Miracle-dz/UniFAR-FTUs huggingface dataset:
New access to kainic acid via intramolecular palladium-catalyzed allylic alkylation

The formal synthesis of kainic acid was carried out in eleven steps. The key cyclization step was accomplished through an intramolecular palladium-catalyzed allylic alkylation of an allylic sulfone. Further functionalization of the resulting pyrrolidone -featured, inter alia, a N-heterocyclic carbene-copper hydride (NHC-CuH)-mediated stereoconvergent conjugate reduction.
Generalised Boosted Forests

This paper extends recent work on boosting random forests to model non-Gaussian responses. Given an exponential family E[Y |X] = g−1(f(X)) our goal is to obtain an estimate for f . We start with an MLE-type estimate in the link space and then define generalised residuals from it. We use these residuals and some corresponding weights to fit a base random forest and then repeat the same to obtain a boost random forest. We call the sum of these three estimators a generalised boosted forest. We show with simulated and real data that both the random forest steps reduces test-set log-likelihood, which we treat as our primary metric. We also provide a variance estimator, which we can obtain with the same computational cost as the original estimate itself. Empirical experiments on real-world data and simulations demonstrate that the methods can effectively reduce bias, and that confidence interval coverage is conservative in the bulk of the covariate distribution.
Optimized Memoryless Fair-Share HPC Resources Scheduling using Transparent Checkpoint-Restart Preemption

Common resource management methods in supercomputing systems usually include hard divisions, capping, and quota allotment. Those methods, despite their 'advantages', have some known serious disadvantages including unoptimized utilization of an expensive facility, and occasionally there is still a need to dynamically reschedule and reallocate the resources. Consequently, those methods involve bad supply-and-demand management rather than a free market playground that will eventually increase system utilization and productivity. In this work, we propose the newly Optimized Memoryless Fair-Share HPC Resources Scheduling using Transparent Checkpoint-Restart Preemption, in which the social welfare increases using a free-of-cost interchangeable proprietary possession scheme. Accordingly, we permanently keep the status-quo in regard to the fairness of the resources distribution while maximizing the ability of all users to achieve more CPUs and CPU hours for longer period without any non-straightforward costs, penalties or additional human intervention.
Quantifying uncertainty about global and regional economic impacts of climate change

The economic impacts of climate change are highly uncertain. Two of the most important uncertainties are the sensitivity of the climate system and the so-called damage functions, which relate climate change to economic costs and benefits. Despite broad awareness of these uncertainties, it is unclear which of them is most important, especially at the regional level. Here we construct regional damage functions, based on two different global damage functions, and apply them to two climate models with vastly different climate sensitivities. We find that uncertainty in both climate sensitivity and aggregate economic damages per degree of warming are of similar importance for the global economic impact of climate change, with the decrease in global economic productivity ranging between 4% and 24% by the end of the century under a high-emission scenario. At the regional level, however, the effects of climate change can vary even more substantially, depending both on a region’s initial temperature and the amount of warming it experiences, with some regions gaining in productivity and others losing. The ranges of uncertainty are therefore potentially much larger at a regional level. For example, at the end of the century, under a high-emission scenario, we find that India’s productivity decreases between 13% and 57% and Russia’s increases between 24% and 74%, while Germany’s change in productivity ranges from an increase of 8% to a decrease of 4%. Our findings emphasise the importance of including these uncertainties in estimates of future economic impacts, as they are vital for the resulting impacts and thus policy implications.
Batched Neural Bandits

In many sequential decision-making problems, the individuals are split into several batches and the decision-maker is only allowed to change her policy at the end of batches. These batch problems have a large number of applications, ranging from clinical trials to crowdsourcing. Motivated by this, we study the stochastic contextual bandit problem for general reward distributions under the batched setting. We propose the BatchNeuralUCB algorithm which combines neural networks with optimism to address the exploration-exploitation tradeoff while keeping the total number of batches limited. We study BatchNeuralUCB under both fixed and adaptive batch size settings and prove that it achieves the same regret as the fully sequential version while reducing the number of policy updates considerably. We confirm our theoretical results via simulations on both synthetic and real-world datasets.
High-Capacity Reversible Data Hiding in Encrypted Image Using Pixel Predictions and Huffman Encoding

