Miracle-dz/UniFAR-FTUs huggingface dataset:
Weblog : an alternative platform to deliver formal lifelong learning

Weblogs (or blogs) usually contain diary style content, with updates posted on a regular basis and displayed in reverse chronological order controlled by a single author. The blogs can be publicly accessed by anyone or by invitation from the blog’s author. The content or use of a blog is the choice of the author and may include news, updates, articles, and reflections. The small but developing literature on web logging underscores its potential as an effective learning resource for use in higher education. Some advantages of blog for learning include assisting students to become subject-matter experts through a process of regular scouring, filtering and posting, increasing student interest and ownership in learning, giving students legitimate chances to participate and acculturating them into a community of practice and providing opportunities for diverse perspectives. However, the use of the blog for formal lifelong learning is very much limited as the open universities prefer to use their own learning management systems or other online platforms to deliver the teaching and learning activities. This paper contributes to these discussions through a case study of the author's experience with the on-going development of an educational blogging resource for use in an undergraduate IT subject. Using the instructional strategy of independent study and indirect instruction to support the learner-centered pedagogies, the author believe the elements of content, interactivity, collaboration and assessment are the pillars to make an education-based blog for adult learners to support their self-managed learning. Detailing the theoretical aims, design, implementation and students’ evaluation of the blog, the paper puts forward the argument for the educational use-value of blogging as a platform to support self-managed learning for adult learners in the formal lifelong learning environment. (Abstract by author)
Fabricating High-Resolution and High-Dimensional Microneedle Mold through the Resolution Improvement of Stereolithography 3D Printing

Microneedles are transdermal drug delivery tools that can be fabricated simply, economically, and rapidly using SLA 3D printing. However, SLA 3D printing has a limitation in that the resolution is slightly lowered when the microneedle is precisely printed. To solve this issue, we optimized the SLA 3D printing conditions such as printing angle, needle height, aspect ratio, and spacing between the microneedles for high-resolution microneedle fabrication. The sharpest microneedle tip was obtained when the printing angle was adjusted to 60° in both the x and y axes. The aspect ratio and the spacing between the microneedles did not affect the output of the sharp tip. Under optimal conditions, the microneedles with 1180 ± 20 µm height, 490 ± 20 µm base, and 30.2 ± 3.4 µm tip diameter were obtained. The dissolving microneedle patch, prepared using the 3D printed microneedle as a mold, penetrated the porcine skin ex vivo. When the printing angle was 60° in the x and y axes, the area of the single stacking layer, including the microneedle tip, increased, and thus the sharp tip could be printed. A high-dimensional, side-notched arrowhead (SNA) microneedle was fabricated by applying the SLA 3D printing condition. Moreover, a letter-type microneedle patch was fabricated using the customized characteristics of 3D printing. Consequently, high-resolution and high-dimensional microneedles were successfully fabricated by adjusting the printing angle using a general SLA 3D printer, and this technology will be applied to the manufacture of drug delivery tools and various microstructures.
Flexibilization of Biogas Plants through Intelligent Automation Generates Earning Opportunities

Due to guaranteed feed-in tariffs under the Renewable Energy Act and the feed-in precedence of renewable power generation plants the operation of biogas plants in Germany is currently plannable and economically advantageous. However, it is foreseeable that without this subvention biogas plants cannot compete with other regenerative plants such as photovoltaic and wind power plants on the open electricity market. Accordingly, it is of great importance for biogas plant operators to identify and occupy suitable niches to make full use of the unique features of their plants. Because of their predictable availability, those plants can particularly benefit of earning opportunities in times of high demand and contribute to grid stabilization. In order to keep the effort for plant operators as low as possible the automation of existing biogas plants can be extended and enabled to communicate with market platforms or control centers of the distribution system operator. Thus biogas plants can contribute to balancing group compensation not only for accounting purposes but factual by appropriate feed-in into the electrical network in consideration of actual demand.
Kinetic Studies on the Biosorption of the Brominated Flame Retardant 4-Dibromodiphenyl ether (BDE-3) using Coconut Palm Leaf Powders

