Miracle-dz/UniFAR-FTUs huggingface dataset:
Inversion of asymmetric histone deposition upon replication stress

Following DNA replication, equal amounts of histones are distributed over sister chromatids by re-deposition of parental histones and deposition of newly synthesized histones. Molecular mechanisms balancing the allocation of new and old histones remain largely unknown. Here, we studied the genome-wide distribution of new histones relative to parental DNA template strands and replication initiation zones using double-click-seq. In control conditions, new histones were preferentially found on DNA replicated by the lagging strand machinery. Strikingly, replication stress induced by hydroxyurea or curaxin treatment, and inhibition of ATR or p53 inactivation, inverted the observed histone deposition bias to the strand replicated by the leading strand polymerase in line with previously reported effects on RPA occupancy. We propose that asymmetric deposition of newly synthesized histones onto sister chromatids reflects differences in the processivity of leading and lagging strand synthesis.
A Systematic Review of the Quantification of Qualitative Data in Proceedings of International Conferences on CSCL from 2005 to 2017

: In computer-supported collaborative learning (CSCL), verbal and non-verbal behaviors among group members are often examined to help investigate how people in groups interact and learn. Analytic methods used on language data that involve a certain degree of quantification are not rare. This study examines the quantification of qualitative data that involves some form of language use in articles included in the proceedings of international conferences on CSCL from 2005 to 2017. The goal of this systematic review is to identify gaps in methodological effort of quantifying human interactions and communication in terms of research contexts, levels of analysis, and time points of assessment. In synthesizing information on these three aspects, we hope to identify trends over the years and encourage more effort in less researched areas.
Moving Beyond the "Façade of Participation": Using Choice-based Design to Enhance Online Discussions

: A universal struggle in online education is encouraging authentic engagement. Nowhere is this familiar challenge more apparent than the online discussion forum, which students often treat as obligatory rather than enriching. This reaction could be due to low self-determination within the course design. Using Self-Determination Theory as its basis, this study seeks to address the question of whether a choice-based course encourages autonomy, competence, and relatedness, and if these result in enhanced engagement in forums.
Transfer Learning for Inference of Metastatic Origin from Whole Slide Histology

Accurate diagnosis of metastatic cancer is essential for prescribing optimal control strategies to halt further spread of metastasizing disease. While pathological inspection aided by immunohistochemistry staining provides a valuable gold standard for clinical diagnostics, deep learning methods have emerged as powerful tools for identifying clinically relevant features of whole slide histology relevant to a tumor’s metastatic origin. Although deep learning models require significant training data to learn effectively, transfer learning paradigms provide mechanisms to circumvent limited training data by first training a model on related data prior to fine-tuning on smaller data sets of interest. In this work we propose a transfer learning approach that trains a convolutional neural network to infer the metastatic origin of tumor tissue from whole slide images of hematoxylin and eosin (H&E) stained tissue sections and illustrate the advantages of pre-training network on whole slide images of primary tumor morphology. We further characterize statistical dissimilarity between primary and metastatic tumors of various indications on patch-level images to highlight limitations of our indication-specific transfer learning approach. Using a primary-to-metastatic transfer learning approach, we achieved mean class-specific areas under receiver operator characteristics curve (AUROC) of 0.779, which outperformed comparable models trained on only images of primary tumor (mean AUROC of 0.691) or trained on only images of metastatic tumor (mean AUROC of 0.675), supporting the use of large scale primary tumor imaging data in developing computer vision models to characterize metastatic origin of tumor lesions.
The effect of stress on memory for temporal context

