Miracle-dz/UniFAR-FTUs huggingface dataset:
Small-scale variability of stratospheric ozone during the sudden stratospheric warming 2018/2019 observed at Ny-Ålesund, Svalbard

Abstract. Middle atmospheric ozone, water vapour and zonal and meridional wind profiles have been measured with the two ground-based microwave radiometers GROMOS-C and MIAWARA-C. The instruments have been located at the Arctic research base AWIPEV at Ny-Ålesund, Svalbard (79∘ N, 12∘ E), since September 2015. GROMOS-C measures ozone spectra in the four cardinal directions with an elevation angle of 22∘. This means that the probed air masses at an altitude of 3 hPa (37 km) have a horizontal distance of 92 km to Ny-Ålesund. We retrieve four separate ozone profiles along the lines of sight and calculate daily mean horizontal ozone gradients which allow us to investigate the small-scale spatial variability of ozone above Ny-Ålesund. We present the evolution of the ozone gradients at Ny-Ålesund during winter 2018/2019, when a major sudden stratospheric warming (SSW) took place with the central date at 2 January, and link it to the planetary wave activity. We further analyse the SSW and discuss our ozone and water vapour measurements in a global context. At 3 hPa we find a distinct seasonal variation of the ozone gradients. The strong polar vortex during October and March results in a decreasing ozone volume mixing ratio towards the pole. In November the amplitudes of the planetary waves grow until they break in the end of December and an SSW takes place. From November until February ozone increases towards higher latitudes and the magnitude of the ozone gradients is smaller than in October and March. We attribute this to the planetary wave activity of wave numbers 1 and 2 which enabled meridional transport. The MERRA-2 reanalysis and the SD-WACCM model are able to capture the small-scale ozone variability and its seasonal changes.
Comparative Study on the Sterol Composition of Marine Mollusks

From the viewpoint of comparative biochemistry, the sterol compositions of mollusks belonging to the class Gastropoda (three orders, nine families, sixteen genera, seventeen species), Pelecypoda (two orders, three families, three genera, three species), and Polyplacophora (one species) were investigated by using gas-liquid chromatography on 1.5% OV-17. The gastropods were found to contain cholesterol as a main sterol. In the case of Murex asianus, Cymatiidae sp. , Charonia sauliae, and Conomurex luhuanus, however, other C27- and C28- sterols were detected in addition to cholesterol (42-64%). Compared to the gastropods, the pelecypods appeared to contain relatively small amount of cholesterol (26-35%) and revealed the very complex composition of sterols. On the other hand, the chiton, Liolophura japonica, belonging to the most primitive mollusks, was found to contain 7-cholestenol ( ? 7-sterol) contrasting that of the other mollusks.
Using Undersampling with Ensemble Learning to Identify Factors Contributing to Preterm Birth

In this paper, we propose Ensemble Learning models to identify factors contributing to preterm birth. Our work leverages a rich dataset collected by a NIEHS P42 Center that is trying to identify the dominant factors responsible for the high rate of premature births in northern Puerto Rico. We investigate analytical models addressing two major challenges present in the dataset: 1) the significant amount of incomplete data in the dataset, and 2) class imbalance in the dataset. First, we leverage and compare two types of missing data imputation methods: 1) mean-based and 2) similarity-based, increasing the completeness of this dataset. Second, we propose a feature selection and evaluation model based on using undersampling with Ensemble Learning to address class imbalance present in the dataset. We leverage and compare multiple Ensemble Feature selection methods, including Complete Linear Aggregation (CLA), Weighted Mean Aggregation (WMA), Feature Occurrence Frequency (OFA) and Classification Accuracy Based Aggregation (CAA). To further address missing data present in each feature, we propose two novel methods: 1) Missing Data Rate and Accuracy Based Aggregation (MAA), and 2) Entropy and Accuracy Based Aggregation (EAA). Both proposed models balance the degree of data variance introduced by the missing data handling during the feature selection process, while maintaining model performance. Our results show a 42% improvement in sensitivity versus fallout over previous state-of-the-art methods.
On the Locality of Nash-Williams Forest Decomposition and Star-Forest Decomposition

