Miracle-dz/UniFAR-FTUs huggingface dataset:
Application of Collaborative Learning Paradigms within Software Engineering Education: A Systematic Mapping Study

Collaboration is used in Software Engineering (SE) to develop software. Industry seeks SE graduates with collaboration skills to contribute to productive software development. SE educators can use Collaborative Learning (CL) to help students develop collaboration skills. This paper uses a Systematic Mapping Study (SMS) to examine the application of the CL educational theory in SE Education. The SMS identified 14 papers published between 2011 and 2022. We used qualitative analysis to classify the papers into four CL paradigms: Conditions, Effect, Interactions, and Computer-Supported Collaborative Learning (CSCL). We found a high interest in CSCL, with a shift in student interaction research to computer-mediated technologies. We discussed the 14 papers in depth, describing their goals and further analysing the CSCL research. Almost half the papers did not achieve the appropriate level of supporting evidence; however, calibrating the instruments presented could strengthen findings and support multiple CL paradigms, especially opportunities to learn at the social and community levels, where research was lacking. Though our results demonstrate limited CL educational theory applied in SE Education, we discuss future work to layer the theory on existing study designs for more effective teaching strategies.
From Generative AI to Generative Internet of Things: Fundamentals, Framework, and Outlooks

Generative Artificial Intelligence (GAI) possesses the capabilities of generating realistic data and facilitating advanced decision-making. By integrating GAI into modern Internet of Things (IoT), Generative Internet of Things (GIoT) is emerging and holds immense potential to revolutionize various aspects of society, enabling more efficient and intelligent IoT applications, such as smart surveillance and voice assistants. In this article, we present the concept of GIoT and conduct an exploration of its potential prospects. Specifically, we first overview four GAI techniques and investigate promising GIoT applications. Then, we elaborate on the main challenges in enabling GIoT and propose a general GAI-based secure incentive mechanism framework to address them, in which we adopt Generative Diffusion Models (GDMs) for incentive mechanism designs and apply blockchain technologies for secure GIoT management. Moreover, we conduct a case study on modern Internet of Vehicle traffic monitoring, which utilizes GDMs to generate effective contracts for incentivizing users to contribute sensing data with high quality. Finally, we suggest several open directions worth investigating for the future popularity of GIoT.
Incorporating nonparametric methods for estimating causal excursion effects in mobile health with zero-inflated count outcomes

In mobile health, tailoring interventions for real-time delivery is of paramount importance. Micro-randomized trials have emerged as the"gold-standard"methodology for developing such interventions. Analyzing data from these trials provides insights into the efficacy of interventions and the potential moderation by specific covariates. The"causal excursion effect", a novel class of causal estimand, addresses these inquiries. Yet, existing research mainly focuses on continuous or binary data, leaving count data largely unexplored. The current work is motivated by the Drink Less micro-randomized trial from the UK, which focuses on a zero-inflated proximal outcome, i.e., the number of screen views in the subsequent hour following the intervention decision point. To be specific, we revisit the concept of causal excursion effect, specifically for zero-inflated count outcomes, and introduce novel estimation approaches that incorporate nonparametric techniques. Bidirectional asymptotics are established for the proposed estimators. Simulation studies are conducted to evaluate the performance of the proposed methods. As an illustration, we also implement these methods to the Drink Less trial data.
Cobordism Obstructions to Complex Sections

A notion of vector field cobordism for oriented manifolds was defined by Bokstedt and Svane. We extend this notion to define complex section cobordism for almost complex manifolds. We then determine the complex section cobordism groups and a relevant cobordism category. We describe an obstruction which tells us when a cobordism class contains a manifold, which can be equipped with $r$ linearly independent complex sections, in terms of the Chern classes. Finally, we show that this obstruction vanishes for certain multiplicative generators in the complex cobordism ring.
Improving Compositional Generalization Using Iterated Learning and Simplicial Embeddings