Stress and emotional arousal interfere with encoding of temporal context memory for episodic events. However, it remains unclear how stress affects more fine-grained temporal memory, such as episodic events sequences and event times. Here, 86 healthy participants (M age = 22.5; 46% women, 54% men) were subjected to either a stress condition (socially evaluated cold pressor test) or a control condition, directly after or at a delay of 30 minutes they were presented the temporal structure of four virtual days. In these virtual days, time was scaled and participants could use clock cues to construe the passage of time within a day. We examined whether acute stress would interfere with encoding of episodic event sequences and temporal memory. Our results show that when learning took place directly after a stressor, virtual time estimates were more strongly biased towards a generalized timeline but temporal memory overall was not differentially affected between the stress and control groups. Exploratory analyses suggest that memory accuracy improved in men and deteriorated in women as a function of subjective stress levels following acute stress. In conclusion, acute stress amplified memory generalization but we found no stress related differences in memory accuracy across levels of temporal granularity,.
Assessing the origins of the European Plagues following the Black Death: A synthesis of genomic, historical, and ecological information

Significance Over the last few years, there has been a great deal of scientific debate regarding whether the plague bacterium, Yersinia pestis, spread from a Western European reservoir during the second plague pandemic, or if it repeatedly came to Europe from Asia. Here, we make a synthesis of the available evidence, including genomes of ancient DNA and historical, archeological, and ecological information. We conclude that the bacterium most likely came to Europe from Asia several times during the second plague pandemic. The second plague pandemic started in Europe with the Black Death in 1346 and lasted until the 19th century. Based on ancient DNA studies, there is a scientific disagreement over whether the bacterium, Yersinia pestis, came into Europe once (Hypothesis 1) or repeatedly over the following four centuries (Hypothesis 2). Here, we synthesize the most updated phylogeny together with historical, archeological, evolutionary, and ecological information. On the basis of this holistic view, we conclude that Hypothesis 2 is the most plausible. We also suggest that Y. pestis lineages might have developed attenuated virulence during transmission, which can explain the convergent evolutionary signals, including pla decay, that appeared at the end of the pandemics.
Please Don't Shoot the Messenger! Prompts in Online Learning Groups - Influences of Nudging Messages' Sender and Publicness on Recipients' Perception and Attribution

Coand socially shared regulation of learning is a challenge for groups in diverse environments – offline and online (Järvelä et al., 2014). Specifically, prompting others to do their share of the work, might be challenging for interpersonal relationships. Thus, addressing the social psychological dynamics in online learning environments, an online experiment was conducted (N = 352). In a 2x(2x)2 between-subjects design the nature of the sender (group member/system), the sender ́s past proficiency (high/low) and publicness (private/public message) were varied to explore whether automated mediation can reduce detrimental effects and enhance impartial message perception, sender impression and causal attribution. Contrasts by sender and proficiency demonstrate improved message perception, sender impression and internal causal attribution when prompts were sent by the system instead of average or low proficient fellow students. Among all groups, public nudges indicate more negative, but also more persuasive perception, however system public and private nudges did not differ.
Hierarchical Text Classification Using CNNS with Local Approaches

In this paper, we discuss the application of convolutional neural networks (CNNs) for hierarchical text classiﬁcation using local top-down approaches. We present experimental results implementing a local classiﬁcation per node approach, a local classiﬁcation per parent node approach, and a local classiﬁcation per level approach. A 20Newsgroup hierarchical training dataset with more than 20 categories and three hierarchical levels was used to train the models. The experiments involved several variations of hyperparameters settings such as batch size, embedding size, and number of available examples from the training dataset, including two variation of CNN model text embedding such as static (stat) and random (rand). The results demonstrated that our proposed use of CNNs outperformed ﬂat CNN baseline model and both the ﬂat and hierarchical support vector machine (SVM) and logistic regression (LR) baseline models. In particular, hierarchical text classiﬁcation with CNN-stat models using local per parent node and local per level approaches achieved compelling results and outperformed the former and latter state-of-the-art models. However, using CNN with local per node approach for hierarchical text classiﬁcation underperformed and achieved worse results. Furthermore, we performed a detailed comparison between the proposed hierarchical local approaches with CNNs. The results indicated that the hierarchical local classiﬁcation per level approach using the CNN model with static text embedding achieved the best results, surpassing the ﬂat SVM and LR baseline models by 7 % and 13 %, surpassing the ﬂat CNN baseline by 5 %, and surpassing the h-SVM and h-LR models by 5 % and 10 %, respectively
Telepresence Robots as Embodied Agents in the Classroom

