Miracle-dz/UniFAR-FTUs huggingface dataset:
Dual-Task Learning for Multi-Behavior Sequential Recommendation

Recently, sequential recommendation has become a research hotspot while multi-behavior sequential recommendation (MBSR) that exploits users' heterogeneous interactions in sequences has received relatively little attention. Existing works often overlook the complementary effect of different perspectives when addressing the MBSR problem. In addition, there are two specific challenges remained to be addressed. One is the heterogeneity of a user's intention and the context information, the other one is the sparsity of the interactions of target behavior. To release the potential of multi-behavior interaction sequences, we propose a novel framework named NextIP that adopts a dual-task learning strategy to convert the problem to two specific tasks, i.e., next-item prediction and purchase prediction. For next-item prediction, we design a target-behavior aware context aggregator (TBCG), which utilizes the next behavior to guide all kinds of behavior-specific item sub-sequences to jointly predict the next item. For purchase prediction, we design a behavior-aware self-attention (BSA) mechanism to extract a user's behavior-specific interests and treat them as negative samples to learn the user's purchase preferences. Extensive experimental results on two public datasets show that our NextIP performs significantly better than the state-of-the-art methods.
Leveraging Scalable Profiling to Learn and Visualize the Latest Trustworthy COVID-19 Medical Research Findings

Accessing large-scale structured datasets such as WDC [31] or CORD-191 is very challenging [ 11, 13, 14, 41, 42]. Even if one topic (e.g. Vaccine Side-Effects) is of interest, the side-effects tables in different papers have hundreds of different schemas, depending on the authors, which significantly complicates both finding and querying them. Here we demonstrate our scalable Meta-data profiler, capable of constructing a standardized interface to a topic of interest in large-scale structured datasets. This interface, called Meta-profile represents a meta-data summary per each topic, representative of the entire dataset. Such profiles can be used as a robust visualization as well as to simplify access to structured data for both data scientists and end users at scale [32, 42]
Modeling Inter-Dependence Between Time and Mark in Multivariate Temporal Point Processes

Temporal Point Processes (TPP) are probabilistic generative frameworks. They model discrete event sequences localized in continuous time. Generally, real-life events reveal descriptive information, known as marks. Marked TPPs model time and marks of the event together for practical relevance. Conditioned on past events, marked TPPs aim to learn the joint distribution of the time and the mark of the next event. For simplicity, conditionally independent TPP models assume time and marks are independent given event history. They factorize the conditional joint distribution of time and mark into the product of individual conditional distributions. This structural limitation in the design of TPP models hurt the predictive performance on entangled time and mark interactions. In this work, we model the conditional inter-dependence of time and mark to overcome the limitations of conditionally independent models. We construct a multivariate TPP conditioning the time distribution on the current event mark in addition to past events. Besides the conventional intensity-based models for conditional joint distribution, we also draw on flexible intensity-free TPP models from the literature. The proposed TPP models outperform conditionally independent and dependent models in standard prediction tasks. Our experimentation on various datasets with multiple evaluation metrics highlights the merit of the proposed approach.
Abstra: Toward Generic Abstractions for Data of Any Model

Digital data sharing leads to unprecedented opportunities to develop data-driven systems for supporting economic activities, the social and political life, and science. Many open-access datasets are RDF (Linked Data) graphs, but others are JSON or XML documents, CSV files, Neo4J property graphs, etc. Potential users need to understand a dataset in order to decide if it is useful for their goal. While some published datasets come with a schema and/or documentation, this is not always the case. We demonstrate Abstra, a dataset abstraction system, which applies on a large variety of data models. Abstra computes a description meant for humans, and integrates Information Extraction to classify dataset content among a set of categories of interest to the user. Our abstractions are conceptually close to Entity-Relationship diagrams, but our entities can have deeply nested structure.
Gold-Polypyrrole-Loaded Eosin in Photo-Mediated Treatment of Hidradenitis Suppurativa: In Vivo Trans-Epidermal Permeation Study and Clinical Case Report

