Miracle-dz/UniFAR-FTUs huggingface dataset:
Similar Product Clustering for Long-Tail Cross-Sell Recommendations

One of the main reasons of the rapid growth and development of e-commerce is the ability of on-line stores to provide large varieties of products, unlike their off-line counterparts, confined by stock spaces. This also means that on-line stores have products, which have few individual purchases but form a large chunk of revenue all together. They are known as "long-tail" products. Long-tail data sparsity makes it challenging to apply recommender algorithms. In this paper, we consider cross-sell recommendations using association rule mining. We consider application of clustering techniques to tackle this problem, and compare different clustering and distance calculation methods. Behavioral data, such as product views, and content data, such as category tree and product names, are used to calculate product similarity. Also, we develop a cross-validation method that allows stable metric calculations for algorithms that focus on long-tail products. We show that product clustering that uses session-based distances improve cross-sell recommendations for long-tail items.
Dosimetric evaluation and systematic review of radiation therapy techniques for early stage node-negative breast cancer treatment

Radiation therapy (RT) is essential in treating women with early stage breast cancer. Early stage node-negative breast cancer (ESNNBC) offers a good prognosis; hence, late effects of breast RT becomes increasingly important. Recent literature suggests a potential for an increase in cardiac and pulmonary events after RT. However, these studies have not taken into account the impact of newer and current RT techniques that are now available. Hence, this review aimed to evaluate the clinical evidence for each technique and determine the optimal radiation technique for ESNNBC treatment. Currently, six RT techniques are consistently used and studied: 1) prone positioning, 2) proton beam RT, 3) intensity-modulated RT, 4) breath-hold, 5) partial breast irradiation, and 6) intraoperative RT. These techniques show dosimetric promise. However, limited data on late cardiac and pulmonary events exist due to challenges in long-term follow-up. Moving forward, future studies are needed to validate the efficacy and clinical outcomes of these current techniques.
Simple Object Classification Using Binary Data

Binary, or one-bit, representations of data arise naturally in many applications, and are appealing in both hardware implementations and algorithm design. In this work, we study the problem of data classiﬁcation from binary data and propose a framework with low computation and resource costs. We illustrate the utility of the proposed approach through styl-ized and realistic numerical experiments, including military classiﬁcation problems like facial and object recognition. We hope that our framework will serve as a foundation for studying similar types of approaches.
The effects of phonological skills and vocabulary on morphophonological processing

Morphophonological processing involves the phonological analysis of morphemes. Item-specific phonological characteristics have been shown to influence morphophonological skills in children. This study investigates the relative contributions of broad phonological skills and vocabulary to production and judgement accuracies of the Dutch past tense and diminutive, two morphophonological processes. Typically developing children (age 5;0–10;0, N = 114) were asked to produce and judge real and nonce diminutives and regular past tenses. Phonological processing skills were measured using a phonological awareness, digit span and nonword repetition task; vocabulary using the PPVT. Phonological skills and vocabulary contributed significantly to the production and judgement of the past tense and diminutive. The results underline the relation between phonological skills and the lexicon and the processing of morphophonology. These findings go further than showing the importance of the item-specific phonological context of the stem and suffix: they indicate that more general skills in the domain of phonology and vocabulary are involved.
The interaction of p130Cas with PKN3 promotes malignant growth

Protein p130Cas constitutes an adaptor protein mainly involved in integrin signaling downstream of Src kinase. Owing to its modular structure, p130Cas acts as a general regulator of cancer cell growth and invasiveness induced by different oncogenes. However, other mechanisms of p130Cas signaling leading to malignant progression are poorly understood. Here, we show a novel interaction of p130Cas with Ser/Thr kinase PKN3, which is implicated in prostate and breast cancer growth downstream of phosphoinositide 3-kinase. This direct interaction is mediated by the p130Cas SH3 domain and the centrally located PKN3 polyproline sequence. PKN3 is the first identified Ser/Thr kinase to bind and phosphorylate p130Cas and to colocalize with p130Cas in cell structures that have a pro-invasive function. Moreover, the PKN3-p130Cas interaction is important for mouse embryonic fibroblast growth and invasiveness independent of Src transformation, indicating a distinct mechanism from that previously characterized for p130Cas. Together, our results suggest that the PKN3-p130Cas complex may represent an attractive therapeutic target in late-stage malignancies. Summary Gemperle et al. present the first report of an interaction between p130Cas with the serine/threonine kinase PKN3, implicated in prostate and breast cancer growth. They show that p130Cas colocalizes with PKN3 in cell structures that have a pro-invasive function and enhance our understanding of PKN3-mediated signaling and tumor growth.
Long-range regulation of p53 DNA binding by its intrinsically disordered N-terminal transactivation domain