Methods such as membrane isolation, ion replacements, precipitation, transformation and biosorption are proven approaches to contaminant control. Biosorption has all of these technological features including low operating costs, very efficient detoxifying of toxicities at low volumes, minimal amounts of removal components and nutrient requirement, as well as bacterial remediation, which are limited to the presence of heavy metals and other toxicants. The biosorption of BDE-3 on coconut leaves powder on the biosorption of BDE-3 from coconut leaves powder were analyzed using three modelsâ€”pseudo-1st, pseudo-2nd and Elovich, and fitted using non-linear regression. Statistical analysis based on root-mean-square error (RMSE), adjusted coefficient of determination (adjR2), bias factor (BF), accuracy factor (AF), corrected AICc (Akaike Information Criterion), Bayesian Information Criterion (BIC) and Hannanâ€“Quinn information criterion (HQC) showed that the Pseudo-2nd order model is the best model. Kinetic analysis using the Pseudo-2nd order model gave a value of equilibrium sorption capacity qe for 0.01 g per L adsorbent of 488.16 mg g-1 (95% confidence interval from 463.68 to 512.64) and a value of the Pseudo-2nd-order rate constant, k2 of 0.00019 (95% confidence interval from 0.00010 to 0.00027) while the equilibrium sorption capacity qe for 0.002 g per L adsorbent of 2403.61 mg g-1 (95% confidence interval from 2313.99 to 2493.22) and a value of the Pseudo-2nd-order rate constant, k2 of 0.000043 (95% confidence interval from 0.000027 to 0.000059). These calculated values will be very useful in designing effective sorption experiment and understanding the limitations of the system developed.
On the ensemble of surrogate models by minimum screening index

The ensemble of surrogate models is attracted more and more attention due to their more stable performance than individual models. This work proposes a novel adaptive ensemble of surrogate models based on the minimum screening index. Constructing the screening index to realize the definition and elimination of a global poor model to further update the model library. Compared with the cross-validation error, this index presents better reliability in the model library update. The baseline model is determined by the minimum screening index to further propose a new weight calculation strategy based on this baseline model. 35 test functions are used to evaluate the performance of the proposed model. The results show that this model presents better accuracy and robustness than the individual surrogates and the other ensemble of surrogate models. More importantly, in engineering applications, the same results are also obtained, indicating that the proposed model has a higher priority than the other ensemble of surrogate models. This effective model gives a new way for the design of engineering problems.
Integration of Neighbor Topologies Based on Meta-Paths and Node Attributes for Predicting Drug-Related Diseases

Identifying new disease indications for existing drugs can help facilitate drug development and reduce development cost. The previous drug–disease association prediction methods focused on data about drugs and diseases from multiple sources. However, they did not deeply integrate the neighbor topological information of drug and disease nodes from various meta-path perspectives. We propose a prediction method called NAPred to encode and integrate meta-path-level neighbor topologies, multiple kinds of drug attributes, and drug-related and disease-related similarities and associations. The multiple kinds of similarities between drugs reflect the degrees of similarity between two drugs from different perspectives. Therefore, we constructed three drug–disease heterogeneous networks according to these drug similarities, respectively. A learning framework based on fully connected neural networks and a convolutional neural network with an attention mechanism is proposed to learn information of the neighbor nodes of a pair of drug and disease nodes. The multiple neighbor sets composed of different kinds of nodes were formed respectively based on meta-paths with different semantics and different scales. We established the attention mechanisms at the neighbor-scale level and at the neighbor topology level to learn enhanced neighbor feature representations and enhanced neighbor topological representations. A convolutional-autoencoder-based module is proposed to encode the attributes of the drug–disease pair in three heterogeneous networks. Extensive experimental results indicated that NAPred outperformed several state-of-the-art methods for drug–disease association prediction, and the improved recall rates demonstrated that NAPred was able to retrieve more actual drug–disease associations from the top-ranked candidates. Case studies on five drugs further demonstrated the ability of NAPred to identify potential drug-related disease candidates.
Role of Depression and Anxiety As Mediators Between Insomnia Symptoms and Suicide Ideation in Patients With Adjustment Disorder