—This paper proposes a high-capacity reversible data hiding scheme for encrypted images using pixel predictions and Huffman encoding. At the owner’s side, we propose to generate the prediction-error histogram (PEH) of the original image using the median edge detector (MED). According to the prediction errors, we divide the pixels into independently encoding pixels and jointly encoding pixels. We then build an optimal Huffman tree to efficiently encode the prediction errors. Then the image is encrypted using the stream cipher and an image encryption key. We replace the lower bit-planes of the encrypted pixels with the Huffman codeword of their prediction error. The rest of the bit-planes are vacated as the embedding room. At the data hider’ s side, we locate the vacated room with the reference of the side information. We then encrypt the additional data using the data hiding key and embed it into the encrypted image. The proposed scheme is separable, namely, the receivers with different authentication can respectively conduct error-free data extraction and/or error-free image recovery. The results show that the embedding capacity of the proposed scheme is larger than previous RDHEI arts. Besides, the proposed scheme can provide high information security. Little detail of the original image can be discovered from the encrypted image by the unauthorized users.
Gemini/Phoenix H-band analysis of the globular cluster AL 3

Context. The globular cluster AL 3 is old and located in the inner bulge. Three individual stars were observed with the Phoenix spectrograph at the Gemini South telescope. The wavelength region contains prominent lines of CN, OH, and CO, allowing the derivation of C, N, and O abundances of cool stars. Aims. We aim to derive C, N, O abundances of three stars in the bulge globular cluster AL 3, and additionally in stars of NGC 6558 and HP 1. The spectra of AL 3 allows us to derive the cluster’s radial velocity. Methods. For AL 3, we applied a new code to analyse its colour-magnitude diagram. Synthetic spectra were computed and compared to observed spectra for the three clusters. Results. We present a detailed identification of lines in the spectral region centred at 15 555 Å, covering the wavelength range 15 525–15 590 Å. C, N, and O abundances are tentatively derived for the sample stars.
Are pre-trained text representations useful for multilingual and multi-dimensional language proficiency modeling?

Development of language proficiency models for non-native learners has been an active area of interest in NLP research for the past few years. Although language proficiency is multidimensional in nature, existing research typically considers a single"overall proficiency"while building models. Further, existing approaches also considers only one language at a time. This paper describes our experiments and observations about the role of pre-trained and fine-tuned multilingual embeddings in performing multi-dimensional, multilingual language proficiency classification. We report experiments with three languages -- German, Italian, and Czech -- and model seven dimensions of proficiency ranging from vocabulary control to sociolinguistic appropriateness. Our results indicate that while fine-tuned embeddings are useful for multilingual proficiency modeling, none of the features achieve consistently best performance for all dimensions of language proficiency. All code, data and related supplementary material can be found at: https://github.com/nishkalavallabhi/MultidimCEFRScoring.
On the Estimation of the Number of Unreachable Peers in the Bitcoin P2P Network by Observation of Peer Announcements

Bitcoin is based on a P2P network that is used to propagate transactions and blocks. While the P2P network design intends to hide the topology of the P2P network, information about the topology is required to understand the network from a scientific point of view. Thus, there is a natural tension between the 'desire' for unobservability on the one hand, and for observability on the other hand. On a middle ground, one would at least be interested on some statistical features of the Bitcoin network like the number of peers that participate in the propagation of transactions and blocks. This number is composed of the number of reachable peers that accept incoming connections and unreachable peers that do not accept incoming connections. While the number of reachable peers can be measured, it is inherently difficult to determine the number of unreachable peers. Thus, the number of unreachable peers can only be estimated based on some indicators. In this paper, we first define our understanding of unreachable peers and then propose the PAL (Passive Announcement Listening) method which gives an estimate of the number of unreachable peers by observing ADDR messages that announce active IP addresses in the network. The PAL method allows for detecting unreachable peers that indicate that they provide services useful to the P2P network. In conjunction with previous methods, the PAL method can help to get a better estimate of the number of unreachable peers. We use the PAL method to analyze data from a long-term measurement of the Bitcoin P2P network that gives insights into the development of the number of unreachable peers over more than five years from 2015 to 2020. Results show that about 31,000 unreachable peers providing useful services were active per day at the end of the year 2020. An empirical validation indicates that the approach finds about 50 % of unreachable peers that provide useful services.
Far UV and Optical Emissions from Three Apparent Supernova Remnants Located at Unusually High Galactic Latitudes

Galactic supernova remnants (SNRs) with angular dimensions greater than a few degrees are relatively rare, as are remnants located more than ten degrees off the Galactic plane. Here we report the results of a UV and optical investigation of two previously suspected SNRs that are more than '10 degrees in both angular diameter and Galactic latitude. One is the proposed G354-33 remnant discovered in 2008 through 1420 MHz polarization maps. GALEX far UV (FUV) emission and Hα mosaics show the object’s radio emission coincident with a nearly continuous 11◦ × 14◦ shell of thin UV filaments which surround a broad Hα emission ring. Another proposed high latitude SNR is the enormous 20◦×26◦ Antlia nebula (G275.5+18.4) discovered in 2002 through low-resolution all-sky Hα images and ROSAT soft X-ray emission. GALEX FUV image mosaics along with deep Hα images and optical spectra of several filaments indicate the presence of shocks throughout the nebula with estimated shock velocities of 70 to over 100 km s−1. We conclude that both of these nebulae are bona fide SNRs with estimated ages less than 10 yr despite their unusually large angular dimensions. Using FUV and optical spectra and images, we also report finding an apparent new, high latitude SNR (G249.2+24.4) approximately 2.8◦ × 4.2◦ in size based on its UV and optical emission properties.
Distributed Optimization With Coupling Constraints