This study reports a new protocol for the management of Hidradenitis Suppurativa (HS), depending on the synergistic photodynamic and photothermal effect of eosin yellow-gold-polypyrrole hybrid nanoparticles (E-G-Ppy NPs). E-G-Ppy NPs and gold-polypyrrole NPs (G-Ppy NPs) were synthesized, characterized, and formulated in topical hydrogels. Then, in vivo trans-epidermal permeation study, under both dark and white light-irradiation conditions, was done on albino mice. The E-G-Ppy hydrogel was then applied on a twenty-four years old female with recurrent axillary HS lesions pretreated with fractional CO2 laser. Thereafter, the treated lesions were irradiated sequentially, using an IPL system, in the visible (~550 nm) and NIR band (630–1100 nm) to activate the synthesized nanoparticles. Results showed that, upon application to mice skin, E-G-Ppy exhibited good tolerance and safety under dark conditions and induced degenerative changes into dermal layers after white-light activation, reflecting deep penetration. Photo-activation of E-G-Ppy hydrogel to a severe Hidradenitis Suppurativa case showed an improvement of 80% of the lesions according to average HS-LASI scores after 4 sessions with no recurrence during a follow-up period of six months. In summary, the dual photodynamic/photothermal activation of E-G-Ppy NPs can represent a promising modality for management of HS. Further expanded clinical studies may be needed.
Neurobiological Signatures of Auditory False Perception and Phantom Perception as a Consequence of Sensory Prediction Errors

Simple Summary The principle of Bayesian inference provides a theoretical framework for stable perception in numerous tasks, including sensory–perceptual tasks, sensorimotor, and motor tasks. Efference copy (EC) signals enable organisms to reduce cognitive loading by decreasing the sensory processing of their own actions. In the auditory domain, the sensorimotor prediction error is responsible for false perceptions, such as auditory hallucinations in schizophrenia, while sensory prediction error also leads to auditory phantom perception such as tinnitus. Attenuation of the N1 component in event-related potentials has been suggested as evidence for the integrity of the EC mechanism. The current study investigated the EC mechanism in auditory false perception and phantom perception as a consequence of sensory prediction errors. N1 attenuation failures were present in tinnitus patients with significant hearing impairment and in those with schizophrenia, indicating that phantom perception after sensory deprivation might lead to impairment in the EC mechanism. However, the corresponding neural representation with spatiotemporal patterns presented differently between patients with schizophrenia and tinnitus. Although the present study had several constraints, the results provide a new perspective on neurobiological aspects of abnormal auditory perception resulting from deficits in predictive coding. Abstract In this study, we hypothesized that top-down sensory prediction error due to peripheral hearing loss might influence sensorimotor integration using the efference copy (EC) signals as functional connections between auditory and motor brain areas. Using neurophysiological methods, we demonstrated that the auditory responses to self-generated sound were not suppressed in a group of patients with tinnitus accompanied by significant hearing impairment and in a schizophrenia group. However, the response was attenuated in a group with tinnitus accompanied by mild hearing impairment, similar to a healthy control group. The bias of attentional networks to self-generated sound was also observed in the subjects with tinnitus with significant hearing impairment compared to those with mild hearing impairment and healthy subjects, but it did not reach the notable disintegration found in those in the schizophrenia group. Even though the present study had significant constraints in that we did not include hearing loss subjects without tinnitus, these results might suggest that auditory deafferentation (hearing loss) may influence sensorimotor integration process using EC signals. However, the impaired sensorimotor integration in subjects with tinnitus with significant hearing impairment may have resulted from aberrant auditory signals due to sensory loss, not fundamental deficits in the reafference system, as the auditory attention network to self-generated sound is relatively well preserved in these subjects.
Computing Subdivision Surface Intersection

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An indicator-based approach for cross-realm coastal biodiversity assessments

Ecosystem status assessments are generally separated into realm-specific analyses (terrestrial, freshwater, estuarine or marine), but without integrating these into a coherent assessment of coastal biodiversity across the land–sea interface. Trends in assessment indicators in coastal versus non-coastal areas have also rarely been considered. In this study we aimed to compile the first cross-realm national biodiversity assessment for the South African coast using three key indicators. The ecological condition, ecosystem threat status, and ecosystem protection level of coastal ecosystem types (n = 186) were determined and compared with those of non-coastal ecosystem types (n = 444). Nearly half (46.9%) of the South African coastal habitat has been degraded compared with 20% of non-coastal areas. Proportionately, there are three-times (60%) as many threatened coastal ecosystem types (or 55% by area) as there are threatened non-coastal ecosystem types (19%, 6% by area). Despite the impacted state of coastal biodiversity, protection levels are generally higher in the coastal zone (87% of ecosystem types have some protection) compared with non-coastal areas (75%), although fewer coastal ecosystem types have met their biodiversity targets (24%, vs 28% for non-coastal ecosystem types). These results illustrate the importance of using a cross-realm approach for status assessments, management and conservation of coastal biodiversity. The assessment methods described are flexible and widely applicable to other regions.
Agency and professional identity among mobile teachers: how does the experience of teaching abroad shape teachers’ professional identity?

