Miracle-dz/UniFAR-FTUs huggingface dataset:
New approach to evaluate satellite-derived XCO2 over oceans by integrating ship and aircraft observations

Abstract. Satellite observations provide spatially resolved global estimates of column-averaged mixing ratios of CO 2 (XCO 2 ) over the Earth's surface. The accuracy of these datasets can be validated against reliable standards in some areas, but other areas remain inaccessible. To date, limited reference data over oceans hinder successful uncertainty quantification or bias correction efforts and preclude reliable conclusions about changes in the carbon cycle in some regions. Here, we propose a new approach to analyze and evaluate seasonal, interannual, and latitudinal variations of XCO 2 over oceans by integrating cargo-ship (Ship Of Opportunity – SOOP) and commercial aircraft (Comprehensive Observation Network for Trace gases by Airliner – CONTRAIL) observations with the aid of state-of-the art atmospheric chemistry-transport model calculations. The consistency of the “observation-based column-averaged CO 2 ” dataset (obs. XCO 2 ) with satellite estimates was analyzed over the western Pacific between 2014 and 2017, and its utility as a reference dataset evaluated. Our results demonstrate that the new dataset accurately captures seasonal and interannual variations of CO 2 . Retrievals of XCO 2 over the ocean from GOSAT (Greenhouse Gases Observing Satellite: National Institute for Environmental Studies – NIES v02.75; Atmospheric CO 2 Observation from Space – ACOS v7.3) and OCO-2 (Orbiting Carbon Observatory, v9r) observations show a negative bias of about 1 part per million (ppm) in northern midlatitudes, which was attributed to measurement uncertainties of the satellite observations. The NIES retrieval had higher consistency with obs. XCO 2 at midlatitudes as compared to the other retrievals. At low latitudes, it shows many fewer valid data and high scatter, such that ACOS and OCO-2 appear to provide a better representation of the carbon cycle. At different times, the seasonal cycles of all three retrievals show positive phase shifts of 1 month relative to the observation-based data. The study indicates that even if the retrievals complement each other, remaining uncertainties limit the accurate interpretation of spatiotemporal changes in CO 2 fluxes. A continuous long-term XCO 2 dataset with wide latitudinal coverage based on the new approach has great potential as a robust reference dataset for XCO 2 and can help to better understand changes in the carbon cycle in response to climate change using satellite observations.
Improved Determination of Europa's Long‐Wavelength Topography Using Stellar Occultations

Europa Clipper will arrive at Jupiter at the end of this decade and will explore Europa through a series of flybys. One of its many goals is to characterize Europa's topography and global shape using the Europa Imaging System and Radar for Europa Assessment and Sounding: Ocean to Near‐surface (REASON) instruments. In addition, Europa Clipper's UV Spectrograph will observe stars pass behind (be occulted by) Europa. The spectrograph has sufficiently precise timing, corresponding to a topographic precision of order meters, that these occultations can also serve as altimetric measurements. Because of gaps in the REASON radar altimeter coverage imposed by the flyby geometries, the addition of ∼100 occultations results in a substantial improvement in the recovery of Europa's long‐wavelength shape. Typically, five extra spherical harmonic degrees of topography can be recovered by combining occultations with radar altimetry.
Implementation of Smart Surveillance System Based on Bio-Metrics

— As Internet of things is the between systems administration of every single physical gadget. There is an expanding interest for smart homes where apparatuses respond naturally to change condition conditions and can be effectively controlled through one normal gadget. Smart surveillance system would give the proprietor a significant serenity when he/she is absent at home. In day by day life, individuals want to know the personality of a visitor who goes to their homes, paying little mind to whether they are there around then. The biometric system assumes a vital part in home security, a productive and predictable system must be created for better safety. This paper center around IOT related programmed systems which are intended to open the entryway consequently when a visitor approaches the entryway utilizing biometric system. It is an intrusion detection system that incorporates a Biometric Detection System. At the point when a validated individual uses the unique finger impression sensor, the entrance is allowed inside the house, the entryway naturally opens, notice is sent to the proprietor through SMS. At the point when an unauthenticated individual uses the unique mark sensor, a notice is sent to the proprietor, again through SMS.
A Decade of Lessons Learned from the 2011 Tohoku‐Oki Earthquake