In this article, we investigate distributed convex optimization with both inequality and equality constraints, where the objective function can be a general nonsmooth convex function and all the constraints can be both sparsely and densely coupling. By strategically integrating ideas from primal-dual, proximal, and virtual-queue optimization methods, we develop a novel distributed algorithm, referred to as IPLUX, to address the problem over a connected, undirected graph. We show that IPLUX achieves an $O(1/k)$ rate of convergence in terms of optimality and feasibility, which is stronger than the convergence results of the alternative methods and eliminates the standard assumption on the compactness of the feasible region. Finally, IPLUX exhibits faster convergence and higher efficiency than several state-of-the-art methods in the simulation.
A Novel Finite Difference Method for Euler Equations in 2D Unstructured Meshes

Finite difference method was extended to unstructured meshes to solve Euler equations. The spatial discretization is made of two steps. First, numerical fluxes are computed at the middle point of each edge with high order accuracy. In this step, a one-dimensional curvilinear stencil is assembled for each edge to perform one-dimensional fast non-uniform WENO interpolation derived in this paper, which is much easier and faster than multi-dimensional interpolation. The second step is to compute the divergence of fluxes at each vertex from the fluxes at nearby edges and vertices by least square approximation of multi-dimensional polynomials. The order of the WENO interpolation in the first step and the degree of the polynomial in the second step determined the order of accuracy of the spatial scheme. After that, explicit RungeKutta time discrete scheme is used to update conservative variables. Several canonical numerical cases were solved to test the accuracy, performance and the capability of shock capturing of the developed method.
Relevance of the Isoflavone Absorption and Testicular Function: A Systematic Review of Preclinical Evidence

Isoflavone is a phytoestrogen found in different types of food that can act as endocrine disrupters leading to testicular dysfunction. Currently, fragmented data on the action of this compound in the testicles make it difficult to assess its effects to define a safe dose. Thus, we systematically reviewed the preclinical evidence of the impact of isoflavone on testicular function. We also determined which form (aglycones or glycosylated) was the most used, which allowed us to understand the main biological processes involved in testicular function after isoflavone exposure. This systematic review was carried out according to the PRISMA guidelines using a structured search on the biomedical databases MEDLINE (PubMed), Scopus, and Web of Science, recovering and analyzing 22 original studies. The bias analysis and the quality of the studies were assessed by the criteria described in the risk of bias tool developed by SYRCLE (Systematic Review Centre for Laboratory Animal Experimentation). The aglycones and glycosylated isoflavones proved to be harmful to the reproductive health, and the glycosylates at doses of 50, 100, 146, 200, 300, 500, and 600 mg/kg, in addition to 190 and 1000 mg/L, appear to be even more harmful. The main testicular pathologies resulting from the use of isoflavones are associated with Leydig cells resulting from changes in molecular functions and cellular components. The most used isoflavone to evaluate testicular changes was the genistein/daidzein conjugate. The consumption of high doses of isoflavones promotes changes in the functioning of Leydig cells, inducing testicular changes and leading to infertility in murine models.
The complete mitochondrial genome of Laevistrombus canarium (Gastropoda: Stromboidae)

Abstract Laevistrombus canarium is a marine gastropod species with high economical value. The complete mitochondrial genome of L. canarium has been characterized in this study. The circular mitogenome is 15626 bp in length and comprises 13 protein-coding genes (PCGs), 22 transfer RNA genes, and two ribosomal RNA (rRNA) genes. The organization of these genes is consistent with that of other stromboidae species. The overall base composition of mitochondrial genome is 30.87% A, 38.99% T, 15.54% G, and 14.60% C, with 69.86% AT. Phylogenetic analysis further implies that L. canarium is placed within the Stromboidae.
Electrochemistry Behind Electrocoagulation Using Iron Electrodes

Electrocoagulation (EC) has been known for more than a century. Applications in industries as a water and wastewater treatment process have been adapted for the removal of metals, non metals, suspended solids, organic compounds, COD and BOD. Iron electrodes have been preferred over aluminum due to their durability and cost. However, the electrochemical reactions occurring with EC using iron electrodes have not been systematically studied. For a better understanding of the mechanism and reactions for EC using iron electrodes, we present a review of the concept of green rust (GR) and its relationship to the current theory of EC. Experimental results obtained by measuring pH at different zones near the iron electrodes during the EC process are detailed, and are used to illustrate the mechanism and reactions that occur at both, the anode and cathode. Mechanism and reactions presented explain phenomena associated with EC and are congruent with solubility and Pourbaix diagrams.
Primary Mediastinal Neuroendocrine Tumor: A Case of Atypical Carcinoid

