Miracle-dz/UniFAR-FTUs huggingface dataset:
Myalgic Encephalomyelitis/Chronic Fatigue Syndrome—Metabolic Disease or Disturbed Homeostasis due to Focal Inflammation in the Hypothalamus?

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex disease characterized by debilitating fatigue, lasting for at least 6 months, with associated malaise, headaches, sleep disturbance, and cognitive impairment, which severely impacts quality of life. A significant percentage of ME/CFS patients remain undiagnosed, mainly due to the complexity of the disease and the lack of reliable objective biomarkers. ME/CFS patients display decreased metabolism and the severity of symptoms appears to be directly correlated to the degree of metabolic reduction that may be unique to each individual patient. However, the precise pathogenesis is still unknown, preventing the development of effective treatments. The ME/CFS phenotype has been associated with abnormalities in energy metabolism, which are apparently due to mitochondrial dysfunction in the absence of mitochondrial diseases, resulting in reduced oxidative metabolism. Such mitochondria may be further contributing to the ME/CFS symptomatology by extracellular secretion of mitochondrial DNA, which could act as an innate pathogen and create an autoinflammatory state in the hypothalamus. We propose that stimulation of hypothalamic mast cells by environmental, neuroimmune, pathogenic and stress triggers activates microglia, leading to focal inflammation in the brain and disturbed homeostasis. This process could be targeted for the development of novel effective treatments.
Effect of epidural levobupivacaine with or without dexamethasone soaked in gelfoam for postoperative analgesia after lumbar laminectomy: A double blind, randomised, controlled trial

Background and Aims: Postoperative pain results in prolonged hospital stay and delayed return to normal activity. This study was conducted with the aim of evaluating the analgesic efficacy of gelfoam soaked in levobupivacaine with or without dexamethasone placed in the epidural space in patients undergoing lumbar laminectomy. Methods: Ninety adult patients were randomised into three groups. Gelfoam was soaked in 12 mL of 0.9% sodium chloride in Group P, 10 mL of 0.25% levobupivacaine + 2 mL of 0.9% sodium chloride in Group L, and 10 mL of 0.25% levobupivacaine + 2 mL of dexamethasone in group LD. The primary outcome was time to first request for rescue analgesia. Total 24-h tramadol consumption, and postoperative visual analog scale (VAS) scores were recorded. Chi-square test and analysis of variance test were used, and P < 0.05 was considered significant. Results: 75 patients completed the study. Time to first rescue analgesia was longer in group LD [10.11 ± 3.10 h] compared with group L [6.48 ± 2.36 h] and group P [1.76 ± 1.13 h]. Total 24-h tramadol consumption was lower in group LD (88 ± 66.58 mg) and group L (120 ± 70.7 mg) compared with group P (280 ± 64.5 mg). Postoperative VAS scores were lower in group LD and group L compared with group P, both at rest and on movement. Conclusion: Epidural gelfoam soaked in levobupivacaine and dexamethasone prolongs the duration of analgesia and decreases rescue analgesic consumption and VAS score postoperatively, in patients undergoing lumbar laminectomy.
Brief Announcement: Asynchronous Secure Distributed Computing with Transferrable Non-equivocation Revisited