The 2011 Mw 9.0 Tohoku‐oki earthquake is one of the world's best‐recorded ruptures. In the aftermath of this devastating event, it is important to learn from the complete record. We describe the state of knowledge of the megathrust earthquake generation process before the earthquake, and what has been learned in the decade since the historic event. Prior to 2011, there were a number of studies suggesting the potential of a great megathrust earthquake in NE Japan from geodesy, geology, seismology, geomorphology, and paleoseismology, but results from each field were not enough to enable a consensus assessment of the hazard. A transient unfastening of interplate coupling and increased seismicity were recognized before the earthquake, but did not lead to alerts. Since the mainshock, follow‐up studies have (1) documented that the rupture occurred in an area with a large interplate slip deficit, (2) established large near‐trench coseismic slip, (3) examined structural anomalies and fault‐zone materials correlated with the coseismic slip, (4) clarified the historical and paleoseismic recurrence of M∼9 earthquakes, and (5) identified various kinds of possible precursors. The studies have also illuminated the heterogeneous distribution of coseismic rupture, aftershocks, slow earthquakes and aseismic afterslip, and the enduring viscoelastic response, which together make up the complex megathrust earthquake cycle. Given these scientific advances, the enhanced seismic hazard of an impending great earthquake can now be more accurately established, although we do not believe such an event could be predicted with confidence.
Intelligence can be detected but is not found attractive in videos and live interactions

Humans’ extraordinary intelligence seems to extend beyond the needs for survival. One theory to explain this surplus intelligence is that it evolved via sexual selection as a fitness indicator to advertise genetic quality to prospective mates. Consistent with this idea, self-reported mate preferences suggest intelligence is valued across cultures. Yet, as the validity of these self-reports has been questioned, it remains unclear whether objectively assessed intelligence is indeed attractive. We analysed data from two studies to test this key premise of the sexual selection theory of intelligence. In Study 1, 88 target men had their intelligence measured and based on short video clips were rated on intelligence, funniness, physical attractiveness and mate appeal by 179 women. In Study 2 (N = 729), participants took part in 2 to 5 speed-dating sessions in which their intelligence was measured and they rated each other’s intelligence, funniness, and mate appeal. Measured intelligence did not predict increased mate appeal in either study, whereas perceived intelligence and funniness did. More intelligent people were perceived as more intelligent, but not as funnier. Results suggest that intelligence is not important for initial attraction, which raises doubts concerning the sexual selection theory of intelligence.
Phytochemical Screening, in vitro Antioxidant and Anti-inflammatory activity of Freeze-dried Borassus flabellifer L. Seed Powder

Palmyra palm tree, native to Tamil Nadu bears seasonal summer fruits (Nungu) with numerous health benefits. Preserving the fruit throughout the year is essential to enjoy its goodness and health benefits. With this focus, the aim of the present study was to evaluate the phytochemical profile, in vitro antioxidant and anti-inflammatory activity of Borassus flabellifer seed and seed coat in the freeze-dried form. Aqueous seed powder extract was used in this study. Phytochemicals were quantified using standard methods. Bioactive compounds were identified using GC-MS. Radical scavenging potential was evaluated using DPPH, Hydrogen peroxide and Nitric oxide radical scavenging assays. Anti-inflammatory potential was evaluated using Albumin denaturation assay. Statistical significance of mean values was tested using One-way ANOVA followed by Tukey’s test and IC50 value was calculated by non-linear regression analysis using GraphPad. Saponins, tannins, terpenoids, steroids, glycosides, flavonoids, alkaloids and phenols were present in the sample. The aqueous seed powder extract exhibited potent radical scavenging activity in a dose dependent manner and the IC50 value of DPPH, Hydrogen peroxide and Nitric oxide radical scavenging assay was 415.91, 1080.19 and 13.489 μg/mL respectively. The aqueous extract also exhibited potent protein denaturation inhibitory activity with an IC50 value of 1174.9 μg/mL. Results indicate that the phytochemical compounds present in the seed powder could have largely contributed to its good antioxidant and anti-inflammatory activity.
Technology Enhanced Training in Family Medicine during Covid-19 pandemic: Trainers’ and Trainees’ View