Compositional generalization, the ability of an agent to generalize to unseen combinations of latent factors, is easy for humans but hard for deep neural networks. A line of research in cognitive science has hypothesized a process, ``iterated learning,'' to help explain how human language developed this ability; the theory rests on simultaneous pressures towards compressibility (when an ignorant agent learns from an informed one) and expressivity (when it uses the representation for downstream tasks). Inspired by this process, we propose to improve the compositional generalization of deep networks by using iterated learning on models with simplicial embeddings, which can approximately discretize representations. This approach is further motivated by an analysis of compositionality based on Kolmogorov complexity. We show that this combination of changes improves compositional generalization over other approaches, demonstrating these improvements both on vision tasks with well-understood latent factors and on real molecular graph prediction tasks where the latent structure is unknown.
Diet and food assimilation of the Plata pompano Trachinotus marginatus Cuvier, 1832 in a subtropical sandy beach inferred by stomach content and stable isotope analyzes

Abstract Investigating trophic linkages sustaining consumers is crucial to understanding their functional ecological role in communities and ecosystems. In this work, we combined stomach content (SCA) and stable isotope (SIA) analyses to investigate the trophic ecology of the Plata pompano Trachinotus marginatus during a critical phase of its life cycle along a subtropical sandy beach. This species is a conspicuous component of the southwestern Atlantic coast and commonly targeted by coastal fisheries. The diet was described using SCA, whereas the relative importance of food sources sustaining juveniles, as well their food niche structure and trophic position (TP), were evaluated using SIA. Juveniles consumed mainly crustaceans like the hippid crab Emerita brasiliensis, although other invertebrates (annelids, insects, molluscs) and fishes (including cannibalism) were also recorded. Although microcrustaceans dominated the diet, SIA showed that more palatable preys without carapaces or shells, like fishes and annelids, were the most assimilated preys in the muscle tissue of juvenile T. marginatus. There were marked changes in their isotopic niches (SEAc) and TP across ontogeny. SEAc ranged from 1.41‰2 for smaller individuals (0–40 TL mm) to 0.3‰2 for larger individuals (>80 TL mm). TP ranged from 3.1 (95% CI 2.7–3.6) for smaller to 4.5 (95% CI 3.9–5.1) for larger individuals. SIA suggest that juvenile T. marginatus derived most of their primary nutrients from a planktonic food web and, to a lesser extent, from a benthic pathway. Future studies are needed to better understand its functional role in food web of surf-zone ecosystems.
New Scheloribates (Topobates) (Acari, Oribatida, Scheloribatidae) from Mexico

Abstract The subgenus Scheloribates (Topobates) (Oribatida, Scheloribatidae) is recorded in Mexico for the first time. Two new species of the subgenus—S. (T.) moskovchenkoi sp. nov. and S. (T.) paramoskovchenkoi sp. nov.—are described, based on adults collected from leaf litter from the karst pits in the secondary semi-evergreen tropical forest. Scheloribates (T.) moskovchenkoi is similar to S. (T.) tibetensis in the presence of heterotridactylous legs and long bothridial seta with elongate, lanceolate head having setiform apex, but it differs from the latter by the number of notogastral setae, the different length of notogastral setae, in having sparse small foveolae in dorsoanterior and dorsocentral parts of notogaster, the position of saccule Sa, the presence of tubercle-like process on the trochanter IV, and the absence of translamella. Scheloribates (T.) paramoskovchenkoi is similar to S. (T.) moskovchenkoi in the presence of bothridial seta with elongate, lanceolate head having setiform apex and 13 pairs of notogastral setae, but it differs from the latter in having monodactylous legs and five pairs of notogastral sacculi, strongly reduced pteromorph, the presence of tooth-like process on the trochanter IV, the presence of two longitudinal dorsodistal carinae and concavity between them on the leg tarsi I, II, and in the absence of foveolae on the notogaster and ventrobasal tooth on the leg tibiae I, II.
Interferon-tau (IFN-τ) Has Antiproliferative Effects, Induces Apoptosis, and Inhibits Tumor Growth in a Triple-negative Breast Cancer Murine Tumor Model

