Miracle-dz/UniFAR-FTUs huggingface dataset:
Artificial Intelligence in NASH Histology: Human Teaches a Machine for the Machine to Help Humans

With the high prevalence of non-alcoholic steatohepatitis (NASH) and its related morbidity, innovate and effective treatments for the disease have been needed. Fortunately, a plethora of clinical trials have been conducted, and many more are on the way (1). Nevertheless, the clinical trials pathway has been associated with limited success and many failures (1). Although non-invasive tests have shown promise and potential to replace liver biopsy, liver histology likely will remain the primary end point for phase 2b/3 trials and a key regulatory approval criterion for NASH drugs in the next few years (1). Unfortunately, histological evaluation of liver tissue has well-known limitations -- sample variability, lack of patient acceptance, low reproducibility among readers, and variable placebo effects -- that have been troublesome in NASH trials, although measures can be taken to reduce the shortcomings of this imperfect gold standard (2).
Myocardial injury in hospitalized patients with COVID-19 infection—Risk factors and outcomes

Myocardial injury in hospitalized patients is associated with poor prognosis. This study aimed to evaluate risk factors for myocardial injury in hospitalized patients with coronavirus disease 2019 (COVID-19) and its prognostic value. We retrieved all consecutive patients who were hospitalized in internal medicine departments in a tertiary medical center from February 9th, 2020 to August 28th with a diagnosis of COVID-19. A total of 559 adult patients were hospitalized in the Sheba Medical Center with a diagnosis of COVID-19, 320 (57.24%) of whom were tested for troponin levels within 24-hours of admission, and 91 (28.44%) had elevated levels. Predictors for elevated troponin levels were age (odds ratio [OR], 1.04; 95% confidence interval [CI], 1.01–1.06), female sex (OR, 3.03; 95% CI 1.54–6.25), low systolic blood pressure (OR, 5.91; 95% CI 2.42–14.44) and increased creatinine level (OR, 2.88; 95% CI 1.44–5.73). The risk for death (hazard ratio [HR] 4.32, 95% CI 2.08–8.99) and a composite outcome of invasive ventilation support and death (HR 1.96, 95% CI 1.15–3.37) was significantly higher among patients who had elevated troponin levels. In conclusion, in hospitalized patients with COVID-19, elevated troponin levels are associated with poor prognosis. Hence, troponin levels may be used as an additional tool for risk stratification and a decision guide in patients hospitalized with COVID-19.
Predicting improvement of work ability in modalities of short- and long-term psychotherapy: The differential impact of reflective ability and other aspects of patient suitability.

OBJECTIVES We investigated how patients' psychological capacities to engage in psychotherapy predict changes in work ability in short- and long-term psychotherapy. METHODS A cohort study of 326 patients, aged 20-46 years and suffering from mood and anxiety disorders, treated by short-term solution-focused, short-term psychodynamic, or long-term psychodynamic psychotherapy, followed-up for 5 years. The Suitability for Psychotherapy Scale, assessed at baseline, was the predictor. Outcomes were assessed at baseline and at six follow-up occasions using the Work Ability Index as the primary indicator. RESULTS Patients with good pretreatment psychological suitability for psychotherapy, good reflective ability in particular, improved more than patients with poor suitability in short-term psychodynamic psychotherapy. Comparisons between therapy groups showed poorer suitability to predict more improvement in solution-focused and in long-term psychodynamic psychotherapy than in short-term psychodynamic psychotherapy. CONCLUSION Patients' psychological suitability for psychotherapy has a different impact on work ability in different therapy modalities and durations.
The effect of perceived social support on psychological distress and life satisfaction among Nepalese migrants in Japan

Background The world is becoming individualized due to modernization. International migration is one of the factors that lead to family dissociation and a lack of social support. Social support is viewed as a crucial factor that contributes to psychological well-being and satisfaction with life among migrants. However, very little is known about the impacts of social support on psychological distress and satisfaction with life among migrants. Therefore, we conducted this study to assess the association of perceived social support with psychological distress and satisfaction with life among Nepalese migrants, and we evaluated the factors associated with receiving social support. Methods This was a cross-sectional study conducted with a convenience sample of Nepalese migrants (N = 249) living in Tokyo. Self-administered online questionnaires were distributed using social networks and chain referral methods. The measures included the Multidimensional Scale of Perceived Social Support, the General Health Questionnaire, and Satisfaction with Life Scale. Descriptive analysis, Pearson’s correlation analysis, and multiple linear regression analyses were performed using SPSS ver. 25. Results The mean (SD) age of the respondents was 31.8 years old (7.3). The family, friends, and significant others subscales of the multidimensional scale of perceived social support were negatively correlated with psychological distress (p<0.01). The family subscale was positively correlated with satisfaction with life (p<0.05), and the friend and significant others subscales were positively correlated with satisfaction with life (p<0.01). Social support from the family was significantly and negatively associated with the type of visa (Beta = -0.160, p = 0.049), and marital status was negatively associated with support from significant others (Beta = -0.175, p = 0.024). Conclusion Social support from family, friends, and significant others was found to be influential in decreasing psychological distress and increasing satisfaction with life among Nepalese migrants in Tokyo. Strengthing social support system through the expansion of interpersonal network may help minimize the psychological distress
Leveraging the replication‐competent avian‐like sarcoma virus/tumor virus receptor‐A system for modeling human gliomas

