessary components for this mechanism are excess methyl groups present in the dielectric layer, supply of selenium and alkali metals, and a minimum annealing temperature. It is shown and explained that to create openings in the dielectric layer, heavier alkali halide metal salts require less energy, or - in other words - a lower annealing temperature. The overall hypothesis is explained via a thermodynamic approach with supportive thermochemical reactions. Thus, an easy way to engineer the dielectric layer to form openings at low temperatures is presented, beneficial for various applications like photovoltaics, optoelectronics, or micro-electro-mechanical systems (MEMS).
The effect of seed moisture content of hybrid maize at harvest time on seed germination traits and antioxidant enzymes activity under simulated conditions of some environmental stresses
Authors: Rahbari Kourosh , Madandoust Mehdi
Published: December 2023

Seed quality of hybrid maize is affected by many factors, including maturity time and environmental conditions. In this study, the effect of four maturity times of hybridized maize from male and female plants was investigated in terms of grain moisture content (30, 35, 40 and 45%) in 2021 & 2022 in Kermanshah, Iran. The experiments were on maize seed vigor using the standard germination and simulated tests of cold, Hiltner brick gravel and germination test under drought stress conditions. The results showed that highest percentage and rate of germination were obtained from the treatment with 30% moisture content at maturity (99% and 0.037 germination per hour). Brick gravel and drought stress tests reduced germination percentage compared to the standard test. Based on Guasnr model, the nonlinear model of germination response curve was fitting to the percentage of moisture contents at maturity time for various tests. In general, due to the reduction in the slope of germination response curve at high moisture content at maturity time for different tests, 30 and 35% moisture content at maturity time were found to be appropriate to produce high quality maize seeds. The early harvest, or in other terms 45% moisture content of the seed at the time of harvest, resulted in enhanced activities of Catalase, Ascorbate peroxidase and Malone Dialdehyde enzymes in different tests. On the other hand, the maximum activities of the Antioxidant enzymes were found in the germination test under drought stress conditions in the amount of 36.6 µmolmin− 1mgprotein Catalase and 2829 nmolmin− 1mg Ascorbate peroxidase.
Weakly supervised and semi-supervised semantic segmentation makes full use of a small amount of labeled data
Authors: Zhang Wenming , Wang Zhe , Li Haibin , Li Yaqian
Published: December 2023

Weakly supervised semantic segmentation based on im-age-level annotations is a very challenging task, which has been studied in the past few years. Most studies train the clas-sification network and obtain the activation maps (CAMs) from the deep part of the classification network, that is, the part closer to the classification end, which results in that the information extracted from the shallow network is not fully utilized. In this paper, we propose a weakly supervised shal-low assisted-supervision (ASS) strategy to introduce semantic information to the shallow network. Not only that, we also fuse the improved shallow features with the deep features to introduce spatial information to the deep features. Our pro-posed auxiliary supervision strategy helps the network to gen-erate better CAMs and improve the feature extraction ability of the network. The classification network often only focuses on the most discriminative part of the picture, which leads to the phenomenon of insufficient activation of CAMs. There-fore, we propose the Multi-scale global association module (MSG). This module uses the correlation degree of different scale regions to improve the weight of the non-discriminative part, and solves the problem of insufficient CAMs activation. Semi-supervised semantic segmentation refers to a strategy that only a small number of samples have pixel-level labeling information, which is between full supervision and weak su-pervision. In previous studies, semi-supervised and weak su-pervision are trained separately. We design a new training strategy that combines semi-supervision with weak supervi-sion, and add pixel-level supervision to the training process of weak supervision, which gives full play to the role of pixel-level annotation. Extensive experiments on the PASCAL VOC 2012 dataset show that our weakly supervised training strat-egy achieves the state-of-the-art, and the combination of weakly supervised and semi-supervised training strategy can make more effective use of pixel-level labels.
Temperature-Dependent Iron Motion in Extremophile Rubredoxins – No Need for ‘Corresponding States’
Authors: Cramer Stephen , Jenney Francis , Wang Hongxin , George Simon , Xiong Jin , Guo Yisong , Gee Leland , Marizcurrena Juan , Castro-Sowinski Susana , Staskiewicz Anna , Yoda Yoshitaka , Hu Michael , Tamasaku Kenji , Nagasawa Nobumoto , Li Lei , Doukov Tzanko , Matsuura Hiroaki
Published: December 2023

