Miracle-dz/UniFAR-FTUs huggingface dataset:
The MOOClet Framework: Unifying Experimentation, Dynamic Improvement, and Personalization in Online Courses

How can educational platforms be instrumented to accelerate the use of research to improve students' experiences? We show how modular components of any educational interface - e.g. explanations, homework problems, even emails - can be implemented using the novel MOOClet software architecture. Researchers and instructors can use these augmented MOOClet components for: (1) Iterative Cycles of Randomized Experiments that test alternative versions of course content; (2) Data-Driven Improvement using adaptive experiments that rapidly use data to give better versions of content to future students, on the order of days rather than months. A MOOClet supports both manual and automated improvement using reinforcement learning; (3) Personalization by delivering alternative versions as a function of data about a student's characteristics or subgroup, using both expert-authored rules and data mining algorithms. We provide an open-source web service for implementing MOOClets (www.mooclet.org) that has been used with thousands of students. The MOOClet framework provides an ecosystem that transforms online course components into collaborative micro-laboratories, where instructors, experimental researchers, and data mining/machine learning researchers can engage in perpetual cycles of experimentation, improvement, and personalization.
Experimental Design of Learning Analysis Dashboards for Teachers and Learners

Since learning in higher education is increasingly taking place online, the multiplication of web-based educational content, learning management systems (LMSs) and collaborative communication platforms have generated a large volume of data on learners and their learning activities. In recent years, interest has been growing in analyzing this data to support real-time decision making and improve the learning experience. This paper presents the results of a study conducted in higher education in Morocco, which evaluates a learning analysis dashboards (LADs) for both teachers and learners. The study shows that the dashboard, called TABAT, allowed a synthetic visualization of learning progress in courses and led to improved student engagement and success rates.
Design of 880MHz Dual Circular Polarization and 2.4GHz Circular Polarization Integrated Antenna

In this paper, a dual circularly polarized IFA antenna array and a circularly polarized microstrip antenna are introduced. The IFA array is composed of four designed Inverted-F shape antennas. The response frequency range of the IFA array is 840MHz-925MHz, which can be applied to RFID applications in UHF band. The two feeding ports correspond to two states of left-handed circular polarization and right-handed circular polarization respectively. The circularly polarized microstrip antenna is located in the middle of the antenna, and the response frequency range is 2.4-2.45ghz, which can be used to design multi-functional applications.
Classification of Discussions in MOOC Forums: An Incremental Modeling Approach

Supervised classification models are commonly used for classifying discussions in a MOOC forum. In most cases these models require a tedious process for manual labeling the forum messages as training data. So, new methods are needed to reduce the human effort necessary for the preparation of such training datasets. In this study we follow an incremental approach in order to examine how soon after the beginning of a new course, we have collected enough data for training a supervised classification model. We show that by employing features that derive from a seeded topic modeling method, we achieve classifiers with reliable performance early enough in the course life, thus reducing significantly the human effort. The content of the MOOC platform is used to bias the topic extraction towards discussions related to (a) course content, (b) logistics, or (c) social interactions. Then, we develop a supervised model at the start of each week based on the topic features of all previous weeks and evaluate its performance in classifying the discussions for the rest of the course. Our approach was implemented in three different MOOCs of different subjects and different sizes. The findings reveal that supervised models are able to perform reliably quite early in a MOOC's life and retain a steady overall accuracy across the remaining weeks, without requiring to be trained with the entire forum dataset.
One‐step selective affinity purification and immobilization of His‐tagged enzyme by recyclable magnetic nanoparticles

The NiFe2O4 magnetic nanoparticles (NF‐MNPs) were prepared for one‐step selective affinity purification and immobilization of His‐tagged recombinant glucose dehydrogenase (GluDH). The prepared nanoparticles were characterized by a Fourier‐transform infrared spectrophotometer and microscopy. The immobilization and purification of His‐tagged GluDH on NF‐MNPs were investigated. The optimal immobilization conditions were obtained that mixed cell lysis and carriers in a ratio of 0.13 in pH 8.0 Tris‐HCl buffer at 30℃ and incubated for 2 h. The highest activity recovery and protein bindings were 71.39% and 38.50 μg mg–1 support, respectively. The immobilized GluDH exhibited high thermostability, pH‐stability and it can retain more than 65% of the initial enzyme after 10 cycles for the conversion of glucose to gluconolactone. Comparing with a commercial Ni‐NTA resin, the NF‐MNPs displayed a higher specific affinity with His‐tagged recombinant GluDH.
Growth of silicon-doped Al0.6Ga0.4N with low carbon concentration at high growth rate using high-flow-rate metal organic vapor phase epitaxy reactor