Gliomas are the most common primary intrinsic brain tumors occurring in adults. Of all malignant gliomas, glioblastoma (GBM) is considered the deadliest tumor type due to diffuse brain invasion, immune evasion, cellular, and molecular heterogeneity, and resistance to treatments resulting in high rates of recurrence. An extensive understanding of the genomic and microenvironmental landscape of gliomas gathered over the past decade has renewed interest in pursuing novel therapeutics, including immune checkpoint inhibitors, glioma‐associated macrophage/microglia (GAMs) modulators, and others. In light of this, predictive animal models that closely recreate the conditions and findings found in human gliomas will serve an increasingly important role in identifying new, effective therapeutic strategies. Although numerous syngeneic, xenograft, and transgenic rodent models have been developed, few include the full complement of pathobiological features found in human tumors, and therefore few accurately predict bench‐to‐bedside success. This review provides an update on how genetically engineered rodent models based on the replication‐competent avian‐like sarcoma (RCAS) virus/tumor virus receptor‐A (tv‐a) system have been used to recapitulate key elements of human gliomas in an immunologically intact host microenvironment and highlights new approaches using this model system as a predictive tool for advancing translational glioma research.
The ‘nightstick’ ischial fracture: a unique oddity of the pelvic injury family

We present an unusual ischial fracture unreported in the literature. We discuss the mechanism and describe the appropriate investigations and surgical management of this fracture. A 36-year-old man sustained a direct blow to his right buttock following a fall from a dirt bike. Examination revealed a firm haematoma, with severe pain on any stretch involving the posterior compartment of the thigh. Radiographs revealed a displaced fracture of the ischial body. CT confirmed integrity of the pelvic ring. The patient underwent open reduction and internal fixation with a partially threaded cannulated screw via a ‘modified longitudinal’ posterior approach to the ischium. The patient was managed partially weight-bearing for 6 weeks; 6-month follow-up confirmed satisfactory clinical and radiographic outcomes. Clinicians should be aware of this novel pelvic fracture and its unusual presentation, currently not included in any pelvic fracture classification system. We report a novel operative technique for appropriate surgical management of such injuries.
The role of sociodemographic and psychosocial variables in early childhood development: A secondary data analysis of the 2014 Multiple Indicator Cluster Survey in the Dominican Republic

Introduction: The association between sociodemographic factors, such as poverty, lack of maternal schooling, and being male at birth, and childhood developmental delay and poor educational outcomes has been established in the Dominican Republic. However, moderating factors present or introduced in families to buffer the effects of such factors on childhood development are still unknown. Methods: We conducted a secondary analysis of the 2014 Multiple Indicator Cluster Survey for the Dominican Republic, a national household survey focused on maternal and child health and development. The first aim of our study was to determine if a sociodemographic model predicted early childhood development. The second aim was to determine if a psychosocial model (including family childrearing practices, discipline, and early childhood stimulation) predicted early childhood development above and beyond the sociodemographic model. Results: We found that both models predicted childhood development significantly, but that the psychosocial model explained 5% more variance than the sociodemographic model. The most relevant sociodemographic predictors were socioeconomic position and mother's education, which uniquely explained 21% and 17% of the early childhood development variance, respectively. The most salient psychosocial predictors of early childhood development were: 1) attendance to an early childhood education program, which uniquely explained 15.0% of the variance; 2) negative discipline, which uniquely explained 12.4% (negative impact); 3) the number of children's books at home, which uniquely explained 12.0%; and 4) stimulating activities at home, which uniquely explained 5%. Conclusion: These results have multiple implications for social programs that aim to improve children's developmental potential in contexts of poverty. Although the results show a protective effect of psychosocial factors, sustainable and large-scale intervention should not be limited to just buffering effects, but to actually solve the underlying problem which is that poverty prevents children from reaching their developmental potential.
Dataset of Natural Language Queries for E-Commerce