Extremophile organisms are known that can metabolize at temperatures down to -25°C (psychrophiles) and up to 122°C (hyperthermophiles). Understanding viability under extreme conditions is relevant for human health, biotechnological applications, and our search for life elsewhere in the universe. Information about the stability and dynamics of proteins under environmental extremes is an important factor in this regard. Here we compare the dynamics of small Fe-S proteins – rubredoxins – from psychrophilic and hyperthermophilic microorganisms, using three different nuclear techniques as well as molecular dynamics calculations to quantify motion at the Fe site. The theory of ‘corresponding states’ posits that homologous proteins from different extremophiles have comparable flexibilities at the optimum growth temperatures of their respective organisms. Although ‘corresponding states’ would predict greater flexibility for rubredoxins that operate at low temperatures, we find that from 4K to 300K, the dynamics of the Fe sites in these homologous proteins are essentially equivalent.
Mixed Conduction in Iodovanadate Glass-Nanocomposites: DC Conductivity, Hopping Frequency and Frequency Response Curves
Authors: Poddar Asmita , Roy Madhab , Ali Mir Sahidul , Chattopadhyay Dipankar , Halder Prolay , Bhattacharya Sanjib
Published: December 2023

Here, the system of amorphous semiconducting glassy system, xAgI − (1-x) (0.1CdO − 0.3 V2O5 − 0.4 P2O5 − 0.2ZnO) with x = 0, 0.05, 0.1, 0.2, 0.3, 0.4has been developed. The gradual change in the size of various nanocrystallites such as VO2, Zn2V2O7, V6O13, ZnV3O8 and P and the development of new phases of their combinations have been pronounced due to a gradual increase in AgI content. This may lead to the possible structural changes of the system under investigation. V-O-V vibration at lower energy may be responsible for weakening the covalent bond, which may be responsible for releasing vanadium ion to contribute more electron/ polaron. Correlated barrier hopping (CBH) model has been found to appropriate to predict the hopping conduction paths of charge carriers (or polarons) in pairs via current transfer between localized sites at the Fermi level. By incorporation of more and more AgI content in the composition, more bridging oxygen is expected to be formed in the composition and a strong covalent bonding between Ag+ and O− 2 may play dominating role for Ag+ transport over polaron hopping. Double activation energy corresponding to DC conductivity in a wide range of temperature may be considered as the signature of mixed conduction process in the present system.Estimated values of frequency exponent (n) may be highlighted to validate this mixed conduction process. Percolation type of motion of polaron may be predicted from the higher values of n for the as-prepared samples with higher AgIcontent. Similarly, three dimensional Ag+ motion may be the dominating charge carriers for the samples with higher AgI content as evident from the moderate values of n.A schematic conduction model has been proposed to explain the nature of electrical conductivity in the present system.
Rapidly progressive interstitial lung disease in the course of juvenile dermatomyositis: a case report
Authors: Oniszczuk Eliza Rebeka Siemaszko - , Jakubów Piotr , Tałałaj Mariola , Turczynowicz Aleksander , Konstantynowicz Jerzy
Published: December 2023