In this paper, we consider two fundamental problems in secure distributed computing, namely Asynchronous Byzantine Agreement (ABA) and Asynchronous Secure Multi-party Computation (ASMPC). Our focus is on the honest majority setting, involving a set of n mutually distrusting parties, t of which can be under the control of a computationally bounded Byzantine adversary Adv, where t < n/2. It is well known that in the cryptographic setting where the parties have access to a public-key infrastructure (PKI) set-up and are connected by pair-wise channels, both ABA and ASMPC requires t n/3. However, Clement et al. (PODC 2012) and Backes et al. (PODC 2014) showed that it is possible to design computationally-secure ABA and ASMPC protocols respectively, even with t < n/2, provided the parties are available with a transferrable non-equivocation mechanism. Non-equivocation is a message authentication mechanism, which prevents a corrupt sender from sending conflicting messages to different parties. The transferability of the mechanism enables a receiver to verifiably transfer any authenticated statement to other parties, on behalf of the sender. In this paper, we revisit the work of Clement et al. and Backes et al. and show the following: 1. If n łeq 3t, then it is impossible to achieve the traditional notion of validity by any ABA protocol, which demands that if the inputs of all honest parties are same, say x, then all honest parties should output x at the end of the protocol. Moreover, this holds even if the parties are equipped with a transferrable non-equivocation mechanism. 2. The input phase of the ASMPC protocol of Backes et al (and hence the overall ASMPC protocol) may never terminate for the honest parties. The input phase runs an asynchronous primitive called Agreement on a Common Subset (ACS), which allows the honest parties to agree upon a common subset of n - t parties who provide their inputs for the computation. The ACS primitive runs n parallel instances of an ABA protocol, where the ith instance is to decide whether the ith party has provided its input. We show that since the underlying ABA instances does not satisfy the validity condition, the ACS primitive may never terminate for the honest parties; this results in the honest parties waiting indefinitely to identify the set of n - t input providers.
Cashew nut allergy in Singaporean children

Background There has been an increasing trend of nut allergies in Singapore. Objective The aim of this study was to review the clinical characteristics of children with cashew nut allergy. Methods A retrospective analysis was conducted in a tertiary paediatric referral centre in Singapore from 2008 to 2015. A total of 99 subjects with positive specific IgE (≥0.35 IU/L) to cashew nut were identified. Clinical features including demographics, clinical reaction to cashew nut, associations with other nuts and test specific measurements were recorded. Results The results showed that cutaneous symptoms (71.2%) were the most common allergic manifestations. Anaphylaxis occurred in 3.8% of children. In addition, all cashew nut allergic subjects were cross-reactive (either sensitized or allergic) to pistachio. Cross-reactivity rate with peanuts was 53.8%. There was a strong prevalence of atopy among cashew nut allergic subjects. Conclusion In conclusion, cashew nut allergy is a significant tree nut allergy in Singapore.
Saber on ARM CCA-secure module lattice-based key encapsulation on ARM

The CCA-secure lattice-based post-quantum key encapsulation scheme Saber is a candidate in the NIST’s post-quantum cryptography standardization process. In this paper, we study the implementation aspects of Saber in resourceconstrained microcontrollers from the ARM Cortex-M series which are very popular for realizing IoT applications. In this work, we carefully optimize various parts of Saber for speed and memory. We exploit digital signal processing instructions and efficient memory access for a fast implementation of polynomial multiplication. We also use memory efficient Karatsuba and just-in-time strategy for generating the public matrix of the module lattice to reduce the memory footprint. We also show that our optimizations can be combined with each other seamlessly to provide various speed-memory trade-offs. Our speed optimized software takes just 1,147K, 1,444K, and 1,543K clock cycles on a Cortex-M4 platform for key generation, encapsulation and decapsulation respectively. Our memory efficient software takes 4,786K, 6,328K, and 7,509K clock cycles on an ultra resource-constrained Cortex-M0 platform for key generation, encapsulation, and decapsulation respectively while consuming only 6.2 KB of memory at most. These results show that lattice-based key encapsulation schemes are perfectly practical for securing IoT devices from quantum computing attacks.
Integrated Use of Phosphorus, Animal Manures and Biofertilizers Improve Maize Productivity under Semiarid Condition

Phosphorus unavailability and lack of organic matter in the soils under semiarid condition are the major reasons for low crop productivity. Field trial was conducted to investigate the impact of different animal manures (poultry, cattle, and sheep manures) and phosphorus levels (40, 80, 120, and 160 kg P2O5 ha−1) on yield and yield components of hybrid maize (CS-200) with (+) and without (−) phosphate-solubilizing bacteria (PSB) seed treatment at the Agronomy Research Farm of The University of Agriculture Peshawar, during summer 2014. Our results confirmed that the application of poultry manure significantly (P ≤ 0.05) increased yield and yield components of maize. Phosphorus applied at the rate of 120 kg P2O5 ha−1 increased ear length, grains ear−1, and shelling percentage, while the highest rate of 160 kg P ha−1 increased grains weight, grain yield, and harvest index. Maize seeds treated with PSB (+) before sowing had produced higher yield and yield components than untreated seeds (−). We concluded from this study that com‐ bined application of 160 kg P2O5 ha−1 + poultry manure and seed treatment with PSB (+) could improve crop productivity and profitability under semiarid condition.
A trilinear approach to square function and local smoothing estimates for the wave operator