Shopping online is more and more frequent in our everyday life. For e-commerce search systems, understanding natural language coming through voice assistants, chatbots or from conversational search is an essential ability to understand what the user really wants. However, evaluation datasets with natural and detailed information needs of product-seekers which could be used for research do not exist. Due to privacy issues and competitive consequences, only few datasets with real user search queries from logs are openly available. In this paper, we present a dataset of 3,540 natural language queries in two domains that describe what users want when searching for a laptop or a jacket of their choice. The dataset contains annotations of vague terms and key facts of 1,754 laptop queries. This dataset opens up a range of research opportunities in the fields of natural language processing and (interactive) information retrieval for product search.
Note the Highlight: Incorporating Active Reading Tools in a Search as Learning Environment

Active reading strategies---such as content annotations (through the use of highlighting and note-taking, for example)---have been shown to yield improvements to a learner's knowledge and understanding of the topic being explored. This has been especially notable in long and complex learning endeavours. With web search engines nowadays used as the primary gateway for learners (or users) to find content that helps them realise their learning goals, they are often poorly equipped with the necessary tools to aid in sense-making, an important aspect of theSearch as Learning (SAL) process. Within theInformation Retrieval (IR) community, research efforts have explored ways to keep track of users' search context by providing a notepad-like interface for the collection of relevant articles, and aid them during the exploratory search process. However, these studies did not explicitly measure the effect that such tools have on knowledge and understanding during a complex, learning-oriented search task. In this paper, we address this research gap by carrying out an Interactive IR experiment with highlighting and note-taking tools built into the search interface. We conducted a crowdsourced between-subjects study (N=115), where participants were assigned to one of four conditions: (i) control (a standard web search interface); (ii) high (highlighting enabled);(iii) note (note-taking enabled); and (iv) highnote (both highlighting and note-taking enabled). We assess participants' learning with a recall-oriented vocabulary learning task, and a cognitively more taxing essay writing task. We find that(i) active reading tools do not aid in the vocabulary learning task. However,(ii) participants in high covered 34% more subtopics, and participants in note covered 34% more facts in their essays when compared to control. Furthermore, (iii) we observed that incorporating active learning tools significantly changed the search behaviour of participants across a number of measures. This is the first work that sheds light on the effect of active reading tools on the SAL process, with important design implications for learning-oriented search systems.
Starting Conversations with Search Engines - Interfaces that Elicit Natural Language Queries

Search systems on the Web rely on user input to generate relevant results. Since early information retrieval systems, users are trained to issue keyword searches and adapt to the language of the system. Recent research has shown that users often withhold detailed information about their initial information need, although they are able to express it in natural language. We therefore conduct a user study (N = 139) to investigate how four different design variants of search interfaces can encourage the user to reveal more information. Our results show that a chatbot-inspired search interface can increase the number of mentioned product attributes by 84% and promote natural language formulations by 139% in comparison to a standard search bar interface.
Influence of input data representations for time-dependent instrument recognition

Abstract An important preprocessing step for several music signal processing algorithms is the estimation of playing instruments in music recordings. To this aim, time-dependent instrument recognition is realized by a neural network with residual blocks in this approach. Since music signal processing tasks use diverse time-frequency representations as input matrices, the influence of different input representations for instrument recognition is analyzed in this work. Three-dimensional inputs of short-time Fourier transform (STFT) magnitudes and an additional time-frequency representation based on phase information are investigated as well as two-dimensional STFT or constant-Q transform (CQT) magnitudes. As additional phase representations, the product spectrum (PS), based on the modified group delay, and the frequency error (FE) matrix, related to the instantaneous frequency, are used. Training and evaluation processes are executed based on the MusicNet dataset, which enables the estimation of seven instruments. With a higher number of frequency bins in the input representations, an improved instrument recognition of about 2 % in F1-score can be achieved. Compared to the literature, frame-level instrument recognition can be improved for different input representations.
The effect of transfer printing on pentacene thin-film crystal structure

The thermal deposition and transfer printing method had been used to produce pentacene thin films on SiO2∕Si and plastic substrates poly(methyl methacrylate) (PMMA) and poly(vinyl pyridine), respectively. X-ray diffraction patterns of pentacene thin films showed reflections associated with highly ordered polycrystalline films and a coexistence of two polymorph phases classified by their d spacing, d(001): 14.4 and 15.4A. The dependence of the c-axis correlation length and the phase fraction on the film thickness and printing temperature were measured. A transition from the 15.4A phase towards 14.4A phase was also observed with increasing film thickness. An increase in the c-axis correlation length of approximately 12%–16% was observed for pentacene (Pn) films transfer printed onto a PMMA coated poly(ethylene terephthalate) substrate at 100–120°C as compared to as-grown Pn films on SiO2∕Si substrates. The transfer printing method is shown to be attractive for the fabrication of pentacene thin-film transist.
Subclausal Local Contexts