Purpose of the study: how to shift from face-to-face clinical training into technology enhanced training during Covid 19 pandemic.Study design: Online trainer simulation with pre-prepared case scenarios and case discussion was our designed interventional training using Zoom application.Results: Regarding trainee’s feedback to the zoom training, 85% of them thought that it was useful. More than 75% of them recommended this online training for future trainees. More than 80% of the trainers were satisfied with the online training experience. More than 75% of them thought that this was a beneficial experience for the participating house officers. Although two-third of the trainers perceived the training to be mildly and moderately overloading, yet more than 80% of them were satisfied with this training experience and about three-fourth of them preferred it on face-to-face training. They suggested increasing the time of the session to allow for more feedback and discussion.Conclusion: Technology enhanced training is a good way of training that can improve many aspects of clinical family medicine skills as communication skills, patient-centred approach, clinical reasoning, and construction of management plan. It can be applied in other specialties especially in crisis times. In the future, it can be used as blended method of training beside face to face training in the clinics so they can complement each other.
Thermal Stability of Clay's Galleries in Polypropylene-Clay (montmorillonite) Nanocomposites using Polypropylene-gMaleic Anhydride as Compatibilizer

Thermal Stability of Clay's Galleries in Polypropylene Clay (montmorillonite) Nanocomposites using Polypropylene-gMaleic Anhydride as Compatibilizer. Superior properties of food packaging can be achieved using nanocomposite technology. However, fabrication of this materials are complex and expensive. Long term objectives of this research is the synthesis of low cost polypropylene clay nanocomposites (PPCN) via a short-cut method known as ‘cascade engineering’. Cascade engineering principle in PPCN fabrication is performed by using compatibilizer (to enable the mixing of PP and clay) masterbatch, and PPCN in one pot process using melt mixer. This paper present the experimental results using small-angle x-ray diffraction (XRD) on the thermal stability of the PPCN. Results from the XRD analysis showed that the clay was intercalated, however no significant changes were observed as a result of variation in mixing time. XRD patterns of the annealed PPCN showed reduction of MMT’s gallery (deintercalation) These phenomenon was probably caused by insufficient bonding and lack of compatibility between PP-g-MA and MMT.
Evaluation of Ad-Hoc Information Retrieval Systems on Web Crawls with Redundant Documents Bachelor’s Thesis

In this thesis, we study the occurrence of duplicates among corpora that consist of crawled web documents and corresponding TREC Ad-Hoc tracks. We study the impact of the novelty principle on the evaluation of TREC Ad-Hoc tracks. The motivation to assess the impact is the discrepancy between the information need of search engine users and the methods used to evaluate information retrieval systems. The information need of a search engine user stays unfulﬁlled if equivalent documents are shown, information retrieval systems are even rewarded for retrieving duplicates. We evaluate an approach to mitigate the impact of duplicates on the evaluation.
Characteristics of Dental Health, Salivary Viscosity, pH and Flow Rate, Gum Hyperpigmentation, Malocclusion, Blood Pressure and Pulse Related to Body Mass Index of Vapers

An electronic cigarette (a Vape) is a battery-powered cigarette-shaped device containing a nicotine-based liquid that is vaporized and inhaled. It is used to stimulate the experience of smoking tobacco. As mentioned before, electronic cigarettes contain nicotine, which could damage blood vessels that could lead to higher blood pressure. The common effect of e-cigarette usage is dry mouth. The purpose of this study is to describe the DMF-T, stain, calculus, salivary viscosity, pH and flow rate, gum hyperpigmentation, malocclusion, blood pressure and pulse, body mass index of vapers. This study was an observational descriptive research that involved 27 males and 3 females vaper in Bandung. The samples were determined by using convenience technique. Information about body weight and height, blood pressure and pulse are compiled for physical examination data. Intra oral examination were performed on the samples to determine dental health, and oral condition. The collection of saliva was carried out by implementing the passive drooling method for ten minutes. The pH of saliva was measured using pH meter. The average salivary pH and flow rate were 6.82 and 0.42 ml/ minutes. Salivary viscosity was moderate (53.33%). The average blood pressure and pulse were 121/78 mmHg and 81. The average DMF-T was 7.06 (poor), the gum hyperpigmentation was mild (36.66%), calculus and stain were fair (53.33%). The most prevalent type of malocclusion was class 1 (83.33%). The BMI showed have an overweight (50%). This study concludes that vapers have poor DMF-T in average, the gum hyperpigmentation and the viscosity of saliva were mild, fair calculus and stain, pH and flow rate of salivary were normal , the pulse and the blood pressure were normal, the malocclusion mostly class 1, and the BMI shows overweight results in most of them. Experimental article (J Int Dent Med Res 2021; 14(1): 151-155)
Using Language Models to Detect Errors in Second-Language Learner Writing Bachelor Thesis