ABSTRACT In the context of global mobility research, this study explores agency and identity formation among mid-career teachers who travel abroad to experience teaching in a new country. We conducted in-depth interviews with 16 Israeli teachers and examined their retrospective narratives of their teaching experience. Our findings reveal a complex nexus of identity and agency, whereby identity formation echoes agency choices. We conceptualise forms of agency and point to possible connections between agency types and their use in identity formation. We conclude that under circumstances of rapid change, agency plays an important role in identity formation.
Strategic corporate social responsibility and tariﬀ policies: The timing of commitments and policy implications

: This study considers commitments between tariff policy and corporate social responsibility (CSR) activities, and compares both domestic CSR and foreign CSR. We show that the committed tariff yields lower tariff and higher CSR under domestic CSR, resulting in higher welfare and lower profits, while it might be reversed under foreign CSR if the substitutability is low, which results in lower welfare and profits. Finally, the committed tariff is a desirable equilibrium of an endogenous timing game under domestic CSR, whereas the committed CSR can be under foreign CSR if the substitutability is low. policy and CSR activities. We identified the nationality of the CSR-firm and investigated the role of product substitutability in the sequential choices between different types of CSR. We showed that the strategic CSR is higher and optimal tariff is lower in the committed tariff game than in the committed CSR game under domestic CSR, while the strategic CSR is lower (higher) and optimal tariff is higher (lower) if the product substitutability is low (high) under foreign CSR. We also showed that the CSR-firm ’s profit is lower and social welfare is higher in the committed tariff game than the committed CSR game under domestic CSR, while the CSR- firm’s profit is lower (higher) and social welfare is lower (higher) if the product substitutability is low (high) under foreign CSR. In an endogenous timing game
Physical Activity and Sedentary Behaviors in Primary School Children in Saudi Arabia during the COVID-19 Pandemic: Association with Parents’ Behaviors

During the COVID-19 pandemic, a few studies used accelerometers to assess physical activity (PA) and sedentary behavior in the family context. This study aimed to assess children and parents’ moderate and vigorous physical activity (MVPA) and sedentary time, as well as their relationship in MVPA and sedentary time. Data were collected from 30 parent–child dyads during the COVID-pandemic for seven days, using a hip-worn accelerometer. Children and parents engaged in 65.6 and 34.6 min/day in MVPA and 442.2 and 427.9 min/day sedentary, respectively. There was no evidence of gender difference in MVPA and sedentary between boys and girls. Male parent spent more time in MVPA than female parents. A total of 50% of children and 53.3% of parents met the recommended PA. Children’s MVPA and sedentary time were both correlated with that of their parents. Adjusted linear regression showed that only child MVPA was negatively associated with their parents’ MVPA. There is evidence that multi-level interventions involving parents and children are more effective than interventions focusing on a single group. This study also provides evidence to support the link between MVPA and sedentary time between parents and children. Generalization of the findings is difficult due to the bias of self-selection sample.
Improving Air Pollution Prediction System through Multimodal Deep Learning Model Optimization

Many forms of air pollution increase as science and technology rapidly advance. In particular, fine dust harms the human body, causing or worsening heart and lung-related diseases. In this study, the level of fine dust in Seoul after 8 h is predicted to prevent health damage in advance. We construct a dataset by combining two modalities (i.e., numerical and image data) for accurate prediction. In addition, we propose a multimodal deep learning model combining a Long Short Term Memory (LSTM) and Convolutional Neural Network (CNN). An LSTM AutoEncoder is chosen as a model for numerical time series data processing and basic CNN. A Visual Geometry Group Neural Network (VGGNet) (VGG16, VGG19) is also chosen as a CNN model for image processing to compare performance differences according to network depth. The VGGNet is a standard deep CNN architecture with multiple layers. Our multimodal deep learning model using two modalities (i.e., numerical and image data) showed better performance than a single deep learning model using only one modality (numerical data). Specifically, the performance improved up to 14.16% when the VGG19 model, which has a deeper network, was used rather than the VGG16 model.
A Versatile and Efﬁcient Novel Approach for Mendelian Randomization Analysis with Application to Assess the Causal Effect of Fetal Hemoglobin on Anemia in Sickle Cell Anemia