Background
Juvenile dermatomyositis is a systemic, autoimmune inflammatory muscle disorder and vasculopathy. While generally it is well-responsive to the standard line of therapy, in rare cases may develop life-threatening complications and show resistance to treatment. We presented the case of a 7-year-old, who developed rapidly progressive interstitial lung disease and pancreatic dysfunction in the course of fulminant juvenile dermatomyositis with a good outcome after aggressive immunosuppressive therapy with the use of rituximab. Our case illustrates the diagnostic challenges of this condition in the setting of non-specific clinical manifestations and a need for novel molecular mechanism-based treatment to improve the survival of refractory dermatomyositis.
Case presentation
A 7-year-old girl presented with erythematous rash, muscle weakness, pain of lower extremities and elevated body temperature. The patient was diagnosed with juvenile dermatomyositis through physical examination (typical skin manifestation, proximal muscle weakness) and based on the finding of elevated levels of serum muscle enzymes and myopathic EMG changes. In the course of the disease she developed interstitial lung disease rapidly progressing to respiratory dysfunction and pancreatic failure. She received combined therapy, including methylprednisolone pulse therapy, followed by intravenous immunoglobulin, both in maximum doses per kilogram. On the 20th day of hospitalization, she was admitted to the intensive care unit and placed on ventilation support. On the 11th day of assisted ventilation rituximab was administered. Because of pancreatic dysfunction, complicating the course of the disease, the child was placed on total parenteral nutrition. After 3 doses of rituximab her general state and respiratory condition showed gradual improvements. Eventually, after 23 days of ventilation support, the patient could be successfully extubated. When the enteral nutrition was re-established and the underlying disease reached the stage of satisfactory improvement she was discharged to an out-patient setting.
Conclusions
In juvenile dermatomyositis, rituximab may be a promising agent for treatment of rapidly progressive interstitial lung disease. It may also play a role in the therapy of simultaneous pancreatic dysfunction. In the future, the efficacy of rituximab in the refractory form of the disease should be further investigated.
EMPOWER-UP: psychometric evaluation of a generic questionnaire for assessing empowerment in relational decision-making and problem-solving among adults with long-term health conditions
Authors: Marqvorsen Emilie Haarslev Schröder , Petersen Morten Aagaard , Lund Line , Pouwer François , Thomsen Thordis , Mathiesen Anne Sophie , Rothmann Mette Juel , Jørgensen Rikke , Winkley Kirsty , Rasmussen Bodil , Skytte Tine Bruhn , Ntoumanis Nikos , Alexander Karyn , Zoffmann Vibeke
Published: December 2023

Background
Relational decision-making and problem-solving are powerful activities occurring daily across all healthcare contexts. Their empowering potential can be difficult to judge and is seldom fully exploited, and they can even be perceived as disempowering. This calls for assessment of the extent to which healthcare users perceive their interactions with healthcare providers as empowering. We developed a 36-item draft version of the generic EMPOWER-UP questionnaire deemed to have good face and content validity by healthcare users and researchers with expertise across multiple healthcare contexts. This article reports the psychometric properties of the Danish and English versions of the questionnaire.
Methods
A cross-sectional study was carried out among 526 adults diagnosed with diabetes, cancer, or severe mental illness in Denmark, United Kingdom, and Australia with recent (≤ 6 months) interaction with a healthcare provider. We evaluated structural validity, cross-cultural validity, and measurement invariance using confirmatory and exploratory factor analyses, item response theory modelling, and differential item functioning. Additionally, we evaluated empirical reliability and internal consistency.
Results
The final 24-item Danish and English versions of EMPOWER-UP has a three-factor second-order structure. The three factors of empowering mechanisms (14 items), disempowering mechanisms (6 items), and empowering insight (4 items) are connected through the second-order factor, realizing empowerment. Partial credit model calibration supported the use of summed subscale item scores, enhancing usability in clinical practice settings. Differential item functioning analysis demonstrated invariance across subgroups. Empirical reliability of the subscales was estimated at 0.85–0.95, and Cronbach’s alpha was 0.90–0.96.
Conclusions
The 24-item EMPOWER-UP questionnaire measuring empowerment in relational decision-making and problem-solving showed strong psychometric properties among adults with cancer, diabetes, and severe mental illness. Further evaluation in other contexts and populations is needed, including evaluation of construct validity, responsiveness to change, and test-retest reliability.
Alpha lipoic acid diminishes migration and invasion in hepatocellular carcinoma cells through an AMPK-p53 axis
Authors: Hidalgo Florencia , Ferretti Anabela C. , Etichetti Carla Borini , Baffo Emilia , Pariani Alejandro , Maknis Tomás Rivabella , Bussi Javier , Girardini Javier E. , Larocca María C. , Favre Cristián
Published: December 2023

