Miracle-dz/UniFAR-FTUs huggingface dataset:
Small Fiber Neuropathy: Clinicopathological Correlations

Small fiber neuropathy develops due to the selective damage of the thin fibers of peripheral nerves. Many common diseases can cause this condition, including diabetes, infections, autoimmune and endocrine disorders, but it can occur due to genetic alterations, as well. Eighty-five skin biopsy-proven small-fiber neuropathy cases were analyzed. Forty-one (48%) cases were idiopathic; among secondary types, hypothyreosis (9.4%), diabetes mellitus (7%), cryoglobulinemia (7%), monoclonal gammopathy with unproved significance (4.7%), Sjögren's disease (3%), and paraneoplastic neuropathy (3%) were the most common causes. Two-thirds (68%) of the patients were female, and the secondary type started 8 years later than the idiopathic one. In a vast majority of the cases (85%), the distribution followed a length-dependent pattern. Intraepidermal fiber density was comparable in idiopathic and secondary forms. Of note, we found significantly more severe pathology in men and in diabetes. Weak correlation was found between patient-reported measures and pathology, as well as with neuropathic pain-related scores. Our study confirmed the significance of small fiber damage-caused neuropathic symptoms in many clinical conditions, the gender differences in clinical settings, and pathological alterations, as well as the presence of severe small fiber pathology in diabetes mellitus, one of the most common causes of peripheral neuropathy.
Prevalence of Plasmodium falciparum Chloroquine Resistance Transporter (Pfcrt76T) Mutation Associated with Antimalarial Drug Resistance in Two Different Epidemiological Setting (Banfora and Saponé) in Burkina Faso Few Years after the Implementation of Artemisnine Based Combination Therapy (ACTs)

Introduction: In spite of considerable progress, malaria remains a public health problem in many areas, particularly in sub-Saharan Africa. One major complexity of malaria disease is caused by the development and the spread of vector and parasite resistance to insecticides and antimalarial drugs respectively. The Pfcrt76T gene mutation has been validated as a marker conferring resistance to chloroquine and other antimalarial drugs. The extension of Plasmodium falciparum resistance to commonly used antimalarial drugs (chloroquine, sulfadoxine-pyrimethamine) led to the adoption and the use of artemisinin-based combinations in Burkina Faso since 2005. Aims: The present study was initiated to assess the prevalence of the Pfcrt76T mutation in two different malaria epidemiological setting after a decade of introduction of artemisinin-based combination therapies (ACTs) in Burkina Faso. Methodology: The study population consisted of 181 uncomplicated malaria patients recruited in Banfora and Saponé health districts in 2012 and 2013. Blood samples were collected from finger prick on filter paper, dried and sent to the Molecular Biology Laboratory at Centre National de Recherche et de Formation sur le Paludisme (CNRFP) for molecular analyzes. DNA of Plasmodium falciparum was extracted with DNA extraction kit (Qiagen®) and the Pfcrt76T mutation was determined based on Polymerase Chain Reaction / Restriction Fragment Length Polymorphism technique (RFLP). Results: The results of this study showed that the frequency of the pfcrt76T mutant allele (33.7%) was statistically lower than the Pfcrt76K wild-type allele (57.4%) in the study area. Moreover, the prevalence of Pfcrt76T mutation was neither associated with the patient age nor with the parasite density while a significant difference was observed between the two epidemiological setting, Banfora and Saponé. Conclusion: The findings of this study has shown a drop in the prevalence of mutant parasites Pfcrt76T in both the study area eight years after the introduction of ACTs compared to previous studies.
Radon Investigation in 650 Energy Efficient Dwellings in Western Switzerland: Impact of Energy Renovation and Building Characteristics