Given a graph G=(V,E) with arboricity a, we study the problem of decomposing the edges of G into (1+ε)a disjoint forests in the distributed LOCAL model. While there is a polynomial time centralized algorithm for a-forest decomposition (e.g. [Imai, J. Operation Research Soc. of Japan '83]), it remains an open question how close we can get to this exact decomposition in the LOCAL model.
Bounded Rational Formation of Beliefs: Explaining Biased Assessment of Probabilities in Insurance and Hedging Markets†

We show that, jointly with moral hazard and adverse selection, insurance and hedging activities present an additional problem related to the accuracy of agents’ beliefs. In particular, we show that contrary to the market selection hypothesis, departure from accurate beliefs is, in some circumstances, beneficial for agents. To prove it, we provide a standard canonical general equilibrium model of insurance markets showing that bounded rational moderate optimistic traders with incorrect beliefs obtain, period by period, higher actual expected utility and higher actual expected wealth than agents with accurate beliefs. Our findings are then consistent with the empirical evidence showing a systematic and coherent optimistic bias of agents in the assessment of probabilities. JEL classification: D51, D84, D90.
A multi-class classification model for supporting the diagnosis of type II diabetes mellitus

Background Numerous studies have utilized machine-learning techniques to predict the early onset of type 2 diabetes mellitus. However, fewer studies have been conducted to predict an appropriate diagnosis code for the type 2 diabetes mellitus condition. Further, ensemble techniques such as bagging and boosting have likewise been utilized to an even lesser extent. The present study aims to identify appropriate diagnosis codes for type 2 diabetes mellitus patients by means of building a multi-class prediction model which is both parsimonious and possessing minimum features. In addition, the importance of features for predicting diagnose code is provided. Methods This study included 149 patients who have contracted type 2 diabetes mellitus. The sample was collected from a large hospital in Taiwan from November, 2017 to May, 2018. Machine learning algorithms including instance-based, decision trees, deep neural network, and ensemble algorithms were all used to build the predictive models utilized in this study. Average accuracy, area under receiver operating characteristic curve, Matthew correlation coefficient, macro-precision, recall, weighted average of precision and recall, and model process time were subsequently used to assess the performance of the built models. Information gain and gain ratio were used in order to demonstrate feature importance. Results The results showed that most algorithms, except for deep neural network, performed well in terms of all performance indices regardless of either the training or testing dataset that were used. Ten features and their importance to determine the diagnosis code of type 2 diabetes mellitus were identified. Our proposed predictive model can be further developed into a clinical diagnosis support system or integrated into existing healthcare information systems. Both methods of application can effectively support physicians whenever they are diagnosing type 2 diabetes mellitus patients in order to foster better patient-care planning.
No Differences in Clinical Outcomes of Suture Tape Augmented Repair Versus Broström Repair Surgery for Chronic Lateral Ankle Instability

Background: Suture tape (ST) augmented repair, an alternative to traditional Broström repair (BR), may protect the repaired anterior talofibular ligament during ligament healing. No systematic review of cohort studies has been conducted to compare traditional BR with ST-augmented repair for chronic lateral ankle instability. Purpose: To review the current evidence in the literature to ascertain whether ST-augmented repair is superior to traditional BR in managing chronic lateral ankle instability. Study Design: Systematic review; Level of evidence, 3. Methods: A literature search was performed to identify relevant articles published in PubMed, Embase, and Cochrane Library databases in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. The search included cohort studies comparing the efficacy of BR and ST-augmented repair procedures in terms of incidence of instability recurrence, functional scores, talar tilt angle (TTA), anterior talar translation (ATT), and complication rate. Methodological quality was assessed using the Jadad scale for randomized studies and the Newcastle-Ottawa Scale for nonrandomized studies. Results: A total of 4 clinical trials with 254 patients were included. No significant differences were detected between BR and ST-augmented repair procedures in terms of incidence of recurrent instability, American Orthopaedic Foot & Ankle Society score, Foot and Ankle Outcome Score, Foot and Ankle Ability Measure, TTA, ATT, or complication rate. The ST group appeared to have a shorter operation time compared with the BR group. Conclusion: No significant differences were found between ST-augmented repair and BR surgery regarding incidence of recurrent instability, functional outcome scores, or complication rates. Although technically challenging, the ST-augmented repair procedure appears to be a safe and fast option.
Plasma Biomarkers of Reticular Pseudodrusen and the Risk of Progression to Advanced Age-Related Macular Degeneration