One of the central topics in semantic theory over the last few decades concerns the nature of local contexts. Recently, theorists have tried to develop general, non-stipulative accounts of local contexts (Ingason, 2016; Mandelkern & Romoli, 2017a; Schlenker, 2009). In this paper, we contribute to this literature by drawing attention to the local contexts of subclausal expressions. More specifically, we focus on the local contexts of quantificational determiners, e.g. ‘all’, ‘both’, etc. Our central tool for probing the local contexts of subclausal elements is the principle Maximize Presupposition! (Percus, 2006; Singh, 2011). The empirical basis of our investigation concerns some data discussed by Anvari (2018b), e.g. the fact that sentences such as ‘All of the two presidential candidates are crooked’ are unacceptable. In order to explain this, we suggest that the local context of determiners needs to contain the information carried by their restrictor. However, no existing non-stipulative account predicts this. Consequently, we think that the local contexts of subclausal expressions will likely have to be stipulated. This result has important consequences for debates in semantics and pragmatics, e.g. those around the so-called “explanatory problem” for dynamic semantics (Heim, 1990; Schlenker, 2009; Soames, 1982).
RELIABLE ARCHITECTURE OF CROSS ORGANIZATIONAL WORKFLOW MANAGEMENT SYSTEM ON BLOCKCHAIN

Currently most of the workflows in enterprise business processes are implemented and managed as information system. However, workflows between organizations are still processed manually based on paper document because it is difficult for the organizations to trust the process and the result of workflow in the system which is provided by one of the organizations or a third-party organization. In this paper, a system architecture for cross organizational workflow management utilizing blockchain technology is proposed. It eliminates every Single Point of Trust (SPoT) which causes falsification risk of the process and data. Our proposed system architecture is considered to connect with internal workflow management system and accommodates two types of smart contracts for interorganizational workflow definition and interorganizational workflow processing, which validates related data in every transaction. By this architecture, each organization can be aware of the data falsification when the data on one of the organization nodes is falsified by a malicious workflow administrator or a system administrator. Through the implementation of the proposed system and evaluation of the falsification risks based on the attack scenarios along workflow life cycle, it is confirmed that all the risks are avoided by the proposed system architecture.
VoltPillager: Hardware-based fault injection attacks against Intel SGX Enclaves using the SVID voltage scaling interface

Hardware-based fault injection attacks such as voltage and clock glitching have been thoroughly studied on embedded devices. Typical targets for such attacks include smartcards and low-power microcontrollers used in IoT devices. This paper presents the first hardware-based voltage glitching attack against a fully-fledged Intel CPU. The transition to complex CPUs is not trivial due to several factors, including: a complex operating system, large power consumption, multi-threading, and high clock speeds. To this end, we have built VoltPillager, a low-cost tool for injecting messages on the Serial Voltage Identification bus between the CPU and the voltage regulator on the motherboard. This allows us to precisely control the CPU core voltage. We leverage this powerful tool to mount fault-injection attacks that breach confidentiality and integrity of Intel SGX enclaves. We present proof-of-concept key-recovery attacks against cryptographic algorithms running inside SGX. We demonstrate that VoltPillager attacks are more powerful than recent software-only undervolting attacks against SGX (CVE-2019-11157) because they work on fully patched systems with all countermeasures against software undervolting enabled. Additionally, we are able to fault securitycritical operations by delaying memory writes. Mitigation of VoltPillager is not straightforward and may require a rethink of the SGX adversarial model where a cloud provider is untrusted and has physical access to the hardware.
A network pharmacology based approach for predicting active ingredients and potential mechanism of Lianhuaqingwen capsule in treating COVID-19

The outbreak of severe respiratory disease caused by SARS-CoV-2 has led to millions of infections and raised global health concerns. Lianhuaqingwen capsule (LHQW-C), a traditional Chinese medicine (TCM) formula widely used for respiratory diseases, shows therapeutic efficacy in the application of coronavirus disease 2019 (COVID-19). However, the active ingredients, drug targets, and the therapeutic mechanisms of LHQW-C in treating COVID-19 are poorly understood. In this study, an integrating network pharmacology approach including pharmacokinetic screening, target prediction (targets of the host and targets from the SARS-CoV-2), network analysis, GO enrichment analysis, KEGG pathway enrichment analysis, and virtual docking were conducted. Finally, 158 active ingredients in LHQW-C were screen out, and 49 targets were predicted. GO function analysis revealed that these targets were associated with inflammatory response, oxidative stress reaction, and other biological processes. KEGG enrichment analysis indicated that the targets of LHQW-C were highly enriched to several immune response-related and inflammation-related pathways, including the IL-17 signaling pathway, TNF signaling pathway, NF-kappa B signaling pathway, and Th17 cell differentiation. Moreover, four key components (quercetin, luteolin, wogonin, and kaempferol) showed a high binding affinity with SARS-CoV-2 3-chymotrypsin-like protease (3CL pro). The study indicates that some anti-inflammatory ingredients in LHQW-C probably modulate the inflammatory response in severely ill patients with COVID-19.