Objective: The aim of this study was to evaluate whether insomnia can independently affect suicide ideation or whether insomnia affect suicide ideation by mediating depression or anxiety in adjustment disorder (AD). Methods: Electronic medical records were retrospectively reviewed for 65 patients with diagnosed AD visited an outpatient clinic between January 2018 and December 2020. Measurements include the Insomnia Severity Index (ISI), Beck Depression Inventory-II (BDI-II), State-Trait Anxiety Inventory (STAI) and Minnesota Multiphasic Personality Inventory-2 (MMPI-2). Statistical analyses were performed to assess relationship between insomnia and suicide ideation in AD and the mediating role of depression or anxiety in this association. Results: During 3 years of study period, of the AD patients, 37 (57%) were male and 28 (43%) were female. Among them, 45 (69.2%) and 23 (35.4%) had clinically significant symptoms of insomnia (ISI ≥15) and suicide ideation (MMPI scale score ≥70), respectively. In a mediation model using depression and anxiety as mediating variable, there were significant effects of insomnia on depression (t=5.55, p<0.001) and anxiety (t=6.21, p<0.001) and of depression (t=5.70, p<0.001) and anxiety (t=3.54, p<0.001) on suicide ideation. Total effect of insomnia on suicide ideation was statistically insignificant, suggesting complete mediation. Conclusion: A significant association with suicide ideation was observed in the case of insomnia accompanied by depression and anxiety. Therefore, in patients with AD who complain of insomnia, symptoms of depression and anxiety should be evaluated by clinicians with active intervention for suicide ideation.
Pulsed Activation Modeling for Chamber Materials of IFE Power Reactors and Experimental Facilities

Inertial confinement fusion (ICF) devices, both test/experimental facilities and fusion energy (IFE) power plants, will operate in a pulsed mode. However, the pulsing schedule in these devices is very different, and it could range from one shot every several days in an experimental facility to some Hz in IFE reactors. The main objective of the present work is to determine whether or not a continuous-pulsed (CP) approach could be an accurate and practical methodology in modeling the pulsed activation experienced by chamber materials of both types of devices. In testing the applicability of the CP irradiation model, we used materials and neutron environment scenarios of the HYLIFE-II reactor and the NIF experimental facility. It is demonstrated that a CP approach consisting of a continuous irradiation period followed by a series of only a few pulses prior to shutdown, can efficiently model the real pulsed operating regimes of the chamber materials, in terms of both accuracy and CPU time consumption. Pros and cons of the model when compared with an equivalent steady-state (ESS) method are discussed, and comparison with the exact pulsed (EP) modeling is also performed.
Pelvic lymph node dissection alone versus adjuvant radiotherapy in node positive penile cancer: A systematic review

Introduction: The management options for regional lymph nodes (LNs) in men with penile cancer include surveillance, surgery, and chemotherapy. The use of radiotherapy (RT) for nodal disease follows tradition and single-institution policies. We aimed to analyse the existing evidence regarding the management of penile cancer patients with suspected or known metastatic pelvic LNs using pelvic LN dissection (PLND) with RT versus PLND or RT alone. Methods: A systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, with no filters for language or time. The search was conducted in EMBASE, MEDLINE/PubMed, and Cochrane Library. Inclusion criteria were adult men with penile cancer and suspected metastatic pelvic LNs, undergoing PLND with or without RT or RT alone. Primary outcomes included disease-specific survival and locoregional recurrence. Secondary outcomes included overall survival and complications of therapy. Results: A total of 552 articles were identified. Only eight retrospective studies were eligible for inclusion (including 406 patients). All studies had a high risk of bias. None of the studies reported the use of neoadjuvant RT. Indications for PLND varied but were usually two or more clinically positive inguinal nodes with or without extracapsular extension. Adjuvant RT was mainly used in positive pelvic LNs or pN2/pN3 stages. The rate of locoregional recurrence following adjuvant RT was 70%. Complications of treatment were reported in two studies only. Conclusions: There is insufficient evidence to recommend the use of adjuvant RT following PLND in penile cancer patients. The quality of evidence is low due to the retrospective design and high risk of bias. Randomized clinical trials are required to assess the efficacy and safety of adjuvant RT and PLND.
Experimental validation of electric bus powertrain model under city driving cycles