Purpose To determine, using an aptamer-based technology in patients with intermediate age-related macular degeneration (AMD), (1) if there is a difference in plasma levels of 4979 proteins in patients with and without reticular pseudodrusen (RPD), and (2) if plasma levels of proteins are related to time to conversion to advanced AMD. Methods Patients with intermediate AMD and RPD were identified from an AMD registry. Relative concentrations of each protein were log (base 2) transformed and compared between patients with and without RPD using linear regression. A Cox proportional hazards survival model was fit to each aptamer to quantify associations with time to conversion. A pathway analysis was conducted in converters versus non-converters using the Reactome database. Results Of the 109 intermediate AMD patients, 39 had bilateral RPD (36%). Two proteins, TCL1A and CNDP1, were lower in patients in the intermediate AMD group with RPD. Twenty-one patients converted to advanced AMD with a median time to conversion of 25.2 months (range, 2.3–48.5 months) and median follow-up time in non-converters of 26.4 months (range, 0.03–49.7 months). Several proteins (lysozyme C, TFF3, RNAS6, and SAP3) distinguished patients who converted from those who did not convert to advanced AMD. The top conversion pathways included tumor necrosis factors bind their physiological receptors, digestion and absorption, signaling by activin, and signaling by TGF-β family members. Conclusions We identified a protein signature related to RPD, as well as to conversion to advanced AMD. The pathway analysis suggests that dysfunction of critical systemic pathways may have links to conversion to advanced AMD. Translational Relevance Biomarkers identified in plasma likely reflect systemic alterations in protein expression in patients with intermediate AMD.
Characteristics of dual carbapenemase-producing Klebsiella pneumoniae strains from an outbreak in Venezuela: a retrospective study

ABSTRACT Objective. To characterize carbapenemase-producing Klebsiella pneumoniae isolated from patients treated at a hospital in Cumaná, Sucre, Venezuela. Methods. This was a retrospective study conducted at the general hospital in Cumaná where 58 K. pneumoniae strains were analyzed for resistance to antimicrobials, specifically carbapenems, in January – June 2015. Production of metallo-β-lactamases and serine carbapenemases was determined by the double-disc synergy test, using EDTA-sodium mercaptoacetic acid and 3-aminophenyl boronic acid discs, respectively. Multiplex-PCR was used to detect genes coding for carbapenemases. Molecular typing using ERIC-PCR determined the presence of clones. Results. Four strains of K. pneumoniae resistant to carbapenems were identified. Phenotypic methods for detection of metallo-β-lactamases and serine carbapenemases were positive, and PCR demonstrated the co-presence of blaNDM and blaKPC genes in all four strains. ERIC-PCR identified two clones circulating in the hospital. Conclusions. Infection control strategies are needed at the central hospital in Cumaná and its surrounding areas to prevent the spread of these pathogens, especially given the high levels of migration from Venezuela to other countries in South America.
Neuropsychiatric symptoms in brain diseases - historical foundations

ABSTRACT. Neuropsychiatric symptoms, which may appear alone or combined with cognitive and neurological manifestations, are frequent in many brain dysfunctions or lesions due to vascular, traumatic, neurodegenerative, or systemic conditions. Throughout history, many of the most prominent names have contributed to the clinical definition of the currently recognized mental symptoms and syndromes. The present paper aims at providing a comprehensive overview of the development, from ancient to modern times, of some widely known concepts and constructs about such neuropsychiatric disorders.
Anoxia-Induced Oxygen Debt of Goldfish (Carassius auratus L.)