The purpose of this paper is to improve Mockenhaupt's square function estimate and Sogge's local smoothing estimate in $\mathbb R^3$. For this we use the trilinear approach of S. Lee and A. Vargas for the cone multiplier and some trilinear estimates obtained from the $l^2$-decoupling theorem and multilinear restriction theorem.
Development of Super Ensemble-Based Aviation Turbulence Guidance (SEATG) for Air Traffic Management

A new method for forecasting turbulence is developed and evaluated using the high resolution weather model and in situ turbulence observations from commercial aircraft. The new method is an ensemble of various turbulence metrics from multiple time-lagged ensemble forecasts created using a sequence of four procedures. These include weather modeling, calculation of turbulence metrics, mapping the metrics into a common turbulence-scale, and production of final forecast. The new method uses similar methodology as current operational turbulence forecast with three improvements. First, it uses a higher resolution ((delta)x = 3 km) weather model to capture cloud resolving scale phenomena. Second, it computes the metrics for multiple forecasts that are combined at the same valid time resulting in a time-lagged ensemble of multiple turbulence metrics. Finally, it provides both deterministic and probabilistic turbulence forecasts. Results show the new forecasts match well with observed radar reflectivity along a surface front as well as convectively induced turbulence outside the clouds on research period. Overall performance skill of the new turbulence forecast compared with the observed EDR data during the research period is superior to any single turbulence metric. The probabilistic turbulence forecast is used in an example air traffic management application for creating a wind-optimal route considering turbulence information. The wind-optimal route passing through areas of 50% potential for moderate-or-greater turbulence and the lateral turbulence avoidance routes starting from three different waypoints along the wind-optimal route from Los Angeles international airport to John F. Kennedy international airport are calculated using different turbulence forecasts. This example shows additional flight time is required to avoid potential turbulence encounters.
Character-level Supervision for Low-resource POS Tagging

Neural part-of-speech (POS) taggers are known to not perform well with little training data. As a step towards overcoming this problem, we present an architecture for learning more robust neural POS taggers by jointly training a hierarchical, recurrent model and a recurrent character-based sequence-to-sequence network supervised using an auxiliary objective. This way, we introduce stronger character-level supervision into the model, which enables better generalization to unseen words and provides regularization, making our encoding less prone to overfitting. We experiment with three auxiliary tasks: lemmatization, character-based word autoencoding, and character-based random string autoencoding. Experiments with minimal amounts of labeled data on 34 languages show that our new architecture outperforms a single-task baseline and, surprisingly, that, on average, raw text autoencoding can be as beneficial for low-resource POS tagging as using lemma information. Our neural POS tagger closes the gap to a state-of-the-art POS tagger (MarMoT) for low-resource scenarios by 43%, even outperforming it on languages with templatic morphology, e.g., Arabic, Hebrew, and Turkish, by some margin.
Multi-task learning for historical text normalization: Size matters

Historical text normalization suffers from small datasets that exhibit high variance, and previous work has shown that multi-task learning can be used to leverage data from related problems in order to obtain more robust models. Previous work has been limited to datasets from a specific language and a specific historical period, and it is not clear whether results generalize. It therefore remains an open problem, when historical text normalization benefits from multi-task learning. We explore the benefits of multi-task learning across 10 different datasets, representing different languages and periods. Our main finding—contrary to what has been observed for other NLP tasks—is that multi-task learning mainly works when target task data is very scarce.
Ion-Irradiation-Induced Carbon Nanostructures in Optoelectronic Polymer Materials