: Telepresence robots are emerging as a way for distant or homebound students to attend face-to-face classes, but their influence on the classroom environment is not yet well understood. This in-progress study explores the experiences of students in a face-to-face classroom where one student attended via telepresence robot. The focus of this study is the extent to which the robot is perceived as an embodied agent in a shared physical space. Telepresence robots are emerging as a way for distant or homebound students to attend face-to-face classes (Goodman, 2017). It is therefore important to understand how the use of these robots influences the classroom environment. This in-progress study explores the experiences of students in a face-to-face doctoral level course where one student attended class using a telepresence robot that allowed her to connect remotely but still maneuver through a shared physical space with her classmates.
Location, Location, Location: The Effects of Place in Place-Based Simulations

Educators who develop and use place-based curricula argue that engaging students in authentic problem-based learning situated in students’ own local place helps them understand the relevance of their academic work, which improves learning. However, while place-based curricula are localized, they are also authentic, problem-based experiences, which have been shown to be effective in their own right. Without controlling for the impact of authenticity, it is not clear whether localization itself improves student learning. In this study, we used a placebased simulation to engage students with authentic problem-based learning about a specific place: a city that is local for some students and not for others. We assessed differences in cognitive, affective, and behavioral outcomes between these two groups. Our results suggest that learning outcomes are better when students engage in a place-based simulation about their own locality, indicating that place does play a critical role in the success of place-based education.
The relationship between thermodynamic properties and local atomic structure of Al-TM (TM = Mn, Fe, Co, Ni, Cu) melts

ABSTRACT The relationship between structure and thermodynamic properties of Al- transition metal (TM) (TM = Mn, Fe, Co, Ni, Cu) melts had been studied by using the results of X-ray diffraction experiments, reverse Monte Carlo simulations and the model of ideal associated solution (MIAS). It was considered that local atomic structure of melts is determined by dense non-crystalline atomic packing and energy of interatomic interactions. This allowed to choose the types of associates for the MIAS. It is shown that the prominent role of the atomic packing factor in the Al-Mn, Al-Fe melts leads to correlation between the local atomic ordering of melts and the one of relevant polytetrahedral phases and defines a set of associates. Strengthening of heteroatomic interactions in the Al-Co, Al-Ni melts leads to an increase of the energy factor role in determining their structure and properties that reduces the number of associates from three for the Al-Mn melts to one for the Al-Ni.
Comparing the Effectiveness of Supports for Collaborative Dialogic Sense-Making with Agent-Based Models

: Collaborative dialogue has been classified by the ICAP framework (Chi & Wylie, 2014) as the highest interactive level of cognitive engagement. In this study we evaluate the balance between type of guidance and learner characteristics while collaborative learning with agent-based models takes place. Participants were students from health-care programs and were randomly assigned to one of two conditions: one group learned with agent-based models using the vicarious approach, where pairs viewed and discussed recordings of others using agent-based models; the other group explored agent-based models while discussing in pairs a set of text-based prompts. The results reveal that the vicarious-learning approach was superior to agent-based models’ exploration. More detailed evaluation shows that nursing students’ performance wasn’t affected by the type of guidance, while less experienced in the content, non-nursing students, benefited more from vicarious guidance. Findings suggest that dialoguing while observing the dialogue of others can maximize immediate learning gains.
Asynchronous Spiking Neural P Systems with Multiple Channels and Symbols