Continuous O₂, consumption measurements of goldfish acclimated to 20°C were carried out at a constant O₂ concentration. The diurnal activity pattern was found to disappear in complete darkness, which resulted in a constant (resting) metabolic rate. After exposure to diferent anoxia periods the excess O₂ consumption was quantified. Short exposures up to 3 h did not result in a significant O₂ debt. However, starting from 4 h anoxia a linear increase of the O₂, debt was observed. Repayment of the O₂, debt lasted up to 24 h. There is a striking resemblance between the ethanol excretion by goldfish and the anoxia-induced O₂ debt, which suggests that the O₂, debt is related to recovery of the glycogen pools.
The Primary Outcome of a Prospective Study: Nucleoplasty with Endoscopic Microdiscectomy

Purpose: Evaluation of combined endoscopic microdiscectomy with Radiofreqent ablation Nucleoplasty where it is predicted to show more satisfying short-term outcome. Study Design: A consecutive cohort of 23 patients with lumbar discogenic back pain who underwent Nucleoplasty with endoscopic microdiscectomy. Outcome measurements evaluating pain intensity and functional disability were completed preoperatively, at 1 months, at 6 months, and at the 1-year follow-up visit. Methods: All cases (N=23) following up with confirmed diagnosis of contained lumber discogenic back pain, who failed conservative treatment and fulfilled the criteria for surgical intervention, then underwent endoscopic microdiscectomy with nucleoplasty, and followed up by regular clinic visits for a period of one year maximum. Primary outcome variables that are going to be used in the research is Visual analogue scale (out of 10) and the Oswestry disability index (out of 100). Results: Of the 23-patient cohort, the 1 year follow up rate was at 100%. The mean VAS for low back pain preoperatively, postoperatively, 1 month, 6 months, and 1 year were 9.17, 6.04, 4.57, 2.02 respectively. The functional assessment was evaluated using ODI and showed a mean of 52.75 preoperatively, and 34.96 at 1 month post operatively, 29.30 at 6 months post operatively, and 16.96 at year post operatively. Conclusion: In this minimal invasive approach, Nucleoplasty with Endoscopic Microdiscectomy, it showed promising short-term outcomes with less post-operative pain, hospital stay, minimal blood loss and no reported post-operative complication which can be an alternative option to the standard open Microdiscectomy.
A Large-Scale Benchmark Study Investigating the Impact of User Experience, Task Complexity, and Start Conﬁguration on Robot Skill Learning

In this work, we contribute a large-scale study benchmarking the performance of existing skill learning from demonstration approaches. By way of this study, our aim is to bring to attention some of the challenges associated with skill learning in real-world scenarios and the limitations of existing methods in overcoming these challenges. We provide our conclusions based on ratings provided by Amazon Mechanical Turk (AMT) users for the task executions.
Securing Public-key Cryptography on the Android Platform

Every second of every day large amounts of confidential data are encrypted to enable financial transactions, intelligence operations, and countless other tasks. Public-key cryptography underlies the security of all of these systems and is used to prevent an attacker from getting access to private information. The cryptographic algorithms that secure the majority of these interactions are widely accepted as sufficiently strong to protect users’ information. The implementations of these algorithms are usually encapsulated in third-party libraries, which are used by systems to secure data. However, there is little assurance that these systems use public-key cryptography correctly, even if they rely on correctly implemented third-party cryptographic libraries. This thesis defines what it means for public-key cryptography to be secure and presents a mechanism that provably enforces it. The definition of safe public-key cryptography is based on one developed by Askarov, Hedin, and Sabelfeld (2008) to reason about information flow and private-key cryptography. We extend our enforcement mechanism to handle language features of the Java programming language, and implement Cryptflow, a tool to track how secure information flows through Java programs and ensure correct use of public-key cryptography. This tool analyzes programs that employ cryptography and rejects programs that exhibit common security vulnerabilities found on the Android Platform, while accepting programs that use cryptography securely. This thesis is a step toward enforcing the secure use of public-key cryptography and guaranteeing that confidential information is encrypted properly.
Collaboration and Internationalization of SMEs: Insights and Recommendations from a Systematic Review