Battery electric city bus model has been created and validated with measurement results from a full-scale city bus prototype. The model utilises multi-physics modelling approach with multiple-domains from friction-tyre and transmission model to electrical drive and a simplified battery model. For the electrical drive model, four approaches to model the losses were studied. The modelled and measured motor torque, speed, current in the battery and inverter, and the bus speed were compared under two bus line driving cycles using three payloads. The simulated results were in good agreement with the experimental results; the error between the simulated and measured energy consumptions was 1.5% with the most accurate model.
PREVALENCE OF DIGESTIVE ENDOPARASITES (HELMINTH AND PROTOZOA) IN PIGEON DOMESTIC (Columba livia) MALE AND FEMALE IN TUBAN

This research was conducted to determine the prevalence of major gastrointestinal helminthiasis and protozoal infections, the kinds of helminth and protozoa that infects and the effect of sex on pigeons in Tuban. Pigeons are taken from five The Tuban area is Widang, Montong, Jenu, Soko, Jatirogo. Each area is taken as many as 20 pigeons consists of 10 male pigeons and 10 female pigeons. Laboratory examinations were carried out in November to December 2021. Samples were examined by the native method, sedimentation, and flotation. Identification using a microscope using a 40x objective scale and 10x ocular scale. Data analysis using chi square test statistical analysis. 81% of the samples were positive for helminthiasis infection. Chi square test statistical analysis showed p value 0.022 (p<0.05) which means significantly different. 71% of samples were positive for gastrointestinal protozoa infection in pigeons in Tuban. Chi square test Results Statistical analysis shows p the value of 0.123 (p>0.05) which means that it is not significantly different. Type of protozoa found that Heterakis gallinarum (45%), Ascaridia columbae (42%), Capillaria sp. (41%), and Eimeria sp. (71%). That prevalence of helminthiasis in male pigeons higher (45%) compared to female pigeons (36%).
A COMBINED BIN PACKING VM ALLOCATION AND MINIMUM LOADED VM MIGRATION APPROACH FOR LOAD BALANCING IN IAAS CLOUD DATACENTERS

Day by day increasing online computation and migration to the cloud, significantly increase the need of proper load balancing. Load balancing ensure service availability and performance to users. Downtime experienced by users is great issue which leads to violation of QoS requirements for users. Improving response time is one of the solution and some extend it helps to meet the SLA. The proposed system has the intention of achieving an improved load balancing performance to cloud data center, and a satisfying service response to users. By focusing on virtualization technology here consider both virtual machine allocation and migration processes to achieve a better load balancing solution. A VM allocation policy called Bin packing and a Minimum loaded VM migration policy based on load threshold are used together to achieve the goal in Infrastructure as a Service cloud environment. A cloud simulation tool called CloudReport is used to perform the simulation of the system. The experimental results show that the approach provides comparatively improved response time and completion time for users.
Genetic diversity of two color morphs of Northern snakehead (Channa argus) unveiled by the mitochondrial DNA D-loop region

Abstract To analyze the genetic background of ‘white’ type Northern snakehead (Channa argus), and provide atheoretical basis for breeding of C. argus, the investigation of genetic diversity and population structure were investigated based on the complete sequences of mitochondrial DNA D-loop region for three cultured ‘white’ type C. argus populations, and four ‘bicolor’ type C. argus populations were used to compare with them; 28 mutation loci and 30 haplotypes were found in the D-loop sequence of all individuals with a total length of 907 bp. The highest haplotype diversity (Hd ) and nucleotide diversity (Pi ) in the ‘white’ type C. argus populations were 0.505 and 0.00057, respectively, which lower than those in the ‘bicolor’ type C. argus populations (Hd = 0.911, Pi = 0.00326). Population differentiation values (F ST) show that the four ‘bicolor’ type C. argus populations had obvious genetic differentiation (Fst: 0.21902–0.49428. p < 0.01), but not in the three ‘white’ type C. argus populations (Fst: −0.00571 to 0.07261. p > 0.05). The phylogenetic tree and Median Joining (MJ) network showed that the genetic distance among ‘white’ type C. argus populations is very close. Therefore, much attention should be paid to protecting population genetic diversity and avoiding inbreeding in the breeding of ‘white’ type C. argus.
MACHINE LEARNING FOR CROP SCIENCE: APPLICATIONS AND PERSPECTIVES IN MAIZE BREEDING