Background/Aim: Resistant triple-negative breast cancer (TNBC) is a subtype of this disease that is resistant to conventional chemotherapy agents. IFN-τ is a cytokine that has recently been shown to have immunoregulatory and antitumor effects. The present study aimed to examine the antiproliferative and apoptosis effects of IFN-τ in breast cancer cells and the antitumor effect in a murine tumor model of TNBC. Materials and Methods: Murine breast cancer 4T1 cells were cultured and treated with ovine IFN-τ and through MTT and Caspase-Glo 3/7 assays, viability and cell death were determined. In addition, the antitumor effect of IFN-τ was determined in a murine tumor model of TNBC. Results: Ovine IFN-τ showed a concentration-dependent antiproliferative effect on 4T1 murine breast cancer cells. Also, treatment of 4T1 cells with IFN-τ induced the activation of caspase 3 and 7, which is indicative of apoptotic cell death. Moreover, we detected an increase in the expression of type I interferon receptor (IFNAR1/2) in cells treated with IFN-. The intratumoral application of IFN-τ in mice inhibited tumor growth compared to the control non-treated group, and the effect was associated with the increased expression of GM-CSF. Conclusion: Ovine IFN-τ may be an effective immunotherapeutic cytokine for the treatment of TNBC.
Transition from arc to oceanic magmatism at the Kamchatka-Aleutian junction

Spatial geochemical variations of Quaternary lavas erupted along the northern segment of the Kamchatka arc are used to trace changes in magma generation across the subducting Pacific slab edge. The late Pleistocene–Holocene lavas of the northern end of the Central Kamchatka depression north of the Pacific slab edge show strong enrichment in high field strength elements and light rare earth elements, relatively unradiogenic strontium and lead but radiogenic neodymium isotope ratios, and oxygen isotope compositions similar to those of mid-oceanic-ridge basalts. These geochemical characteristics are distinct from the southern Central Kamchatka depression volcanoes located above the subducting Pacific slab. Extensive fluid-triggered mantle melting dominates magma genesis beneath the largest Kamchatka volcanoes in the south, whereas low-degree decompression melting of the Pacific asthenospheric mantle is the major magma generation process north of the Pacific slab edge. Quaternary detachment of the subducted Pacific plate fragment resulted in the influx of fertile mantle beneath Kamchatka. We propose that upwelling and southward flow of this hotter, more fertile mantle is the main reason for recent magmatism in northern Kamchatka and for the exceptional productivity of the Central Kamchatka depression volcanoes (Klyuchevskoy and Sheveluch), the most active arc volcanoes on Earth.
The Associations of Maternal Blood Hemoglobin and Serum Triglyceride Levels and the Risk of Preterm Delivery

Abstract The abnormal hemoglobin (HGB) and serum lipid concentrations during pregnancy will increase the risk of preterm delivery. Our study aimed to explore the correlation between prenatal HGB and serum lipid levels and preterm delivery. We enrolled 215 mother-infant pairs in a pilot cohort study. The logistic regression model and Restricted Cubic Spline model (RCS) were used to investigate the levels of prenatal blood HGB and serum lipid such as triglyceride (TG), total cholesterol, high-density lipoprotein, low density lipoprotein and preterm delivery. The results showed that moderate levels of prenatal blood HGB (OR=0.28; 95%CI: 0.10, 0.75, p-trend=0.018) and high level of serum TG (OR=0.29; 95%CI: 0.10, 0.84, p-trend=0.022) level were negatively associated with the risk of preterm delivery. The joint effect results showed that compared with lower level of prenatal blood HGB (≤123.13 g/l) and TG (≤3.7 mmol/l), we found that high levels prenatal blood HGB and serum TG (OR=0.32, 95%CI: 0.12, 0.89) had a negative association with the risk of preterm delivery. Moreover, prenatal blood HGB and serum TG levels had negative linear dose-effect relationships with the risk of preterm delivery in overall and girl group (p<0.05). Moderate levels of prenatal blood HGB and high level of serum TG were negatively associated with the risk of preterm delivery. The joint effect of high levels prenatal HGB and prenatal serum TG in the normal range were negatively correlated with preterm delivery. Moreover, the underlying mechanisms should be clarified in future studies.
Pre-treatment Tumor Size and Tumor Growth Rate as Prognostic Predictors for Patients With Recurrent/Metastatic Squamous Cell Carcinoma of the Head and Neck Treated With Nivolumab