The recent results obtained on the ion-irradiation-induced carbon nanostructures in optoelectronic polymer materials exemplified by boron-ion-implanted polymethylme‐ thacrylate (B:PMMA) with an energy of 40 keV, ion doses from 6.25 × 10 14 to 5.0 × 10 16 ions/ cm 2 , and current density <2 μA/cm 2 are reviewed. The positron annihilation spectrosco‐ py (slow positron beam spectroscopy based on Doppler broadening of positron annihilation gamma rays as a function of incident positron energy and positron annihilation lifetime at a positron energy of 2.15 keV, and temperature-dependent positron annihilation lifetime spectroscopy), optical UV-visible spectroscopy, Raman spectrosco‐ py, electrical (current–voltage) measurements, and nanoindentation test are chosen as the main experimental tools for the investigation of low-energy ion-induced processes in B:PMMA. The formation of carbon nanostructures is confirmed for the samples irradiated with higher ion fluences (>10 16 ions/cm 2 ) and the experimental results of the comprehen‐ sive study are found to be in a good agreement with SRIM (stopping and range of ions in matter) simulation results.
Biased hooking for primitive chain network simulations of block copolymers

Primitive chain network model for block copolymers is used here to simulate molecular dynamics in the entangled state with acceptable computational cost. It was found that i) the hooking procedure rearranging the topology of the entangled network is critical for the equilibrium structure of the system, and ii) simulations accounting for the different chemistry, i.e., with a biased hooking probability based on interaction parameter for selection of the hooked partner, generates a reasonable phase diagram.
Localized States in Bi-Pattern Systems

We present a unifying description of localized states observed in systems with coexistence of two spatially periodic states, called bi-pattern systems. Localized states are pinned over an underlying lattice that is either a self-organized pattern spontaneously generated by the system itself, or a periodic grid created by a spatial forcing. We show that localized states are generic and require only the coexistence of two spatially periodic states. Experimentally, these states have been observed in a nonlinear optical system. At the onset of the spatial bifurcation, a forced one-dimensional amplitude equation is derived for the critical modes, which accounts for the appearance of localized states. By numerical simulations, we show that localized structures persist on two-dimensional systems and exhibit different shapes depending on the symmetry of the supporting patterns.
The Direct and Indirect Effects of Environmental Factors on Nurturing Intellectual Giftedness.

Many people believe that environmental factors promote giftedness and invest in many programs to adopt gifted students providing them with challenging activities. Intellectual giftedness is founded on fluid intelligence and extends to more specific abilities through the growth and inputs from the environment. Acknowledging the roles played by the environment in the development of giftedness leads to an effective nurturing of gifted individuals. Further, giftedness requires a context that enables it to develop. However, no study has investigated the direct and indirect effects of environment and fluid intelligence on intellectual giftedness. Thus, this study investigated the contribution of environment factors to giftedness development by conducting tests of fluid intelligence using CCFT and analytical abilities using culture reduced test items covering problem solving, pattern recognition, audiologic, audio-matrices, and artificial language, and self report questionnaire for the environmental factors. A number of 180 high-scoring students were selected using CCFT from a leading university in Malaysia. Structural equation modelling was employed using Amos V.16 to determine the direct and indirect effects of environment factors (family, peers, teachers, school, society, and resources) on the intellectual giftedness. The findings showed that the hypothesized model fitted the data, supporting the model postulates and showed significant and strong direct and indirect effects of the environment and fluid intelligence on the intellectual giftedness. Environment plays an essential role as an incubator hold the energy, direction, and feedback which give the gifted opportunities to manifest their potentials, and support constructing connections between the fluid intelligence and crystallized intelligence through social interfaces (Al-Shabatat et al., 2008). However, giftedness requires social context that enables it to develop and individuals’ aptitudes need nurturance and support. The child surrounded environments such as family, peers, school, and community, beside the social, economical, and political institutions can help to determine the field of talent that society expects to be achieved (Tannenbaum, 1991). However, researchers advocating the environment, or nurturing, account of talent development promoted the belief that appropriate environmental conditions could lead to the development of giftedness to become into talent. Individuals’ dedication to their activities is typically accompanied by great sacrifices for both the individuals themselves and their families, they are surrounded by others, who support and nurture their talent. Further, families, peers, and teachers play an essential role in the development of expertise (Bloom, 1985; Csikzentmihalyi et al., 1993; Feldman, 1986; Winner, 1996).
Organic aerosol components derived from 25 AMS data sets across Europe using a consistent ME-2 based source apportionment approach