Hepatocellular carcinoma (HCC) associated with viral or metabolic liver diseases is a growing cancer that lacks effective therapy. AMPK is downregulated in the early stages of HCC and its activation diminishes tumor progression in culture and in vivo. Alpha lipoic acid (ALA), an indirect AMPK activator that inhibits hepatic steatosis in rodents, shows antitumor effects in different cancers. We aimed to study the putative antitumor action of ALA in HCC cells through AMPK signaling. ALA led to significant inhibition of cell migration and invasion in HCC cells with wild-type TP53. We showed that these effects depended on AMPK, and ALA also increased the levels and nuclear compartmentalization of the AMPK target p53. The anti-invasive effect of ALA was abrogated in stable-silenced versus isogenic-TP53 cells. Furthermore, ALA inhibited epithelial-mesenchymal transition in control wild-type TP53, but no significant changes of EMT markers were observed in silenced TP53 cells. In addition, we spotted that in patients from the HCC-TCGA dataset some EMT genes showed different expression patterns or survival profiles depending on TP53 status. ALA emerges as a potent activator of AMPK-p53 axis in HCC cells, and it decreases migration/invasion by reducing EMT which could mitigate the disease in wild-type TP53 patients.
Novel long small RNAs (lsRNAs) are evolutionary conserved in plants and differentially expressed during epitype inducing conditions in Norway spruce embryos
Authors: Yakovlev Igor , Nakamura Miyuki , Viejo Marcos , Zhang Yupeng , Fossdal Carl Gunnar
Published: December 2023

Small non-coding RNA (sRNA) and the various other RNA species have tissue specific expression profiles. However, some size fractions may be missed or left out in the sequencing library preparation process, sequence data processing and downstream bioinformatic analysis. Here, we performed sRNA profiling in embryonic and vegetative tissues to elucidate a more complete picture of the gymnosperm sRNA populations than previously reported. We detected a novel group of sRNA between 31–34 nt in our Norway spruce sequencing data, with a prevalence in the 32–33 nt fraction, defined as the long small RNAs (lsRNAs). These lsRNAs were predominantly present in embryonic samples of Norway spruce. An in-silico analysis indicated that these lsRNA could originate from transfer RNAs (tRNA) and other non-coding transcripts and thus may target other non-coding RNAs (including tRNAs) or target repetitive elements such as transposons. We identified 18 putative orthologs of genes involved in Piwi-interacting RNA (piRNA) biogenesis but no spruce proteins were true homologs to the animal Piwi-proteins, thus lsRNAs cannot be considered as plant analogs to the animal piRNAs. Among the lsRNAs, tRNA-derived sequences from Asp, Glu and His iso-acceptors were in a majority and these sequences showed 3’ or 5’- bias dependent on the iso-acceptor type putatively targeted. The lsRNA sized fraction was detected in seeds of all the gymnosperms examined and in Arabidopsis thaliana, suggesting that these comprise a conserved type of sRNAs between gymnosperms and angiosperms. lsRNA levels differed significantly among tissue types and developmental stages, and interestingly their expression was impacted by epitype-inducing temperature conditions. The lsRNAs add to the complexity of the small RNA world and may play a role in epigenetic regulation of gene expression in plants.
Flexible Multi-Layered Security System: Secure 6G Mobile Network Considerations
Authors: Sr Tarek , El-Bendary Mohsen A. M. , Eltokhy Mostafa , Abouelazm Atef E.
Published: December 2023

The vision of 6G networks refers to linking undersea, terrestrial, and space networks together. This vision involves transferring a massive amount of data over the network. 6G network requires very high levels of security. This paper presents the proposed vision of 6G security. This paper focuses on security levels on 6G network. The paper proposes a multi-level security system that secures the data without affecting it. The multi-level security system consists of three security levels, which are two encryption techniques and a data hiding technique. The paper carried outmany simulation experiments to find the best integration of these techniques that provides the best security performance without affecting the data. The best simulation experiments that provided the best data security performance were the integration between 2D Logistic map, SVD, and Baker Map, respectively. This system provided the best simulation results for data security. The simulation results indicated a perfect match between the original message and the decryption original message after applying the system. The results also indicated that there was no effect on the data and no loss of data.
A Study of Online Academic Risk Prediction Based on Multivariate Time Series Features
Authors: Yu Mengping , Hou Rui , Huang Huan , Wu Yang , Fan Fulan , Yuan Shuai
Published: December 2023