Significance The tumor suppressor p53 plays a central role in mediating the cellular response to stress and DNA damage. p53 is a tetramer containing both structured and intrinsically disordered domains that function synergistically to regulate p53 activity. Using intein technology and NMR spectroscopy, we show that the disordered N-terminal transactivation domain of p53 makes intramolecular interactions with the structured DNA-binding domain. These interactions impair binding of p53 to nonspecific DNA sequences but not to p53-specific DNA sequences, providing a means whereby p53 can discriminate more effectively between cognate sites and the vastly more abundant noncognate sites in the genome. Atomic resolution characterization of the full-length p53 tetramer has been hampered by its size and the presence of extensive intrinsically disordered regions at both the N and C termini. As a consequence, the structural characteristics and dynamics of the disordered regions are poorly understood within the context of the intact p53 tetramer. Here we apply trans-intein splicing to generate segmentally 15N-labeled full-length p53 constructs in which only the resonances of the N-terminal transactivation domain (NTAD) are visible in NMR spectra, allowing us to observe this region of p53 with unprecedented detail within the tetramer. The N-terminal region is dynamically disordered in the full-length p53 tetramer, fluctuating between states in which it is free and fully exposed to solvent and states in which it makes transient contacts with the DNA-binding domain (DBD). Chemical-shift changes and paramagnetic spin-labeling experiments reveal that the amphipathic AD1 and AD2 motifs of the NTAD interact with the DNA-binding surface of the DBD through primarily electrostatic interactions. Importantly, this interaction inhibits binding of nonspecific DNA to the DBD while having no effect on binding to a specific p53 recognition element. We conclude that the NTAD:DBD interaction functions to enhance selectivity toward target genes by inhibiting binding to nonspecific sites in genomic DNA. This work provides some of the highest-resolution data on the disordered N terminus of the nearly 180-kDa full-length p53 tetramer and demonstrates a regulatory mechanism by which the N terminus of p53 transiently interacts with the DBD to enhance target site discrimination.
Distribution Status of Hybrid Types in Large Liver Flukes, Fasciola Species (Digenea: Fasciolidae), from Ruminants and Humans in Vietnam

The aim of this study is to delineate ‘admixed hybrid’ and ‘introgressive’ Fasciola genotypes present in the Fasciola population in Vietnam. Adult liver flukes collected from ruminants in 18 Provinces were morphologically sorted out by naked eyes for small (S), medium (M) and large (L) body shapes; and human samples (n=14) from patients. Nuclear ribosomal (rDNA) ITS1 and ITS2, and mitochondrial (mtDNA) nad1 markers were used for determination of their genetic status. Total 4,725 worm samples of ruminants were tentatively classified by their size: 6% (n=284) small (S)-, 13% (n=614) medium (M)-, and 81% (n=3,827) large (L)-forms. All the representative (n=120, as 40 each group) and 14 human specimens, possessed maternal mtDNA of only F. gigantica and none of F. hepatica. Paternally, all (100%) of the L-(n=40) and 77.5% (n=31) of the M-flukes had single F. gigantica rDNA indicating ‘pure’ F. gigantica. A majority (90%, n=36) of the S- and 15% (n=6) of the M-worms had single F. hepatica rDNA, indicating their introgressive; the rest (10%, n=4) of the S- and 7.5% (n=3) of the M-flukes had mixture of both F. gigantica and F. hepatica rDNAs, confirming their admixed hybrid genetic status. Fourteen human samples revealed 9 (64%) of pure F. gigantica, 3 (22%) of introgressive and 2 (14%) of admixed hybrid Fasciola spp. By the present study, it was confirmed that the small worms, which are morphologically identical with F. hepatica, are admixed and/or introgressive hybrids of Fasciola spp. , and able to be the pathogens of human fascioliasis.
Burnout and work satisfaction in general practitioners practicing in rural areas: results from the HaMEdSi study

Background An increasing number of general practitioners (GPs) are not satisfied with their working conditions and are at risk of developing burnout symptoms. As family medicine is becoming a major subject within the medical curriculum in Germany, practicing GPs need to meet higher demands in the future, ie, treating patients and taking part in the education of medical students. Accordingly, we aimed to determine GPs’ work satisfaction and risk of burnout. Materials and methods A survey was conducted among GPs in the region of Siegen-Wittgenstein. This area is a representative rural region in Germany. The Maslach Burnout Inventory (MBI) was used to assess the risk of burnout, while the Work Satisfaction Questionnaire (WSQ) was applied to assess work satisfaction. Canonical correlations were used to examine the association between work satisfaction and burnout in GPs. Results A good model fit was demonstrated for both the MBI and the WSQ. The canonical correlation analysis resulted in two statistically significant canonical functions with correlations of 0.64 (P<0.001) and 0.56 (P=0.001). The full model across all functions was significant (χ2 [18]=72.41, P<0.001). Burden and the global item in the WSQ are good predictors of emotional exhaustion, while patient care, personal rewards and professional relations seem to be good predictors of depersonalization/lack of empathy. This supports the approach to burnout as a multidimensional construct which has to be thoroughly diagnosed. Conclusion Differential interventions tailored to GPs with specific deficits in certain areas should be delivered. GPs with a high score on emotional exhaustion would need a different intervention, as these respondents have different associations with work satisfaction than do GPs with a high score for depersonalization/low empathy. Therefore, the results of this study could contribute to the design of differential interventions aimed at ameliorating symptoms of burnout in GPs.
Mediation analysis in a case‐control study when the mediator is a censored variable