Primary mediastinal neuroendocrine tumor (PMNET) is an extremely rare clinical entity and few cases have been described in the literature. Here, we report a histologically confirmed rare PMNET case of a 66-year-old male patient with a mass detected in the anterior upper mediastinum by chest high-resolution computed tomography (HRCT). Early detection and surgical intervention of this neoplasm are critical for long term survival, though the tumor is associated with a dismal outcome.
Diabetic Peripheral Neuropathy in Ethiopia: A Systematic Review and Meta-Analysis

Background Currently, diabetic peripheral neuropathy (DPN) is one of the most severe complications of diabetes mellitus (DM). Despite the seriousness of this problem, limited evidence is available on the prevalence of diabetic peripheral neuropathy among patients with diabetes mellitus in Ethiopia. In Ethiopia, there were no updated studies that estimate the national prevalence of DPN. Hence, this systematic review and meta-analysis provided a national prevalence of diabetic peripheral neuropathy among patients with diabetes mellitus in Ethiopia. Methods This study was submitted for registration with the International Prospective Register of Systematic Reviews (PROSPERO) in March 2020 and accepted with the registration number CRD42020173831. Different database searching engines were searched online to retrieve related articles, including PubMed, Scopus, Google Scholar, African Journals Online, World Health Organization (WHO) Afro Library, and Cochrane Review. The reviewers used the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guideline in the reviewing process. In this systematic review and meta-analysis, all published and unpublished articles were analyzed. The reviewers used the random effects model to estimate the pooled prevalence of diabetic peripheral neuropathy among diabetes mellitus patients. The reviewers conducted the statistical analysis using the R version 3.5. 3 and RStudio version 1.2. 5033 software for Windows. The reviewers evaluated the heterogeneity across the included studies by the inconsistency index (I2). The reviewers examined the publication bias by the funnel plot. Results The search of the databases produced 245 papers. After checking the inclusion and exclusion criteria, 38 articles with 14029 total patients with diabetes mellitus were found suitable for the review. Except for three (retrospective cohort study), all studies were cross-sectional. The overall pooled prevalence of diabetic peripheral neuropathy was 22% (95% CI 18% to 26%). The subgroup analysis of diabetic peripheral neuropathy among patients with diabetes in the different regions was 23% (95% CI 17% to 29%) in Addis Ababa, 27% (95% CI 16% to 38%) in Oromia, 16% (95% CI 14% to 18%) in South nation and nationalities, and 15% (95% CI 6% to 24%) in Amhara. Conclusions More than one-fifth of patients with diabetes have diabetic peripheral neuropathy. According to this study, the prevalence of diabetic peripheral neuropathy in Ethiopia is considerably high. This evidence suggests that attention should be given to patients with diabetes in monitoring patients' blood glucose.
Brachial-Ankle Pulse Wave Velocity as a Novel Modality for Detecting Early Diabetic Nephropathy in Type 2 Diabetes Patients

Brachial-ankle pulse wave velocity (baPWV) has been shown to correlate with a host of disorders associated with arterial stiffness. Type 2 diabetes is associated with the involvement of both small vessels and large vessels. Studies on the relevance of baPWV to early diabetic nephropathy are scarce. This retrospective observational case-control study enrolled 120 patients with type 2 diabetes from our medical records. We classified patients into two groups depending on the magnitude of albuminuria: 60 patients with microalbuminuria were classified as the early diabetic nephropathy group (EDN group) and 60 patients without albuminuria were classified as the diabetes without nephropathy group (DWN group). An additional 30 nondiabetic age- and sex-matched controls were also enrolled. Data regarding the lipid profile, blood pressure, baPWV, high-sensitivity C reactive protein (hs-CRP) level, anthropometric measurements, urine albumin/creatinine ratio (UACR), serum creatinine level, and glycemic control indices (i.e., fasting plasma glucose (FPG), postprandial glucose (PPG), and glycosylated hemoglobin (hemoglobin A1c, HbA1c)) were recorded for all enrolled participants. baPWV was significantly higher in the EDN group than in the DWN group. Moreover, baPWV was positively correlated with age, duration of diabetes, obesity, poor glycemic control, and high serum levels of triglycerides (TG), hs-CRP, creatinine, and uric acid as well as a high UACR (all P < 0.01). A significant negative correlation was found between baPWV and high-density lipoprotein levels (P < 0.05). Multivariate regression analysis showed that the hs-CRP level and duration of diabetes most strongly influenced baPWV. baPWV may be a convenient, noninvasive, and reproducible method for detecting early diabetic nephropathy.