Academic risk prediction is a hot topic in the field of big data in education that aims to identify and help students who experience great academic difficulties. In recent years, the use of machine learning algorithms to achieve academic risk prediction has garnered more attention and development. However, most of these studies use static statistics as features for prediction, which are slightly insufficient in terms of timeliness. To be able to capture students who have difficulties in course learning in a timely manner and to improve the academic performance of school students, this paper proposes a method based on multivariate time series features to predict academic risk. The method includes three steps: first, the multivariate time series feature is extracted from the interaction records of the students' online learning platforms; second, the multivariate time series feature transformation model ROCKET is applied to convert the multivariate time series feature into a new feature; third the new feature is converted into a final prediction result. Comparative tests show that the proposed method has high effectiveness.
An exploration of the impact of phylogenetic tree structure on NTI and βNTI estimates of community assembly
Authors: Gundersen Madeleine , Vadstein Olav
Published: December 2023

The nearest taxon index (NTI) and beta nearest taxon index (βNTI) are popular analytical tools for assessing the community assembly processes in a variety of ecosystems. However, the fundamental dependence of these models on the underlying phylogenetic tree is often overlooked and can potentially lead to erroneous conclusions. In this paper, we investigated how outlier sequences in the phylogenetic tree and reduction of the metacommunity richness affect estimates of the assembly processes. We estimated assembly in two datasets investigating fish-microbiota interactions. We found that outlier sequences can drastically change the interpretation of assembly processes. NTI consistently increased after outlier sequences were removed, which changed the ecological interpretation for 82.8% of the communities in one of the datasets. Similarly, βNTI was strongly affected by outliers in the phylogenetic tree, changing the ecological interpretation for 44.7% (Dataset 1) and 6.3% (Dataset 2) of the community comparisons. Lower metacommunity richness generally resulted in decreased NTI and increased βNTI, but the effect sizes were small and generally did not result in a change in ecological interpretation. This exploratory work highlights the need to assess the phylogenetic tree for spurious outlier sequences prior to null model analysis.
Brain Connectivity Analysis Based Classification of Obstructive Sleep Apnea using Electroencephalogram Signals
Authors: Rajeswari J. , Jagannath M.
Published: December 2023

Obstructive sleep apnea (OSA) is a disorder which blocks the upper airway during sleep. The severity of OSA will lead heart attack, stroke and end of life. This proposed study explored the classification of OSA and healthy subjects using brain connectivity analysis from electroencephalogram (EEG) signals. ISRUC database were used for acquiring 50 EEG signals using 4 channels and noise removal has been accomplished by 50 Hz notch filter. Wavelet packet decomposition method was performing the segregation of EEG signals into five bands; Gamma (γ), beta (β), alpha (α), theta (θ) and delta (ẟ). A total of 4 electrode positions were used for the brain connectivity analysis for each EEG band. Pearson correlation method was effectively used for measuring the correlation between healthy and OSA subjects. The nodes and edges were highlighted the connection between brain and subjects. The highest correlation was achieved in delta band of OSA subjects which starts from 0.7331 to 0.9172 respectively. For healthy subjects, the positive correlation achieved was 0.6995. The delta band has been correlated well with brain when compared other bands. It has been noted that the positive correlation well associated with brain in OSA subjects, which classifies OSA from healthy subjects.
OCL2NL: Automatic Generation Natural Language Description from OCL Contracts
Authors: Yang Yilong , Li Qizhen , Niu Nan , Liu Yibo , Bao Tianshu
Published: December 2023

Formal contracts play a crucial role in precisely specifying system requirements and facilitating the verification of system implementation through automated test case generation or formal verification techniques, particularly in the development of safety-critical systems. The Object Constraint Language (OCL) is a lightweight formal language widely utilized for expressing constraints in UML-based models. However, due to the semantic gap between OCL expressions and their interpretations, comprehending OCL contracts can be challenging.In this paper, we propose a novel approach called OCL2NL, which enables the automatic generation of natural language descriptions from OCL contracts. OCL2NL encompasses a comprehensive set of translation rules and algorithms that map OCL contracts to semantic and signature descriptions of system operations. To validate our approach, we conduct four case studies. The results demonstrate a high success rate, with 97.06% of the OCL expressions and 87.68% of the signatures generating accurate descriptions. Moreover, domain experts evaluate that 50 out of 52 descriptions of OCL expressions and 11 out of 12 signature descriptions effectively capture essential information about the corresponding OCL contracts. The natural language descriptions significantly enhance the understanding of OCL contracts when compared to the contracts alone. Overall, the results are promising, indicating the potential extension of our proposed approach within the software industry.
Overall performances of Leucaena leucocephala and Morus alba in high-density shrub fodder banks at maturity in western Burkina Faso Running head: Performance of High-density fodder banks for livestock feeding
Authors: Sib Ollo , González-García Eliel , Vall Eric
Published: December 2023