Background/Aim: The prognosis of recurrent/metastatic squamous cell carcinoma of the head and neck (R/M SCCHN) is poor, although immune checkpoint inhibitors (ICIs), such as nivolumab, have been shown to prolong survival. We investigated the factors that predict the efficacy of nivolumab when selecting an appropriate treatment strategy for patients with R/M SCCHN. Patients and Methods: Forty-four Japanese patients with R/M SCCHN treated with nivolumab between May 2017 and October 2021 were analyzed. The primary endpoint of the study was overall survival (OS). We defined pre-treatment tumor size (PTS) as the sum of the size of all measurable lesions, and tumor growth rate (TGR) as the total growth rate of the largest tumor diameter on CT scans taken to determine treatment response, divided by the interval between CT scans. Receiver operating characteristic (ROC) curves were used to identify the cutoff points of PTS and TGR for OS. Cox proportional hazards regression analysis was performed to examine the relationships between various factors, including patient characteristics, PTS, and TGR, as well as treatment outcomes. Results: In multivariate analysis, Eastern Cooperative Oncology Group (ECOG) performance status (PS) score ≥1, progressive disease (PD) as best overall response (BOR), and TGR >0.60%/day were independent risk factors for poor OS in patients with R/M-SCCHN. Conclusion: Higher TGR, poor PS, and PD as BOR may be prognostic factors in patients with R/M SCCHN.
Stratospheric influences on the tropospheric seasonal cycles of nitrous oxide and chlorofluorocarbons

The stratospheric influence on the tropospheric seasonal cycles of N2O, CFC‐11 (CCl3F), CFC‐12 (CCl2F2) and CFC‐113 (CCl2FCClF2) is investigated using observations from the AGAGE global trace gas monitoring network and the results of the Whole Atmosphere Community Climate Model (WACCM). WACCM provides the basis for a number of predictions about the relative amplitudes of N2O and CFC seasonal cycles and about the relative magnitude and phasing of seasonal cycles in the northern and southern hemispheres. These predictions are generally consistent with observations, suggesting that the stratosphere exerts a coherent influence on the tropospheric seasonal cycles of trace gases whose primary sinks are in the stratosphere. This stratospheric influence may complicate efforts to validate estimated source distributions of N2O, an important greenhouse gas, in atmospheric transport model studies.
Immigrants in the Heartland: Columbus as a New Settlement Destination City for Brazilians

KLIMPEL, JILL M. , M.A., June 2009, Latin American Studies Immigrants in the Heartland: Columbus as a New Settlement Destination City for Brazilians (134 pp.) Director of Thesis: Brad D. Jokisch Immigrant communities have been developing in a diverse array of new settlement destinations across the US. This research focuses on a group of Brazilian immigrants in Columbus, to better understand the city as a settlement destination, as well as the changing profile of the Brazilian immigrant community. Using a semiethnographic approach that uses qualitative methods, this research presents several new findings. First, it portrays a diverse community of Brazilian immigrants, including Brazilians from Rondonia. Second, it offers insight on Brazilians and their manner to self-identify, as well as the importance of their feelings of fear. Third, it highlights the importance of the internet as a vital space for immigrant communities. Finally, it supports findings on the importance of the five new settlement destination factors. Approved: _____________________________________________________________ Brad D. Jokisch Associate Professor of Geography
Repeated methamphetamine exposure decreases plasma brain-derived neurotrophic factor levels in rhesus monkeys

Background Brain-derived neurotrophic factor (BDNF) is known to prevent methamphetamine (METH)-induced neurotoxicity and plays a role in various stages of METH addiction. However, there is a lack of research with longitudinal design on changes in plasma BDNF levels in active METH-dependent individuals. Aims The aim of the study was to investigate changes in BDNF levels during METH self-administration in monkeys. Methods This study measured plasma BDNF levels in three male rhesus monkeys with continuous METH exposure and four male control rhesus monkeys without METH exposure. Changes in plasma BDNF levels were then assessed longitudinally during 40 sessions of METH self-administration in the three monkeys. Results Repeated METH exposure decreased plasma BDNF levels. Additionally, plasma BDNF decreased with long-term rather than short-term accumulation of METH during METH self-administration. Conclusions These findings may indicate that the changes in peripheral BDNF may reflect the quantity of accumulative METH intake during a frequent drug use period.
Foundation Models Meet Imbalanced Single-Cell Data When Learning Cell Type Annotations