Spiking neural P systems (SNP systems, in short) are a class of distributed parallel computation systems, inspired from the way that the neurons process and communicate information by means of spikes. A new variant of SNP systems, which works in asynchronous mode, asynchronous spiking neural P systems with multiple channels and symbols (ASNP-MCS systems, in short), is investigated in this paper. There are two interesting features in ASNP-MCS systems: multiple channels and multiple symbols. That is, every neuron has more than one synaptic channels to connect its subsequent neurons, and every neuron can deal with more than one type of spikes. The variant works in asynchronous mode: in every step, each neuron can be free to ﬁre or not when its rules can be applied. The computational completeness of ASNP-MCS systems is investigated. It is proved that ASNP-MCS systems as number generating and accepting devices are Turing universal. Moreover, we obtain a small universal function computing device that is an ASNP-MCS system with 67 neurons. Specially, a new idea that can solve “block” problems is proposed in INPUT modules.
Facile one-step synthesis of Fe5(PO4)4(OH)3 · 2H2O hollow octahedra and their application for DNA separation

ABSTRACT A simple one-step process has been used to synthesize novel Fe5(PO4)4(OH)3 · 2H2O hollow octahedra in a mixed solvent of diethylene glycol (DEG) and H2O. The x-1ray diffraction (XRD) and scanning electron microscopy (SEM) have been provided for the characterizations of the nanostructures. The shape of the as-obtained products could be controlled by adjusting the volume ratio of DEG and H2O in the solvothermal process. The possible formation mechanism was proposed based2 on nucleation and the Ostwald ripening process as well as the soft-template function of DEG. In addition, the study herein demonstrated that the hollow octahedra exhibit excellent capability for the adsorption of salmon sperm DNA and would have great application potentials in DNA separation.
Optimization of antioxidant phenolic compounds extraction from Thomson orange peels and their incorporation in yogurt

1 Département de Biotechnologie, Institut de la Nutrition, de l'Alimentation et des Technologies Agro-Alimentaires (INATAA), Université Frères Mentouri-Constantine 1, 25000 Constantine, Algeria, 2 Laboratoire de Biochimie Appliquée, Faculté des Sciences de la Nature et de la Vie, Université de Bejaia, 06000 Bejaia, Algeria, 3 Laboratoire de Microbiologie Appliquée, Faculté des Sciences de la Nature et de la Vie, Université de Bejaia, 06000 Bejaia, Algeria,
KInetIcs Of quartZ sanD anD Its MIXtures DryIng By MIcrOwaVe raDIatIOn

l. I. solonenko1, orcid.org/0000-0003-2092-8044, s. I. repiakh2, orcid.org/0000-0003-0203-4135, K. I. uzlov2, orcid.org/0000-0003-0744-9890, I. Mamuzich3, orcid.org/0000-0002-7968-7540, t. V. Kimstach2, orcid.org/0000-0002-8993-201X, O. p. Bilyi2, orcid.org/0000-0003-1234-5404 1 – Odesa National Polytechnic University, Odesa, Ukraine 2 – National Metallurgical Academy of Ukraine, Dnipro, Ukraine, e­mail: 123rs@ua.fm 3 – University of Zagreb, Croatian metallurgical society, Za­ greb, the Republic of Croatia
Study of Soil Improvement and Slope Protection on the Double Track Engineering Design Between Giham- Martapura

The train is a means of transportation favored by the community because the train is one of the modes of transportation that has special characteristics and advantages. Along with the development of infrastructure development in Lampung Province and South Sumatra Province, the planning and design of a building must be done carefully and well, one of them is by building a double track between Giham - Martapura, South Sumatra because the application of one track has many obstacles. It is hoped that the addition of the double track can make the train schedule more accurate and can improve the quality of the trip. Therefore, for the construction of this double track railroad, one of them is needed a layer of soil that is able to support the load and can improve the physical and mechanical properties of the soil. Based on the results of the Atterberg boundary test the soil originating from the undisturbed soil sample of the Giham-Martapura railroad gets an PI value <LL-30 (26.51% <27.95%), then the land based on the AASHTO system is classified into A -7-5 that is clay soil and as subgrade material has normal to poor evaluation. Based on the calculation results, the peel depth (excavation) for the improvement of subgrade in STA 188 + 300 - STA 188 + 600 is as deep as 1.7 m, but after using additional reinforcement with geogrid material with strength specifications 19 Kpa / m2 the peel depth (excavation) to repair subgrade to 0.5 m. So that there is an excavation efficiency of 70.5%.
Intrusion Detection using Deep Learning Long Short-term Memory with Wrapper Feature Selection Method