The objective of this work was to carry out a long-term monitoring of shrub fodder banks (SFB), established under the real-low-input-farm conditions of Burkina Faso, characterised by a Sudano-Sahelian climate type with wide variations in rainfall. The SFBs, which were planted in 2016-2017 with Leucaena leucocephala (LL) and Morus alba (MA) at a high-density (20,000 plants/ha), were monitored from 2016/2017 to 2021 for their biomass (fodder) production, chemical composition and nutritive value of the edible forage, and their impacts on soil carbon content. The average annual forage production of LL for the 6 SFBs (1, 2, 3, 4, 5 and 6) was 11.4 ± 2.12 t DM/ha/year while that of MA was 3.8 ± 1.2 t DM/ha/year for the 3 SFB (1, 2, and 3). Such differences are likely related to higher adaptive capacity for LL in such climatic conditions. The high nutritive value observed in both fodder resources agreed with available literature worldwide. Crude protein was higher in LL (19% vs. 17%), but dry matter digestibility (65% vs 77%) were superior in MA. Soil carbon increased during the five monitored years, which is an interesting result for these poor, low fertility soil conditions. Our results demonstrate the technical and environmental feasibility for establishing this low-input agroforestry technology in these conditions, as an agroecological alternative to overcoming feed shortages for local livestock farming. However, the successful management of a SFB relies on the selection of the right species, the protection provided, and the management during the establishment and fodder production periods, with suitable cutting frequency and appropriate post-harvest management.
Human-Machine Cooperative Program Translation Based on Abstract Syntax Tree
Authors: Zhang Fengming , Liu Jiaqi , Yu Zhiwen , Guo Bin
Published: December 2023

Program translation involves converting one programming language into another, which can modernize and migrate applications across platforms. Most of the current program translation methods are sequence-based, which cannot capture the semantic information of the code. To overcome this, abstract syntax tree-based program translation rises up. However, even the state-of-the-art machine translation methods can not guarantee error-free translation results. Consequently, software engineers need to make corrections on the machine's results before using, which is labor-intensive. To solve this problem, we propose the Human-Machine Cooperative Program Translation Based on Abstract Syntax Tree (HMPT-AST), which feeds the human's modification into the model in each iteration and the model updates the result based on human's feedback. It enables two patterns of human participation: First-error-based and Layer-based HMPT-AST. In the former one, the software engineer corrects one error node in each iteration. In the latter one, all error nodes within the same layer are corrected. In addition, the proposed method can also reduce the interactive response time from two aspects: avoiding generating the correct AST subtree repeatedly with parameter cache module, as well as reducing the generation of unnecessary AST subtree with early termination module. We conducted experiments on multiple dataset. The results show that compared with baselines, our method reduces the human effort up to 94.44\% and reduces the response time up to 94.32\%. We have made the code publicly available.\footnote{https://drive.google.com/drive/folders/1878Or6cEsW21fu_cpdpnv_dGevfFr9mB?usp=sharing}
Is local excision with chemoradiotherapy the optimal treatment for early stage rectal cancer patients？a population-based study
Authors: zhu si rui , Tu Jiawei , Pei Wei , Bi Jianjun , Zheng Zhao-xu , Feng Qiang
Published: December 2023