As part of more stringent energy targets in Switzerland, we witness the appearance of new green-certified dwellings while many existing dwellings have undergone energy efficiency measures. These measures have led to reduced energy consumption, but rarely consider their impact on indoor air quality. Consequently, such energy renovation actions can lead to an accumulation of radon in dwellings located in radon-prone areas at doses that can affect human health. This study compared the radon levels over 650 energy-efficient dwellings in western Switzerland between green-certified (Minergie) and energy-renovated dwellings, and analyzed the building characteristics responsible of this accumulation. We found that the newly green-certified dwellings had significantly lower radon level than energy-renovated, which were green- and non-green-certified houses (geometric mean 52, 87, and 105 Bq/m3, respectively). The new dwellings with integrated mechanical ventilation exhibited lower radon concentrations. Thermal retrofitting of windows, roofs, exterior walls, and floors were associated with a higher radon level. Compared to radon measurements prior to energy renovation, we found a 20% increase in radon levels. The results highlight the need to consider indoor air quality when addressing energy savings to avoid compromising occupants’ health, and are useful for enhancing the ventilation design and energy renovation procedures in dwellings.
Temporary and net sinks of atmospheric CO2 due to chemical weathering in subtropical catchment with mixing carbonate and silicate lithology

Abstract. The study provided the major ion chemistry, chemical weathering rates and temporary and net CO2 sinks in the Bei Jiang, which was characterized as a hyperactive region with high chemical weathering rates, carbonate and silicate mixing lithology, and abundant sulfuric acid chemical weathering agent of acid deposition and acid mining drainage (AMD) origins. The total chemical weathering rate of 85.46 t km−2 a−1 was comparable to that of other rivers in the hyperactive zones between the latitudes 0 and 30∘. A carbonate weathering rate of 61.15 t km−2 a−1 contributed to about 70 % of the total. The lithology, runoff, and geomorphology had a significant influence on the chemical weathering rate. The proportion of carbonate outcrops had a significant positive correlation with the chemical weathering rate. Due to the interaction between dilution and compensation effect, a significant positive linear relationship was detected between runoff and total carbonate and silicate weathering rates. The geomorphology factors such as catchment area, average slope, and hypsometric integral value (HI) had nonlinear correlation with chemical weathering rate and showed significant scale effect, which revealed the complexity in chemical weathering processes. Dissolved inorganic carbon (DIC) apportionment showed that CCW (carbonate weathering by CO2) was the dominant origin of DIC (35 %–87 %). SCW (carbonate weathering by H2SO4) (3 %–15 %) and CSW (silicate weathering by CO2) (7 %–59 %) were non-negligible processes. The temporary CO2 sink was 823.41×103 mol km−2 a−1. Compared with the temporary sink, the net sink of CO2 for the Bei Jiang was approximately 23.18×103 mol km−2 a−1 of CO2 and was about 2.82 % of the “temporary” CO2 sink. Human activities (sulfur acid deposition and AMD) dramatically decreased the CO2 net sink, even making chemical weathering a CO2 source to the atmosphere.
The impact of crime on security in tourism

Objectives: Tourism has become one of the main economic sectors of the 21st century. Today, tourism is facing various security threats such as terrorism, crime and potential armed conflicts, and the most common security threat to tourism is crime. The aim of this paper is to analyse how crime affects security in tourism and to describe the consequences of crime for tourism. Methods: A descriptive method was used in this paper to explain the concept of security in tourism and to analyse the relationship between tourism and crime. The data was drawn from the scientific and professional literature and policy documents on this subject. Results: The impact of crime on tourism can be seen on two levels: the macro and micro levels. The impact of crime on the macro level refers to its effects on society in general, on the social community or tourist destination, and the impact of crime at the micro level refers to the effects of crime on individuals. The most significant impact of crime on a tourist destination is the negative image of the destination, resulting in reduced tourist demand. The impact of crime on the micro level is evident in the influence on the behaviour and attitudes of tourists, and their decision to visit or revisit a destination where criminal incidents happen. Conclusions: Crime can have a very negative impact on tourism and security in tourism can not be taken for granted, so it is necessary to make significant efforts to ensure a safe environment for tourists. In order to prevent crime and to create a safe environment for tourists, it is necessary to ensure the cooperation all stakeholders involved in tourism: the tourism industry, local community, national authorities, police and state agencies.
Prognostic impact of NOTCH1 and MYD88 mutations in chronic lymphocytic leukemia patients