This article performs a systematic literature review of the undeniably diverse – and somewhat fragmented – current state of research on the collaborations and internationalization of small and medium-sized enterprises (SMEs). We analyze key works and synthesize them into a framework that conceptually maps key antecedents, mediators, and moderators that influence the internationalization of SMEs. In addition, we highlight limitations of the literature, most notably in terms of theoretical fragmentation; extant theories are deployed and illustrated but rarely extended in a manner that significantly informs subsequent work. At an applied (but related) level, we argue the need for supplementary work that explores the distinct stages of internationalization – and the scope and scale of this process – rather than assuming closure around particular events. With this, we highlight the need for more rigorous and empirically informed explorations of contextual effects that take account of the consequences of developments in the global economic ecosystem.
Reducing Beat Frequency Oscillation in a Two-phase Sliding Mode-controlled ...(JC. Magsino et al)

Received Jul 1, 2019 Revised Feb 6, 2020 Accepted Mar 6, 2020 During static and dynamic loading conditions, voltage regulator modules (VRMs) are expected to provide regulated voltage with minimal ripple even at high current requirement. Compared to regular power supplies, VRMs repetitively experience high-frequency loading conditions that is greatly dependent on the software running in the processor utilizing them. In the scenario that when the transient load frequency is near the VRM’s switching frequency, high-magnitude and low-frequency oscillations are observed at the phase currents. This phenomenon is called the beat frequency oscillation. In this study, the sliding mode control principle is employed to both the voltage and current share loops of the VRM to reduce the phase currents’ beat frequency oscillations. A fixed frequency sliding mode controller is derived and extensively evaluated using the PSIM simulator. Our results show that while maintaining equal load sharing among VRMs at less than 5% sharing error and various types of loading conditions, the sliding mode controller can reduce the beat frequency oscillation phenomenon to 20 kHz at maximum with reduced peak current values. The output voltage is also regulated within the desired 1.65% band.
Symmetric Encryption Algorithms: Review and Evaluation Study

The increased exchange of data over the Internet in the past two decades has brought data security and confidentiality to the fore front. Information security can be achieved by implementing encryption and decryption algorithms to ensure data remains secure and confidential, especially when transmitted over an insecure communication channel. Encryption is the method of coding information to prevent unauthorized access and ensure data integrity and confidentiality, whereas the reverse process is known as decryption. All encryption algorithms aim to secure data, however, their performance varies according to several factors such as file size, type, complexity, and platform used. Furthermore, while some encryption algorithms outperform others, they have been proven to be vulnerable against certain attacks. In this paper, we present a general overview of common encryption algorithms and explain their inner workings. Additionally, we select ten different symmetric encryption algorithms and conduct a simulation in Java to test their performance. The algorithms we compare are: AES, BLOWFISH, RC2, RC4, RC6, DES, DESede, SEED, XTEA, and IDEA. We present the results of our simulation in terms of encryption speed, throughput, and CPU utilization rate for various file sizes ranging from 1MB to 1GB. We further analyze our results for all measures that have been tested, taking into account the level of security they provide.
EFFECTS OF THE PRIVATE-LABEL INVASION

Using supermarket scanner data, we test a variety of hypotheses from trade journals about the invasion of private-label food products. According to conventional industry wisdom, name-brand firms defended their brands against new private-label products by lowering their prices, engaging in additional promotional activities, and increasingly differentiating their products. Our empirical evidence is inconsistent with these beliefs.