Objective Adjuvant chemoradiotherapy in early stage rectal cancer is still controversial. The purpose of this study was to access the survival benefits of chemoradiotherapy for overall survival (OS) and cancer-specific survival (CSS) in patients with early stage rectal cancer and find the optimal treatment for these patients.
Methods The study analyzed data from patients diagnosed with T1-2N0M0 rectal cancer between 2010 and 2016, using the Surveillance, Epidemiology, and End Results (SEER) database. The researchers then divided the patients into low-risk and high-risk groups based on various prognostic factors. Kaplan-Meier analysis was employed to evaluate the impact of chemoradiotherapy on OS and CSS in these patient groups.
Results The Kaplan-Meier analysis revealed that patients with T1 stage (T1N0M0) had better OS and CSS outcomes than the T2 stage (T2N0M0) groups. Furthermore, it was shown that both low-risk groups of T1 stage and T2 stage had better OS and CSS outcomes than the high-risk groups. No significant benefits was shown when adding chemoradiotherapy in T1 stage groups while it was observed significant improvements for OS and CSS in T2 stage groups. Furthermore, local excision alone in T1 stage groups and local excision with chemoradiotherapy in T2 stage shown no significant difference comparing to those treated with segmental resection.
Conclusion In our study, we found that chemoradiotherapy was beneficial for T2N0M0 rectal cancer patients. What’s more, local excision alone was a feasible alternative for T1N0M0 rectal cancer patients and local excision with chemoradiotherapy was a promising alternative for T2N0M0 rectal cancer patients.
Informal recycling sector contribution to plastic pollution mitigation: A systematic scoping review and analysis of prevalence and productivity
Authors: Cook Ed , Cano Nathalia Silva de Souza Lima , Velis Costas A.
Published: December 2023

A large global workforce of informal entrepreneurs has historically dominated circular economy practices in the Global South, collecting many millions of tonnes of waste for recycling, and supplementing insufficiencies in struggling municipal waste management systems. Ongoing negotiations for a ‘Legally Binding Instrument on Plastic Pollution’ implicitly recognise the substantial contribution made by the informal recycling sector (IRS - waste pickers) to plastic pollution mitigation. To this, we carried out a systematic scoping review of IRS prevalence and productivity following the PRISMA-ScR method followed by extensive data analytics. Waste pickers represent median 0.2% (interquartile range – IQR: 0.1-0.5%) of the urban population worldwide, collecting between 20 kg and 80 kg of engineered materials for recycling each day, of which 30% (mean wt. ar) are plastics. We identify substantial shortcomings in most methodologies used to gather data on the IRS, introducing epistemic uncertainty into some previous estimates of the sector’s activity. We recommend development of a standardised resource-efficient method of sampling and data gathering, suitable for implementation at municipal/local scale. Our work offers verifiable quantitative knowledge on the sector’s activities to date, suitable for use in plastic pollution quantification models and local/national action plans required to baseline and monitor progress towards multilateral targets.
Biosorption of Fluoride from Water Using Aluminum Hydroxide Modified Activated Carbon from Composte Coffee Husk and Corn Cob
Authors: Hirbo Hirbo Geremew , Hola Roba Nebi
Published: December 2023

The earth's crust contains the highest concentration of fluoride minerals. Long-term exposure to water containing fluoride concentrations higher than the 1.5 mg/L WHO recommendation can be harmful to one's health and cause dental, skeletal fluorosis, neurological, and thyroid problems. Therefore, it is imperative to create an affordable, accessible, and eco-friendly way to remove fluoride from water using activated carbon made from a locally available composite of maize cob and coffee husk. In this study, coffee husk and maize cob were ground, dried, and calcined in a muffle furnace at 500°C for two hours. The materials were then activated with a 30% aqueous Al (OH)3solution. To describe its properties, the resultant activated carbon—known as CMAC (coffee husk and maize cob derived activated carbon) was put through proximate and ultimate analysis. Using batch adsorption methods, the impact of several parameters, including pH, sorbent dosage, contact time, and initial fluoride concentration, is investigated with respect to the extraction of fluoride. The adsorption kinetics were investigated using pseudo first and second-order kinetic analysis, and Freundlich and Langmuir isotherms were used for analysis. The study's maximum fluoride removal efficiency of 88.1 percent was attained with an initial fluoride concentration of 10 mg/L, pH of 3, contact time of 90 minutes, and adsorbent dosage of 3 grams. It is discovered that CMAC works well as an adsorbent to remove fluoride from water. The study's adsorption data had pseudo-second-order kinetics (R^2 = 0.957) and a high coefficient of determination (R^2 = 0.976), indicating a good fit to the Freundlich isotherm model. These results point to a high potential for efficiently removing fluoride from aqueous solution using the modified adsorbent CMAC composite.
Optimization validation of online system for COD variation measurement in wastewater at levels of parallel matrixes designed through bias correction by Deming regression under AD hypothesis test
Authors: Douwen Wang
Published: December 2023