Abstract. Organic aerosols (OA) represent one of the major constituents of submicron particulate matter (PM1) and comprise a huge variety of compounds emitted by different sources. Three intensive measurement field campaigns to investigate the aerosol chemical composition all over Europe were carried out within the framework of the European Integrated Project on Aerosol Cloud Climate and Air Quality Interactions (EUCAARI) and the intensive campaigns of European Monitoring and Evaluation Programme (EMEP) during 2008 (May–June and September–October) and 2009 (February–March). In this paper we focus on the identification of the main organic aerosol sources and we define a standardized methodology to perform source apportionment using positive matrix factorization (PMF) with the multilinear engine (ME-2) on Aerodyne aerosol mass spectrometer (AMS) data. Our source apportionment procedure is tested and applied on 25 data sets accounting for two urban, several rural and remote and two high altitude sites; therefore it is likely suitable for the treatment of AMS-related ambient data sets. For most of the sites, four organic components are retrieved, improving significantly previous source apportionment results where only a separation in primary and secondary OA sources was possible. Generally, our solutions include two primary OA sources, i.e. hydrocarbon-like OA (HOA) and biomass burning OA (BBOA) and two secondary OA components, i.e. semi-volatile oxygenated OA (SV-OOA) and low-volatility oxygenated OA (LV-OOA). For specific sites cooking-related (COA) and marine-related sources (MSA) are also separated. Finally, our work provides a large overview of organic aerosol sources in Europe and an interesting set of highly time resolved data for modeling purposes.
BLOCK-MODIFIED WISHART MATRICES : THE EASY

Associated to any complex Wishart matrix W of parameters (dn, dm) and any linear map φ : Mn(C ) → Mn(C ) is the “block-modified” matrix W̃ = (id ⊗ φ)W . Following some previous work with Nechita, we study here the asymptotic ∗-distribution of W̃ , in the d → ∞ limit, in the case where the modification map φ is “easy”, or more generally super-easy, in the quantum algebra/representation theory sense. Under suitable assumptions on φ we obtain in this way a compound free Poisson law. Introduction One of the guiding principles of Random Matrix Theory is that “you can get anything inside a usual random matrix”. Indeed, the random matrices are known to encode a bewildering quantity of interesting mathematical and physical phenomena. See [1], [19]. A particularly efficient construction, which leads to a vast and beautiful combinatorial landscape, which has been barely explored so far, consists in looking at the asymptotic distribution of the block-modified Wishart matrices. To be more precise, consider a Wishart matrix W of parameters (dn, dm), with d, n,m ∈ N . Associated to any linear map φ : Mn(C ) → Mn(C ) is then the “block-modified” matrix W̃ = (id ⊗ φ)W , and the problem is that of computing the ∗-distribution of W̃ , in the d→∞ limit. All this goes back to a 2012 paper of Aubrun [3], where the case of the transposition map φ(A) = A was considered. Aubrun’s computation, leading to shifted semicircles, was generalized soon after in [8], with a result leading to certain free differences of free Poisson laws. A further generalization, leading to large classes of compound free Poisson laws, covering as well the result of Marchenko-Pastur [18], and some computations from [14], [15] was worked out in [9]. A number of supplementary results on the subject, sometimes obtained in different asymptotic regimes, are now available from [2], [16], [20]. According to the general theory in [9], the 4 “basic” computations, corresponding to results in [8], [14], [15], [18], come from the following 4 diagrams: π1 = [ ◦ • ◦ • ] , π2 = [ ◦ • • ◦ ] , π3 = [ ◦ ◦ • • ] , π4 = [ ◦ ◦ ◦ ◦ ] 2010 Mathematics Subject Classification. 60B20 (46L54).