: Mendelian randomization (MR) is increasingly employed as a technique to assess the causation of a risk factor on an outcome using observational data. The two-stage least-squares (2SLS) procedure is commonly used to examine the causation using genetic variants as the instrument variables. The validity of 2SLS relies on a representative sample randomly selected from a study cohort or a population for genome-wide association study (GWAS), which is not always true in practice. For example, the extreme phenotype sequencing (EPS) design is widely used to investigate genetic determinants of an outcome in GWAS as it bears many advantages such as efﬁciency, low sequencing or genotyping cost, and large power in detecting the involvement of rare genetic variants in disease etiology. In this paper, we develop a novel, versatile, and efﬁcient approach, namely MR analysis under Extreme or random Phenotype Sampling (MREPS), for one-sample MR analysis based on samples drawn through either the random sampling design or the nonrandom EPS design. In simulations, MREPS provides unbiased estimates for causal effects, correct type I errors for causal effect testing. Furthermore, it is robust under different study designs and has high power. These results demonstrate the superiority of MREPS over the widely used standard 2SLS approach. We applied MREPS to assess and highlight the causal effect of total fetal hemoglobin on anemia risk in patients with sickle cell anemia using two independent cohort studies. A user-friendly Shiny app web interface was implemented for professionals to easily explore the MREPS.
Advances in Research on the Involvement of Selenium in Regulating Plant Ecosystems

Selenium is an essential trace element which plays an important role in human immune regulation and disease prevention. Plants absorb inorganic selenium (selenite or selenate) from the soil and convert it into various organic selenides (such as seleno amino acids, selenoproteins, and volatile selenides) via the sulfur metabolic pathway. These organic selenides are important sources of dietary selenium supplementation for humans. Organoselenides can promote plant growth, improve nutritional quality, and play an important regulatory function in plant ecosystems. The release of selenium-containing compounds into the soil by Se hyperaccumulators can promote the growth of Se accumulators but inhibit the growth and distribution of non-Se accumulators. Volatile selenides with specific odors have a deterrent effect on herbivores, reducing their feeding on plants. Soil microorganisms can effectively promote the uptake and transformation of selenium in plants, and organic selenides in plants can improve the tolerance of plants to pathogenic bacteria. Although selenium is not an essential trace element for plants, the right amount of selenium has important physiological and ecological benefits for them. This review summarizes recent research related to the functions of selenium in plant ecosystems to provide a deeper understanding of the significance of this element in plant physiology and ecosystems and to serve as a theoretical basis and technical support for the full exploitation and rational application of the ecological functions of selenium-accumulating plants.
Impact of ﬁnancial development on manufacturing output: The Nigerian

: This study examined the influence of financial deepening on manufacturing output in Nigeria. Using the Vector Autoregression (VAR) based Johansen cointegration technique and an Ordinary Least Square (OLS) estimator on annual data spanning 1970 to 2010, we found insignificant coefficients for credit to the manufacturing sector, banking efficiency and the non-oil trade balance. This suggests a fundamental disconnect between the real and financial sectors of the Nigerian economy. Policymakers should therefore innovate with productivity enhancing reforms which are better tailored to the needs of the manufacturing sector. This should work to boost growth prospects for the aggregate economy.
Lynch Syndrome Identification in Saudi Cohort of Endometrial Cancer Patients Screened by Universal Approach

Lynch syndrome (LS) is the most common cause of inherited endometrial cancer (EC). The prevalence and molecular characteristic of LS in Middle Eastern women with EC have been underexplored. To evaluate the frequency of LS in a cohort of EC patients from Saudi Arabia, a total of 436 EC cases were screened utilizing immunohistochemistry (IHC), MLH1 promoter methylation analysis and next-generation sequencing technology. A total of 53 of 436 (12.2%) ECs were classified as DNA mismatch repair-deficient (dMMR). MLH1 promoter hypermethylation was detected in 30 ECs (6.9%). Three ECs (0.7%) were found to be LS harboring germline pathogenic variants (PVs)/likely pathogenic variants (LPVs): two in the MSH2 gene and one in the MSH6 gene. Three ECs (0.7%) were Lynch-like syndrome (LLS) carrying double somatic MSH2 PVs/LPVs. Seven cases were found to have variants of uncertain significance in cancer-related genes other than MMR genes. Our results indicate that LS prevalence is low among Saudi EC patients and LLS is as common as LS in this ethnicity. Our findings could help in better understanding of the prevalence and mutational spectrum of this syndrome in Saudi Arabia, which may help in defining best strategies for LS identification, prevention and genetic counseling for EC patients.
On the no-gravity limit of gravity

We argue that Relative Locality may arise in the no gravity $G\rightarrow0$ limit of gravity. In this limit gravity becomes a topological field theory of the BF type that, after coupling to particles, may effectively deform its dynamics. We briefly discuss another no gravity limit with a self dual ground state as well as the topological ultra strong $G\rightarrow\infty$ one.