The relationship between the carbon concentration and electrical characteristics of silicon-doped AlGaN (Al > 0.5) was investigated using a high-flow-rate metal organic vapor phase epitaxy (MOVPE) reactor. The carbon concentration and electrical properties of AlGaN (Al > 0.5) were measured as a function of the growth rate, V/III ratio, and growth temperature. The growth rate of Al0.6Ga0. 4N was linearly controlled up to 7.2 µm/h under a constant ammonia (NH3) flow rate. However, a decrease in V/III ratio resulted in an increase in carbon concentration to 8 × 1017 cm−3. With increased growth temperature, the carbon concentration decreased to less than 2 × 1017 cm−3 without showing any reduction in growth rate. As a result, n-type Al0.6Ga0. 4N with a carrier concentration of 5.4 × 1018 cm−3 and a resistivity of 2.2 × 10−2 Ω·cm was obtained.
Screening of Botanical Drugs against SARS-CoV-2 Entry Reveals Novel Therapeutic Agents to Treat COVID-19

An escalating pandemic caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is impacting global health. Specific treatment options for diseases caused by SARS-CoV-2 are largely lacking. Herein, we used a pseudotype virus (pv) bearing the SARS-CoV-2 S glycoprotein to screen a botanical drug library to identify an agent against SARS-CoV-2 entry. All the four hits, including angeloylgomisin O, schisandrin B, procyanidin, and oleanonic acid, were identified for effective inhibition of SARS-CoV-2 S pv entry in the micromolar range. A mechanistic study revealed that these four agents inhibit SARS-CoV-2 S pv entry by blocking S-mediated membrane fusion. Furthermore, angeloylgomisin O, schisandrin B, and oleanonic acid inhibited authentic SARS-CoV-2 with a high selective index (SI). We also showed that all the four hits could also inhibit the entry of pv of Middle East respiratory syndrome coronavirus (MERS-CoV) and newly emerged SARS-CoV-2 variants (D614G, K417N/E484K/N501Y/D614G). In drug combination studies performed in cellular antiviral assays, angeloylgomisin O and schisandrin B displayed synergistic effects in combination with remdesivir. These results indicated that angeloylgomisin O, schisandrin B, procyanidin, and oleanonic acid can inhibit SARS-CoV-2 and that they are potential therapeutic agents for COVID-19.
Elicitation of Neutralizing Antibody Responses to HIV-1 Immunization with Nanoparticle Vaccine Platforms

A leading strategy for developing a prophylactic HIV-1 vaccine is the elicitation of antibodies that can neutralize a large fraction of circulating HIV-1 variants. However, a major challenge that has limited the effectiveness of current vaccine candidates is the extensive global diversity of HIV-1 Env, the sole target for HIV-neutralizing antibodies. To address this challenge, a variety of strategies to incorporate Env diversity into the vaccine formulation have been proposed. Here, we assessed the potential of two such strategies that utilize a nanoparticle-based vaccine platform to elicit broadly neutralizing antibody responses. The nanoparticle immunogens developed here consisted of different formulations of Envs from strains BG505 (clade A) and CZA97 (clade C), attached to the N-termini of bacterial ferritin. Single-antigen nanoparticle cocktails as well as mosaic nanoparticles bearing both Env trimers elicited high antibody titers in mice and guinea pigs. Furthermore, serum from guinea pigs immunized with nanoparticle immunogens achieved autologous, and in some cases heterologous, tier 2 neutralization, although significant differences between mosaic and single-antigen nanoparticles were not observed. These results provide insights into the ability of different vaccine strategies for incorporating Env sequence diversity to elicit neutralizing antibodies, with implications for the development of broadly protective HIV-1 vaccines.
Control over sampling boosts numerical evidence processing in human decisions from experience

When acquiring information about choice alternatives, decision makers may have varying levels of control over which and how much information they sample before making a choice. How does control over sampling affect the quality of experience-based decisions? Here, combining variants of a numerical sampling task with neural recordings, we show that control over when to stop sampling can enhance (i) behavioral choice accuracy, (ii) the build-up of parietal decision signals, and (iii) the encoding of numerical sample information in multivariate electroencephalogram (EEG) patterns. None of these effects were observed when participants could only control which alternatives to sample, but not when to stop sampling. Furthermore, levels of control had no effect on early sensory signals or on the extent to which sample information leaked from memory. The results indicate that freedom to stop sampling can amplify decisional evidence processing from the outset of information acquisition and lead to more accurate choices.
A Branching Process Model of Evolutionary Rescue

Evolutionary rescue is the process whereby a declining population may start growing again, thus avoiding extinction, via an increase in the frequency of fitter genotypes. These genotypes may either already be present in the population in small numbers, or arise by mutation as the population declines. We present a simple two-type discrete-time branching process model and use it to obtain results such as the probability of rescue, the shape of the population growth curve of a rescued population, and the time until the first rescuing mutation occurs. Comparisons are made to existing results in the literature in cases where both the mutation rate and the selective advantage of the beneficial mutations are small.
Genetic diversity of honeybee colonies predicts gut bacterial diversity of individual colony members