Recently, many companies move to use cloud com-puting systems to enhance their performance and productivity. Using these cloud computing systems allows the execution of applications, data, and infrastructures on cloud platforms (i.e., online), which increase the number of attacks on such systems. As a resulting, building robust Intrusion detection systems (IDS) is needed. The main goal of IDS is to detect normal and abnormal network trafﬁc. In this paper, we propose a hybrid approach between an Enhanced Binary Genetic Algorithms (EBGA) as a wrapper feature selection (FS) algorithm and Long Short-Term Memory (LSTM). A novel injection method to prevent premature convergence of the GA is proposed in this paper. An intelligent k-means algorithm is employed to examine the solution distribution in the search space. Once 80% of the solutions belong to one cluster, an injection method (i.e., add new solutions) is used to redistribute the solutions over the search space. EBGA will reduce the search space as a preprocessing step, while LSTM works as a binary classiﬁcation method. UNSW-NB15, a real-world public dataset, is used in this work to evaluate the proposed system. The obtained results show the ability of feature selection method to enhance the overall performance of LSTM.
Determinants of Intergenerational Transmission of Poverty in Pakistan: A Case Study

a Assistant Professor, School of Economics, Bahauddin Zakariya University, Multan, Pakistan Email: furrukh@bzu.edu. pk b Chairman, School of Business and Economics, University of Management and Technology,Lahore, Pakistan Email: hafeez.rehman@umt.edu. pk c M.Phil. Scholar, School of Economics, Bahauddin Zakariya University, Multan, Pakistan d M.Phil. Scholar, School of Economics, Bahauddin Zakariya University, Multan, Pakistan
Development of Amoxicillin-Loaded Modified Polycaprolactone Microparticles in Medical Application

Amoxicillin is realized as significant drug due to their essential inhibition of bacterial infections. However, the effective time of amoxicillin in clinical position is less than 8 hours. Therefore, this research was to prolong the drug delivery system. Chitosan was modified by PCL (PCL/CS) microparticles were fabricated by oil in water emulsion (o/w emulsion) techniques for the protection and controlled the release of amoxicillin. The ratio of PCL: chitosan at different ratios were investigated for their influences on the zeta potential, size, morphology, swelling ratio and the release rate of amoxicillin from PCL/CS microparticles. The encapsulation efficiency was 74% to 83% and the maximum cumulative released amounts of amoxicillin from the PCL/CS at ratio 1:5 was about 6.5±0.03 mg for 7 days. Furthermore, the antimicrobial of amoxicillin was demonstrated by antimicrobial activity assays, which are effective in treating Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus). The PCL/CS was enough for the bacterial inhibition growth of E. coli and S. aureus. The PCL/CS could be appropriate to supply a model the drug delivery system for the medical application.
Learning Experiences of Students from Sindh and Balochistan About Online Learning during Covid-19 Pandemic Crisis

This research study explored the learning experiences of the students of government schools of Sindh province and private schools of Balochistan about online learning during Covid-19 pandemic crisis. Qualitative research methodology through a semi-structured online interview and focused group discussions was adopted for answering research questions.Through purposive sampling, sixteen students of federal public schools of Karachi and fifteen students from private schools of Balochistan were selected for interviews. Three focused group discussions were conducted among the participants from Karachi and two among the participants of Quetta. The qualitative raw data were transcribed, categorized and themes were generated. The findings of this study concluded that digital social media leaves deep impacts on the teaching and learning process of students. It is widely considered as a good initiative and appropriate alternative approach by saving and retaining the educational activities possibly from huge educational loss.Although these online classes have some limitations, they serve as a healthy and innovative approach reaching to students. Study recommends that the platforms of digital social media should be enhanced across the country both in rural and urban setting. Government should invest in technology based teaching and learning in order to train for such unfamiliar and sudden crisis.