Background. Chronic lymphocytic leukemia (CLL) is one of the most common types of leukemia in adults with highly heterogeneous clinical course of the disease. Currently available prognostic factors are not fully efficient in predicting the course of CLL. New molecular mutations such as NOTCH1 and MYD88 could partly explain the CLL heterogeneity and help in identifying clinically relevant groups of patients. Material and methods. NOTCH1 c. 7544_7545delCT (n = 200) in PEST domain (exon 34) and MYD88 L265P (n = 60) mutations was investigated by amplification refractory mutation system (ARMS). Expression of MYD88 in CLL was assessed in peripheral blood (PB) (n = 60) and bone marrow (BM) (n = 92) of CLL patients and 25 healthy volunteers (HVs) using qRT-PCR. Results. NOTCH1 mutation occurred in 18/200 (9.0%) CLL patients. Patients harboring NOTCH1 mutations prevalently belonged to aggressive cases, i.e. cases with an unmutated IGVH gene status, expression of CD38 and ZAP-70. MYD88 mutation occurred in 2/60 (3.3%) CLL patients. MYD88 mutations were strikingly enriched among patients expressing mutated IGVH genes. Our study demonstrated significantly higher PB MYD88 expression than in HVs and relevantly higher PB MYD88 expression in comparison with BM (respectively p < 0.0001 and p = 0.0015). There was no correlation between MYD88 expression in PB and BM and expression of ZAP-70, CD38 and IGVH mutational status. Conclusions. NOTCH1 mutations are more frequently detected in cases with unfavorable biological markers and seem to be independent predictive markers for worse outcome in CLL patients. Further collaborative studies in CLL are obligate to study the prognostic and predictive relevance of MYD88 mutations and expression.
Adaptation of business hotels to the needs of disabled tourists in Poland

This paper presents an overview of the issues related to the readiness of Polish hotel establishments to develop the business tourism services for disabled tourists. The purpose of this study is to identify new innovative amenities for business tourism, with particular emphasis on disabled tourists.The paper has been divided into two parts: theoretical approach to disabled hotel guests in business hotel and the needs of disabled in the Polish business hotels. The authors conducted a study on Polish business hotels. Studies have confirmed that business hotels, like traditional hotels, are not accessible to people with disabilities. The study established a research hypothesis, which was proved in findings, i.e. the hotels are not prepared for older people and people with disabilities. Besides, the research results substantiated the necessity of the business hotels adaption to the needs of disable people. Also, the paper presents the suggestions on what the disabled guests expect from the Polish business hotels. In respect of doing this, further investments and financial support are necessary to allow creating friendly conditions for the disabled people.
MT-BioNER: Multi-task Learning for Biomedical Named Entity Recognition using Deep Bidirectional Transformers

Conversational agents such as Cortana, Alexa and Siri are continuously working on increasing their capabilities by adding new domains. The support of a new domain includes the design and development of a number of NLU components for domain classification, intents classification and slots tagging (including named entity recognition). Each component only performs well when trained on a large amount of labeled data. Second, these components are deployed on limited-memory devices which requires some model compression. Third, for some domains such as the health domain, it is hard to find a single training data set that covers all the required slot types. To overcome these mentioned problems, we present a multi-task transformer-based neural architecture for slot tagging. We consider the training of a slot tagger using multiple data sets covering different slot types as a multi-task learning problem. The experimental results on the biomedical domain have shown that the proposed approach outperforms the previous state-of-the-art systems for slot tagging on the different benchmark biomedical datasets in terms of (time and memory) efficiency and effectiveness. The output slot tagger can be used by the conversational agent to better identify entities in the input utterances.
An O(sr)-Resolution ODE Framework for Discrete-Time Optimization Algorithms and Applications to Convex-Concave Saddle-Point Problems