Chemical oxygen demand (COD), with its unique socio-economic structure and conditions in regional wastewater of Dalian, China, can bring about the long-term potential harm impacts to ecosystems and human health. As the key indicators of total sewage discharge control and the must-measure item for routine testing in China, COD test is basically completed by the online system (as X-method). However, X-method belongs to the domains of non-standard, and the validity of its reported results deserves attention. The background effect treatment has been debated when dealing with the accuracy of COD test, and the usual practice is referred to the matrixes spikes at multiple levels. However, we hold the opinion that COD of the actual extraction efficiency (naturally existing matrix matched), is out of the question while measuring for unstable samples greatly fluctuated in wastewater, with its instantaneous effluent and temporal and spatial characteristics, and cannot be repeated and predicted. Instead, we decided to use regression to solve this problem. We may assess the methodology of leverage (hi) and Cook’s distance (Di) to identify influential observation prior to model transformation for ordinary least squares (OLS) fitting, in which, the random parallel samples designed, within each level consistent differing by ≤ 10%, is deployed to establish the bias correction reasoning between X-method and the arbitration, referee or primary system (as Y-method). As OLS fitting is, yielding biased and inefficient estimates, not suitable for uncertainties existed in both regressed variables, instead, we use a knowledge-based Deming regression (DR) to optimally monitor and validate the validity of X-method system. In this paper, we give the detailed fitting process of DR technique with its weighted iteration accounted for measurement error in both methods. To ensure the residuals, in chronological order, deduced from the bias correction function, under independence identical distribution (i.i.d) condition, we strongly advocate a more robust Anderson Darling (AD) hypothesis test for validation of X-method. If the AD null hypothesis is held, we further hold the opinion that X-method is, under the site precision (sR'), reliable for its COD determination in wastewater. Meanwhile, the sR' is more appropriate to maximally incorporate all cumulative effects, even with the annoying interaction, into the data quality objective (DQO) of the COD system over an entire range levels range, and minimize the intractable problem caused by matrix effect. Our motive is to compare the COD variation measurement from real-time online system, across all matrices, with the results obtained historically or subsequently, to meet client’s needs in a way that allows the operation of the COD system from X-method in consistency, in impartial, in competency, and to assist management decision making.
Picard Estimation Method for the Weibull Extension Model Parameters
Authors: Maswadah M.
Published: December 2023

In parameter estimation techniques, the Bayesian estimation method is the most common technique that has been used in social science and psychology, despite the fact that it is subjective to prior information other than data, which worries some statisticians. Thus, the main objective of this paper is to introduce a numerical iteration technique, which is Picard’s method for estimating the distribution parameters. This method has been applied for deriving the estimators for the Weibull extension model parameters and compared with the Bayes method via Monte Carlo simulations. The simulation results indicate that Picard’s method is strongly favorable because it provides better estimates and outperforms the Bayes method. Finally, numerical examples are given to demonstrate the efficiency of the proposed methods.
Numerical Estimation for the Three-Parameter Burr-XII Model Parameters Based on Picard’s Method
Authors: Maswadah M.
Published: December 2023

In parameter estimation techniques, there are several methods for estimation in lifetime distributions and reliability theory. However, most of them are less efficient than the Bayes method based on the informative prior. Thus, the main objective of this study is to present an optimal estimation technique using Picard’s method for estimating the three-parameter Burr type-XII distribution parameters. A comparison between the Picard and Bayes methods is provided using an extensive Monte Carlo simulation based on two criteria, namely, the average bias and the mean squared error. The simulation results indicate that Picard’s method is highly efficient and outperforms the Bayes method based on the generalized progressive hybrid censoring scheme. Finally, two real dataset analyses are presented to illustrate the efficiency of the proposed methods.