With the emergence of single-cell foundation models, an important question arises: how do these models perform when trained on datasets having an imbalance in cell type distribution due to rare cell types or biased sampling? We benchmark three foundation models, scGPT, scBERT, and Geneformer, using skewed single-cell cell-type distribution for cell-type annotation. While all models had reduced performance when challenged with rare cell types, scGPT and scBERT, performed better than Geneformer. Notably, in contrast to scGPT and scBERT, Geneformer uses ordinal positions of the tokenized genes rather than actual raw gene expression values. To mitigate the effect of a skewed distribution, we find that random oversampling, but not random undersampling, improved the performance for all three foundation models. Finally, scGPT, using FlashAttention, has the fastest computational speed, whereas scBERT is more memory-efficient. We conclude that tokenization and data representation are essential areas of research, and new strategies are needed to mitigate the effects of imbalanced learning in single-cell foundation models. Code and data for reproducibility are available at https://github.com/SabbaghCodes/ImbalancedLearningForSingleCellFoundationModels.
KIF1C activates and extends dynein movement through the FHF cargo adaptor

Cellular cargos move bidirectionally on microtubules due to the presence of opposite polarity motors dynein and kinesin. Many studies show these motors are co-dependent, whereby one requires the activity of the other, although the mechanism is unknown. Here, using in vitro motility assays, we show that the kinesin-3 KIF1C acts both as an activator and a processivity factor for dynein. Activation only requires a fragment of the non-motor tail of KIF1C (KIF1C-stalk) to bind the cargo adaptor HOOK3. Cryo-EM, crosslinking mass spectrometry and AlphaFold2 predictions reveal this binding site to be separate from that of two constitutive factors (FTS and FHIP), which link HOOK3 to small G-proteins on cargos. We provide a structural model for how the FTS-HOOK3-FHIP1B (FHF) complex is auto-inhibited and explain how the KIF1C-stalk relieves this inhibition. Collectively, our work provides a molecular explanation for co-dependency by revealing that the mutual activation of dynein and kinesin is mediated through their shared adaptor. Many adaptors bind both dynein and kinesins, suggesting this mechanism could be generalised to other bidirectional complexes.
Lifecycle of a predatory bacterium vampirizing its prey through the cell envelope and S-layer

Predatory bacteria feed upon and kill other bacteria in various natural environments. Obligate epibiotic predators like Bdellovibrio exovorus consume their prey whilst remaining attached to the outside of the prey. How these predators achieve epibiotic feeding through the prey cell envelope has not been explored previously. Whereas the S-layer is the only proposed defensive structure against predatory bacteria, it remains unclear how this thin outer layer of the envelope might prevent epibiotic attacks. Similarly, the lifecycle of B. exovorus during the predator-prey interaction is poorly understood, with current models suggesting a binary division. Here we imaged the entire predatory lifecycle of B. exovorus and the fate of its Caulobacter crescentus prey by time-lapse microscopy and cryo-electron microscopy to monitor predator attack, growth and division and assess the impact of the S-layer on epibiotic predation. Our data reveal that B. exovorus uses non-binary division in a novel proliferation pattern that mainly generates three progenies. Moreover, we found that B. exovorus predates regardless of the presence of an S-layer, calling for revisiting its protective role against predators. Finally, our results indicate that epibiotic predation relies on the establishment of a secured junction between the prey and predator outer membranes, which must be resolved unilaterally to maintain cellular integrity of the predator departing from the prey surface.
Using deep-learning to obtain calibrated individual disease and ADL damage transition probabilities between successive ELSA waves

We predictively model damage transition probabilities for binary health outputs of 19 diseases and 25 activities of daily living states (ADLs) between successive waves of the English Longitudinal Study of Aging (ELSA). Model selection between deep neural networks (DNN), random forests, and logistic regression found that a simple one-hidden layer 128-node DNN was best able to predict future health states (AUC ≥ 0.91) and average damage probabilities (R2 ≥ 0.92). Feature selection from 134 explanatory variables found that 33 variables are sufficient to predict all disease and ADL states well. Deciles of predicted damage transition probabilities were well calibrated, but correlations between predicted health states were stronger than observed. The hazard ratios (HRs) between high-risk deciles and the average were between 3 and 10; high prevalence damage transitions typically had smaller HRs. Model predictions were good across all individual ages. A simple one-hidden layer DNN predicts multiple binary diseases and ADLs with well calibrated damage and repair transition probabilities.