There has been a long history of using Ordinary Differential Equations (ODEs) to understand the dynamic of discrete-time optimization algorithms. However, one major difficulty of applying this approach is that there can be multiple ODEs that correspond to the same discrete-time algorithm, depending on how to take the continuous limit, which makes it unclear how to obtain the suitable ODE from a discrete-time optimization algorithm. Inspired by the recent paper \cite{shi2018understanding}, we propose the $r$-th degree ODE expansion of a discrete-time optimization algorithm, which provides a principal approach to construct the unique $O(s^r)$-resolution ODE systems for a given discrete-time algorithm, where $s$ is the step-size of the algorithm. We utilize this machinery to study three classic algorithms -- gradient method (GM), proximal point method (PPM) and extra-gradient method (EGM) -- for finding the solution to the unconstrained convex-concave saddle-point problem $\min_{x\in\RR^n} \max_{y\in \RR^m} L(x,y)$, which explains their puzzling convergent/divergent behaviors when $L(x,y)$ is a bilinear function. Moreover, their $O(s)$-resolution ODEs inspire us to define the $O(s)$-linear-convergence condition on $L(x,y)$, under which PPM and EGM exhabit linear convergence. This condition not only unifies the known linear convergence rate of PPM and EGM, but also showcases that these two algorithms exhibit linear convergence in broader contexts.
The Will to Write: An Assessment of the Perceptions of Writing Readiness and Success of First-Generation Students

4 Introduction 5 Literature Review 7 Methodology 20 Findings 24 Writing Ability and Self-Efficacy 24 Writing at the Secondary Level 27 Writing Perceptions and Practices 32 Writing at the Postsecondary Level 36 Recommendations 39 Recommendation 1 40 Recommendation 2 42 Recommendation 3 44 Recommendation 4 46 Recommendation 5 47 Conclusion 48 References 51 Appendix A 56 Appendix B 57
K-resolver: Towards Decentralizing Encrypted DNS Resolution

Centralized DNS over HTTPS/TLS (DoH/DoT) resolution, which has started being deployed by major hosting providers and web browsers, has sparked controversy among Internet activists and privacy advocates due to several privacy concerns. This design decision causes the trace of all DNS resolutions to be exposed to a third-party resolver, different than the one specified by the user's access network. In this work we propose K-resolver, a DNS resolution mechanism that disperses DNS queries across multiple DoH resolvers, reducing the amount of information about a user's browsing activity exposed to each individual resolver. As a result, none of the resolvers can learn a user's entire web browsing history. We have implemented a prototype of our approach for Mozilla Firefox, and used it to evaluate the performance of web page load time compared to the default centralized DoH approach. While our K-resolver mechanism has some effect on DNS resolution time and web page load time, we show that this is mainly due to the geographical location of the selected DoH servers. When more well-provisioned anycast servers are available, our approach incurs negligible overhead while improving user privacy.
Fine-Tuning a Transformer-Based Language Model to Avoid Generating Non-Normative Text

Large-scale, transformer-based language models such as GPT-2 are pretrained on diverse corpora scraped from the internet. Consequently, they are prone to generating content that one might find inappropriate or non-normative (i.e. in violation of social norms). In this paper, we describe a technique for fine-tuning GPT-2 such that the amount of non-normative content generated is significantly reduced. A model capable of classifying normative behavior is used to produce an additional reward signal; a policy gradient reinforcement learning technique uses that reward to fine-tune the language model weights. Using this fine-tuning technique, with 24,000 sentences from a science fiction plot summary dataset, halves the percentage of generated text containing non-normative behavior from 35.1% to 15.7%.
Ultra-long-lived quasi-normal modes of neutron stars in massive scalar-tensor gravity