Summary The gut microbiota of social bees is relatively simple and dominated by a set of core taxa found consistently in individuals around the world. Yet, variation remains and can affect host health. We characterized individual‐ and regional‐scale variation in honeybee (Apis mellifera) gut microbiota from 64 colonies in North‐West England by sequencing the V4 region of the 16S rRNA gene and asked whether microbiota were influenced by host genotype and landscape composition. We also characterized the genotypes of individual bees and the land cover surrounding each colony. The literature‐defined core taxa dominated across the region despite the varied environments. However, there was variation in the relative abundance of core taxa, and colony membership explained much of this variation. Individuals from more genetically diverse colonies had more diverse microbiotas, but individual genetic diversity did not influence gut microbial diversity. There were weak trends for colonies in more similar landscapes to have more similar microbiota, and for bees from more urban landscapes to have less diverse microbiota. To our knowledge, this is the first report for any species that the gut bacterial communities of individuals are influenced by the genotypes of others in the population.
Biallelic loss-of-function OBSCN variants predispose individuals to severe, recurrent rhabdomyolysis

Rhabdomyolysis is the acute breakdown of skeletal myofibres in response to an initiating factor, most commonly toxins and over exertion. A variety of genetic disorders predispose to rhabdomyolysis through different pathogenic mechanisms, particularly in patients with recurrent episodes. However, the majority of cases remain without a genetic diagnosis. Here we present six patients who presented with severe and recurrent rhabdomyolysis, usually with onset in the teenage years; other features included a history of myalgia and muscle cramps. We identified ten bi-allelic loss-of-function variants in the gene encoding obscurin (OBSCN) co-segregating with disease. We show reduced expression of OBSCN and loss of obscurin protein in patient muscle. Obscurin is proposed to be involved in SR function and Ca2+ handling. Patient cultured myoblasts appear more susceptible to starvation as evidenced by a greater decreased in SR Ca2+ content compared to control myoblasts. This likely reflects a lower efficiency when pumping Ca2+ back into the SR and/or a decrease in Ca2+ SR storage ability when metabolism is diminished. OSBCN variants have previously been associated with cardiomyopathies. None of the patients presented with a cardiomyopathy and cardiac examinations were normal in all cases in which cardiac function was assessed. There was also no history of cardiomyopathy in first degree relatives, in particular in any of the carrier parents. This cohort is relatively young, thus follow-up studies and the identification of additional cases with bi-allelic null OBSCN variants will further delineate OBSCN-related disease and the clinical course of disease.
Human single-chain antibodies neutralize SARS-CoV-2 variants by engaging an essential epitope of the spike: a new weapon against COVID-19

As of June 2021, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remains a global emergency and effective therapeutic interventions for the treatment and prevention of coronavirus disease 2019 (COVID-19) are urgently needed. SARS-CoV-2-neutralizing monoclonal antibodies (mAbs) represent a promising approach to COVID-19 therapy. However, the recently described accumulating mutations in the SARS-CoV-2 spike protein are challenging the efficacy of approved and investigational mAbs, whose widespread use is also hampered by their significant costs and possible side effects, including Antibody-Dependent Enhancement (ADE). Here we describe a cluster of SARS-CoV-2 neutralizing human single chain variable fragment antibodies, identified by phage display, sharing a common VH CDR3 sequence. Phage libraries were built by amplifying variable domains of immunoglobulin genes from cDNA derived from lymphocytes of COVID-19 convalescent subjects living in Bergamo, Italy. The scFv76-cluster antibodies (scFv76-cl Abs) exhibit high affinity for the spike receptor binding domain (RBD) of Wuhan strain and emerging variants, leading to inhibition of RBD/human ACE2 interaction. The antigenic epitope recognized by scFv76 was mapped in the receptor binding motif (RBM) of RBD at residues L455, F456, Y473, N487 and Y489. None of these residues has been to date listed among the RBD mutations of SARS-CoV-2 variants of concern (VOCs), suggesting an important role of such epitope in viral infectivity. Treatment with scFv76-cl Abs is effective against SARS-CoV-2, as determined by in vitro experiments of viral infection, replication, cytopathogenicity and spike-mediated syncytia formation. Moreover, their intranasal administration is shown to counteract infection in two independent animal models. Overall, the biochemical and biological characteristics of scFv76-cl Abs are compatible with their clinical use for COVID-19 therapy by intranasal or aerosol administration. To our knowledge, this is the first example of promising human anti-SARS-CoV-2 scFv antibodies as drug candidates for COVID-19 therapy.
Clinical Outcome in Patients With Intracerebral Hemorrhage Stratified by Type of Antithrombotic Therapy