O aprendizado de máquinas (ML) foi um dos principais impulsionadores da análise de dados nas últimas décadas, permitindo a mineração de grandes bancos de dados. Como técnicas de ML permitem a criação de modelos, e reconhecimento, considerando uma premissa de que o computador pode adquirir para realizar a criação sem ser explicitamente programados para tal finalidade. Impulsionados pela eficiência, diversos estudos demonstrados para sua ampla gama de aplicações o melhoramento de milho. Desde a predição de valores genéticos por dados ômicos aplicações de dados de tipagem de alto, os modelos de ML o avanço no desenvolvimento das espécies e auxiliares de desenvolvimento das espécies e auxiliares de ferramentas mais eficientes para seu melhoramento, gerando ganhos de produtividade.Neste contexto,
Effects of EDTA and aqueous plants extract on the developmental and stress tolerance attributes of Spinacia oleracea and Brassica rapa under sewage water regime

Sewage water is causing a potential threat to agriculture sector due to industrial effluents having heavy metals. Present investigation was carried to study the role of ethylenediaminetetraacetic acid (EDTA) or aqueous extracts of Hyacinth and Hedychium on soil quality and growth of spinach and turnip plants irrigated with sewage water (SW). Treatment of plants with SW resulted in an increment of catalase (CAT), peroxidase (POD) and polyphenol oxidase (PPO) activities. However, EDTA or plant extracts further enhanced their activities. At both stages of development of the tested crops, a substantial increase was found in the content of proline and total phenols, indicating the strengthening of the antioxidant protection mechanism to boost the oxidative effects of SW stress. Sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE) studies revealed considerable variation in the protein profile among the different treatments, with an expression of some unique proteins obvious with other treatments. SW treatments increased heavy metals (HM) content in soil and plants; however, EDTA or plant extracts greatly decreased the levels of HMs in both shoots and roots and soils. The present study results suggest that the application of EDTA or aqueous plant extracts can be a useful strategy for phytoextraction in areas irrigated with sewage water.
Applying a novel two-stage deep-learning model to improve accuracy in detecting retinal fundus images

Applications of artificial intelligence (AI) in medical imaging informatics have attracted broad research interest. In ophthalmology, for example, automated analysis of retinal fundus photography helps diagnose and monitor illnesses like glaucoma, diabetic retinopathy, hypertensive retinopathy, and cancer. However, building a robust AI model requires a large and diverse dataset for training and validation. While large number of fundus photos are available online, collecting them to create a clean, well-structured dataset is a difficult and manually intensive process. In this work, we propose a two-stage deep-learning system to automatically identify clean retinal fundus images and delete images with severe artifacts. In two stages, two transfer-learning models based the ResNet-50 architecture pre-trained using ImageNet data are built with Increased threshold values on SoftMax to reduce false positives. The first stage classifier identifies “easy” images, and the remaining “difficult” (or undetermined) images are further identified by the second stage classifier. Using the Google Search Engine, we initially retrieve 1,227 retinal fundus images. Using this two-stage deep-learning model yields a positive predictive value (PPV) of 98.56% for the target class compared to a single-stage model with a PPV of 95.74%. The two-stage model helps reduce by two-thirds the false positives for the retinal fundus image class. The PPV over all classes increases from 91.9% to 96.6% without compromising the number of images classified by the model. The superior performance of this two-stage model indicates that the building of an optimal training dataset can play an important role in increasing performance of deep-learning models.