Mediation analysis is an approach for assessing the direct and indirect effects of an initial variable on an outcome through a mediator. In practice, mediation models can involve a censored mediator (eg, a woman's age at menopause). The current research for mediation analysis with a censored mediator focuses on scenarios where outcomes are continuous. However, the outcomes can be binary (eg, type 2 diabetes). Another challenge when analyzing such a mediation model is to use data from a case‐control study, which results in biased estimations for the initial variable‐mediator association if a standard approach is directly applied. In this study, we propose an approach (denoted as MAC‐CC) to analyze the mediation model with a censored mediator given data from a case‐control study, based on the semiparametric accelerated failure time model along with a pseudo‐likelihood function. We adapted the measures for assessing the indirect and direct effects using counterfactual definitions. We conducted simulation studies to investigate the performance of MAC‐CC and compared it to those of the naïve approach and the complete‐case approach. MAC‐CC accurately estimates the coefficients of different paths, the indirect effects, and the proportions of the total effects mediated. We applied the proposed and existing approaches to the mediation study of genetic variants, a woman's age at menopause, and type 2 diabetes based on a case‐control study of type 2 diabetes. Our results indicate that there is no mediating effect from the age at menopause on the association between the genetic variants and type 2 diabetes.
How differing methods of ascribing ethnicity and socio-economic status affect risk estimates for hospitalisation with infectious disease

Abstract Significant ethnic and socio-economic disparities exist in infectious diseases (IDs) rates in New Zealand, so accurate measures of these characteristics are required. This study compared methods of ascribing ethnicity and socio-economic status. Children in the Growing Up in New Zealand longitudinal cohort were ascribed to self-prioritised, total response and single-combined ethnic groups. Socio-economic status was measured using household income, and both census-derived and survey-derived deprivation indices. Rates of ID hospitalisation were compared using linked administrative data. Self-prioritised ethnicity was simplest to use. Total response accounted for mixed ethnicity and allowed overlap between groups. Single-combined ethnicity required aggregation of small groups to maintain power but offered greater detail. Regardless of the method used, Māori and Pacific children, and children in the most socio-economically deprived households had a greater risk of ID hospitalisation. Risk differences between self-prioritised and total response methods were not significant for Māori and Pacific children but single-combined ethnicity revealed a diversity of risk within these groups. Household income was affected by non-random missing data. The census-derived deprivation index offered a high level of completeness with some risk of multicollinearity and concerns regarding the ecological fallacy. The survey-derived index required extra questions but was acceptable to participants and provided individualised data. Based on these results, the use of single-combined ethnicity and an individualised survey-derived index of deprivation are recommended where sample size and data structure allow it.
Nonlinear decision weights or moment-based preferences? A model competition involving described and experienced skewness

The predictive power of cumulative prospect theory and expected utility theory is typically compared using decisions from description, where lotteries' outcome values and probabilities are explicitly stated. In decisions from experience, individuals sample (in the sampling paradigm without cost) from the return distributions to learn outcome values and their relative frequencies; here cumulative prospect theory and expected utility theory require the calculation of probabilities from experience. Individuals, however, may be more attuned to the experienced moments of outcome distributions, rather than the probabilities. We therefore test the mean-variance-skewness model, and retrieve the proportion of expected utility theory (over income), cumulative prospect theory, and mean-variance-skewness populations using a latent-class hierarchical Bayesian model across six large datasets. For simple lotteries (with 1-2 outcomes), we find a mixture of cumulative prospect theory and mean-variance-skewness populations in decisions from both description and experience. For more complex lotteries (with 2-3 outcomes), all participants are classified as cumulative prospect theory types in decisions from description, but as mean-variance-skewness types in decisions from experience. This suggests that in decisions from experience with more complex return distributions, preferences for skewness are more predictive than nonlinear probability weighting.
Current perspectives on psychedelic therapy: use of serotonergic hallucinogens in clinical interventions