The spectrum of frequencies and characteristic times that compose the ringdown phase of gravitational waves emitted by neutron stars carries information about the matter content (the equation of state) and the underlying theory of gravity. Typically, modified theories of gravity introduce additional degrees of freedom/fields, such as scalars, which result in new families of modes composing the ringdown spectrum. Simple but physically promising candidates are scalar-tensor theories, which effectively introduce an additional massive scalar field (i.e., an ultra-light boson) that couples non-minimally to gravity, resulting in scalarized neutron stars. Here we present the first calculation of the full ringdown spectrum in such theories. We show that the ringdown spectrum of neutron stars with ultra-light bosons is much richer and fundamentally different from the spectrum in general relativity and that it possesses propagating ultra-long-lived modes.
Improving generalisation of AutoML systems with dynamic fitness evaluations

A common problem machine learning developers are faced with is overfitting, that is, fitting a pipeline too closely to the training data that the performance degrades for unseen data. Automated machine learning aims to free (or at least ease) the developer from the burden of pipeline creation, but this overfitting problem can persist. In fact, this can become more of a problem as we look to iteratively optimise the performance of an internal cross-validation (most often k-fold). While this internal cross-validation hopes to reduce this overfitting, we show we can still risk overfitting to the particular folds used. In this work, we aim to remedy this problem by introducing dynamic fitness evaluations which approximate repeated k-fold cross-validation, at little extra cost over single k-fold, and far lower cost than typical repeated k-fold. The results show that when time equated, the proposed fitness function results in significant improvement over the current state-of-the-art baseline method which uses an internal single k-fold. Furthermore, the proposed extension is very simple to implement on top of existing evolutionary computation methods, and can provide essentially a free boost in generalisation/testing performance.
Mechanism Design for Multi-Party Machine Learning

In a multi-party machine learning system, different parties cooperate on optimizing towards better models by sharing data in a privacy-preserving way. A major challenge in learning is the incentive issue. For example, if there is competition among the parties, one may strategically hide his data to prevent other parties from getting better models. In this paper, we study the problem through the lens of mechanism design and incorporate the features of multi-party learning in our setting. First, each agent's valuation has externalities that depend on others' types and actions. Second, each agent can only misreport a type lower than his true type, but not the other way round. We call this setting interdependent value with type-dependent action spaces. We provide the optimal truthful mechanism in the quasi-monotone utility setting. We also provide necessary and sufficient conditions for truthful mechanisms in the most general case. Finally, we show the existence of such mechanisms is highly affected by the market growth rate and provide empirical analysis.
Universal polarimetric signatures of the black hole photon ring

Black hole images present an annular region of enhanced brightness. In the absence of propagation effects, this "photon ring" has universal features that are completely governed by general relativity and independent of the details of the emission. Here, we show that the polarimetric image of a black hole also displays universal properties. In particular, the photon ring exhibits a self-similar pattern of polarization that encodes the black hole spin. We explore the corresponding universal polarimetric signatures of the photon ring on long interferometric baselines, and propose a method for measuring the black hole spin using a sparse interferometric array. These signatures could enable spin measurements of the supermassive black hole in M87, as well as precision tests of general relativity in the strong field regime, via a future extension of the Event Horizon Telescope to space.
Some insight into Feynman’s approach to electromagnetism

We retrace an ab initio relativistic derivation of the inhomogeneous Maxwell’s equations that was developed by Feynman in unpublished notes, clarifying the analogies and the differences with analogous treatments present in the literature. Unlike the latter, Feynman’s approach stands out because it considers electromagnetic potentials as primary, reflecting his ideas about the quantum foundations of electromagnetism.
Five-linear singular integral estimates of
Brascamp–Lieb-type

We prove the full range of estimates for a five-linear singular integral of Brascamp-Lieb type. The study is methodology-oriented with the goal to develop a sufficiently general technique to estimate singular integral variants of Brascamp-Lieb inequalities that are not of Holder type. The invented methodology constructs localized analysis on the entire space from local information on its subspaces of lower dimensions and combines such tensor-type arguments with the generic localized analysis. A direct consequence of the boundedness of the five-linear singular integral is a Leibniz rule which captures nonlinear interactions of waves from transversal directions.