Background: Antithrombotic therapy influences clinical outcome after spontaneous intracerebral hemorrhage (ICH). However, evidence on the effect of different antithrombotic therapies on outcome and a comparison between different therapies is scarce, while this is important for medical decision making. Therefore, we investigated clinical outcome after ICH stratified by type of antithrombotic therapy. Patients/Methods: We performed a cohort study selecting consecutive ICH patients from our database, excluding patients without data on medication or therapeutic heparin use. Primary outcome was poor outcome (modified Rankin Scale ≥ 4) after 90 days. Secondary outcome was mortality at 90 days. We analyzed outcome and survival in patients with ICH using vitamin K antagonists (VKA), antiplatelet therapy (AP), and direct oral anticoagulant (DOAC) compared to no antithrombotic therapy adjusted for age, National Institutes of Health Stroke Scale (NIHSS), infratentorial localization, intraventricular extension, history of hypertension, diabetes, or stroke, and interaction between age and NIHSS. Results: We included 916 patients (223 AP, 161 VKA, and 40 DOAC). VKA (adjusted odds ratio [aOR] 3.2, 95% confidence interval [CI], 1.6–6.3) and AP (aOR = 2.0, 95%CI: 1.1–3.7) were associated with poor outcome. DOAC use did not reach statistical significance (aOR = 2.4, 95%CI: 0.8–7.7). Patients who used any antithrombotic therapy had poorer survival compared to patients without antithrombotic treatment and patients using AP and DOAC had better survival compared to VKA after adjustment. Conclusions: Patients with antithrombotic therapy have worse clinical outcome after ICH. Patients using VKA have higher risk of poor outcome and mortality compared to patients using AP. These findings highlight the deleterious effect of antithrombotic therapy in patients with ICH and stress the need for effective therapies for ICH patients.
Gender Differences in Anxiety, Depression, and Nursing Needs Among Isolated Coronavirus Disease 2019 Patients

Objective This study explored gender differences in anxiety, depression, and nursing needs among isolated Coronavirus Disease 2019 (COVID-19) patients, with a particular focus on the influencing factors. The main goal was to elucidate breakthrough points and intervention targets for psychological counseling aimed at the promotion of overall health during isolation treatment. Methods A survey was conducted to obtain information about the nursing needs of COVID-19 patients, with mental health assessed via the Hospital Anxiety and Depression Scale (HADS). Participants included 219 isolated COVID-19 patients at a Wuhan module hospital in Hubei province, China. Results A total of 216 valid questionnaires were collected (98.63% retrieval rate). Of these participants, 21.76% had anxiety symptoms, while 17.59% had depression symptoms. Colleagues infected with COVID-19 (OR = 3.896, 95%CI: 1.555–9.764, P = 0.004) were the main influencing factors for anxiety symptoms, while marital status (OR = 2.700, 95% CI: 1.033–7.055, P = 0.043) and family members infected with COVID-19 (OR = 2.969, 95% CI: 1.243–7.095, P = 0.014) were the main influencing factors for depression symptoms. As for gender, male patients were generally more prone to depression and anxiety than female patients, especially those who were infected with colleagues. On the other hand, female patients reported greater concerns about safe treatment environments and communication with medical staff. Conclusion This study found gender-based differences regarding the factors influencing anxiety and depression in isolated COVID-19 patients, with males reporting a greater general tendency for symptoms. On the other hand, female patients reported greater overall psychological nursing needs than males. Targeted nursing should thus be implemented to address specific psychological characteristics and nursing needs.
Enrichment of Autotrophic Denitrifiers From Anaerobic Sludge Using Sulfurous Electron Donors

This study compared the rates and microbial community development in batch bioassays on autotrophic denitrification using elemental sulfur (S0), pyrite (FeS2), thiosulfate (S2O32–), and sulfide (S2–) as electron donor. The performance of two inocula was compared: digested sludge (DS) from a wastewater treatment plant of a dairy industry and anaerobic granular sludge (GS) from a UASB reactor treating dairy wastewater. All electron donors supported the development of a microbial community with predominance of autotrophic denitrifiers during the enrichments, except for sulfide. For the first time, pyrite revealed to be a suitable substrate for the growth of autotrophic denitrifiers developing a microbial community with predominance of the genera Thiobacillus, Thioprofundum, and Ignavibacterium. Thiosulfate gave the highest denitrification rates removing 10.94 mM NO3– day–1 and 8.98 mM NO3– day–1 by DS and GS, respectively. This was 1.5 and 6 times faster than elemental sulfur and pyrite, respectively. Despite the highest denitrification rates observed in thiosulfate-fed enrichments, an evaluation of the most relevant parameters for a technological application revealed elemental sulfur as the best electron donor for autotrophic denitrification with a total cost of 0.38 € per m3 of wastewater treated. Graphical Abstract