Abstract Humans have used serotonergic hallucinogens (i.e. psychedelics) for spiritual, ceremonial, and recreational purposes for thousands of years, but their administration as part of a structured therapeutic intervention is still a relatively novel practice within Western medical and psychological frameworks. In the mid-20th century, considerable advances were made in developing therapeutic approaches integrating administration of low (psycholytic) and high (psychedelic) doses of serotonergic hallucinogens for treatment of a variety of conditions, often incorporating psychoanalytic concepts prevalent at that time. This work contributed seminal insights regarding how these substances may be employed with efficacy and safety in targeted therapeutic interventions, including the importance of optimizing set (frame of mind) and setting (therapeutic environment). More recently, clinical and pharmacological research has revisited the effects and therapeutic potential of psychedelics utilizing a variety of approaches. The current article provides an overview of past and present models of psychedelic therapy, and discusses important considerations for future interventions incorporating the use of psychedelics in research and clinical practice.
Association of Cerebrospinal Fluid Neurofilament Light Protein With Risk of Mild Cognitive Impairment Among Individuals Without Cognitive Impairment

Importance Accumulating data suggest that elevated cerebrospinal fluid (CSF) neurofilament light (NfL) and neurogranin (Ng) levels are associated with cognitive decline and may be useful markers of neurodegeneration. However, to our knowledge, previous studies have not assessed these CSF markers in the community, evaluated them with regards to risk of mild cognitive impairment (MCI), or compared their prognostic value with CSF total tau (T-tau) or phosphorylated tau (P-tau). Objective To determine (1) whether CSF NfL and Ng levels were associated with risk of MCI, (2) the effect size of these markers compared with CSF T-tau or P-tau for risk of MCI, and (3) whether CSF amyloid-&bgr; (A&bgr;42) modified these associations. Design, Setting and Participants The analyses included 648 participants without cognitive impairment who were enrolled into the prospective population-based Mayo Clinic Study of Aging between January 2004 and December 2015 with available CSF data and at least 1 follow-up visit. Participants were followed up for a median of 3.8 years (interquartile range, 2.6-5.4 years). The CSF NfL and Ng levels were measured using an in-house sandwich enzyme-linked immunosorbent assay. The CSF A&bgr;42, T-tau, and P-tau levels were measured with automated electrochemiluminescence immunoassays. Cox proportional hazards models, with age as the timescale, were used to assess the association between CSF NfL, Ng, A&bgr;42, T-tau, or P-tau with risk of MCI after adjusting for sex, education, apolipoprotein E genotype, and the Charlson comorbidity index. To examine CSF A&bgr;42 as an effect modifier, it was categorized into tertiles; the bottom tertile was defined as having elevated brain amyloid. Main Outcomes and Measures Risk of MCI. Results At baseline, the median age of the 648 participants without cognitive impairment was 72.3 years (range, 50.7-95.3 years) and 366 (56.5%) were men; 96 (14.8%) developed incident MCI. Compared with the bottom quartile, the top quartile of CSF NfL was associated with a 3.1-fold increased risk of MCI (hazard ratio, 3.13; 95% CI, 1.36-7.18) in multivariate models. Neither CSF T-tau, P-tau, nor Ng was associated with risk of MCI. There was no interaction between A&bgr;42 and CSF NfL for risk of MCI. Conclusions and Relevance Elevated CSF NfL levels but not CSF T-tau, P-tau or Ng are a risk factor for MCI in a community population and are independent of brain amyloid.
Critical Nodes Identification of Power Grids Based on Network Efficiency

Critical nodes identification is of great significance in protecting power grids. Network efficiency can be used as an evaluation index to identify the critical nodes and is an indicator to quantify how efficiently a network exchanges information and transmits energy. Since power grid is a heterogeneous network and can be decomposed into small functionallyindependent grids, the concept of the Giant Component does not apply to power grids. In this paper, we first model the power grid as the directed graph and define the Giant Efficiency sub-Graph (GEsG). The GEsG is the functionally-independent unit of the network where electric energy can be transmitted from a generation node (i.e., power plants) to some demand nodes (i.e., transmission stations and distribution stations) via the shortest path. Secondly, we propose an algorithm to evaluate the importance of nodes by calculating their critical degree, results of which can be used to identify critical nodes in heterogeneous networks. Thirdly, we define node efficiency loss to verify the accuracy of critical nodes identification (CNI) algorithm and compare the results that GEsG and Giant Component are separately used as assessment criteria for computing the node efficiency loss. Experiments prove the accuracy and efficiency of our CNI algorithm and show that the GEsG can better reflect heterogeneous characteristics and power transmission of power grids than the Giant Component. Our investigation leads to a counterintuitive finding that the most important critical nodes may not be the generation nodes but some demand nodes. key words: network efficiency, giant efficiency sub-graph, the algorithm of critical nodes identification, critical degree, node efficiency loss