This thesis explores the use of different language modelling approaches to error detection in English Language Learner writing and investigates detection performance measures at different levels of detection granularity. We compare the error detection performance of word language models and a class-based extension to them at sentence and world level using language learner corpora and a corpus of automatically generated errors. Furthermore, we explore the issues that arise from ambiguities in both human and algorithmic error annotation and the impact they have on error detection results. We find that our class-based extensions to word language models improve error detection performance and that error detection quality at word level may require more advanced measures than the standard precision and recall as they seem to neither adequately assess human nor algorithm error detection quality. We conclude that the latter finding requires further investigation as the learner corpora we draw our results from are too small in size to produce fully conclusive results.
Reassessing the Constancy of End-to-End Internet Latency

—A paper by Zhang et al. in 2001, “On the Constancy of Internet Path Properties” [1] examined the constancy of end-to-end packet loss, latency, and throughput using a modest set of hosts deployed in the Internet. In the time since that work, the Internet has changed dramatically, including the ﬂattening of the autonomous system hierarchy and increased deployment of IPv6, among other developments. In this paper, we investigate the constancy of end-to-end Internet latency, revisiting ﬁndings of the earlier study. We use latency measurements from RIPE Atlas, choosing a set of 124 anchors with broad geographic distribution and drawn from 112 distinct autonomous systems. The earlier work of Zhang et al. relies on changepoint detection methods to identify mathematically constant time periods. We reimplement the two methods described in that earlier work and use them on the RIPE Atlas latency measurements. We also use a recently- published method (HMM-HDP) that has direct support in a RIPE Atlas API. Comparing the three changepoint detection methods, we ﬁnd that the two methods used in the earlier work may miss many changepoints caused by common level-shift events. Overall, we ﬁnd that the recently proposed HMM-HDP method performs substantially better. Moreover, we ﬁnd that delay spikes—as deﬁned by the earlier work—are an order of magnitude less prevalent than 20 years ago. We also ﬁnd that maximum change- free regions (CFRs) along paths that we observe in today’s Internet are substantially longer than what was observed in 2001, regardless of the changepoint detection method used. In particular, the 50 th percentile maximum CFR was on the order of 30 minutes in the earlier study, but our analysis reveals it to be on the order of 3 days or longer . Moreover, we ﬁnd that CFR durations appear to have steadily increased over the past 5 years.
A Holistic Analysis of Datacenter Operations: Resource Usage, Energy, and Workload Characterization - Extended Technical Report

Improving datacenter operations is vital for the digital society. We posit that doing so requires our community to shift, from operational aspects taken in isolation to holistic analysis of datacenter resources, energy, and workloads. In turn, this shift will require new analysis methods, and open-access, FAIR datasets with fine temporal and spatial granularity. We leverage in this work one of the (rare) public datasets providing fine-grained information on datacenter operations. Using it, we show strong evidence that fine-grained information reveals new operational aspects. We then propose a method for holistic analysis of datacenter operations, providing statistical characterization of node, energy, and workload aspects. We demonstrate the benefits of our holistic analysis method by applying it to the operations of a datacenter infrastructure with over 300 nodes. Our analysis reveals both generic and ML-specific aspects, and further details how the operational behavior of the datacenter changed during the 2020 COVID-19 pandemic. We make over 30 main observations, providing holistic insight into the long-term operation of a large-scale, public scientific infrastructure. We suggest such observations can help immediately with performance engineering tasks such as predicting future datacenter load, and also long-term with the design of datacenter infrastructure.
Using a Cross-Task Grid of Linear Probes to Interpret CNN Model Predictions On Retinal Images

We analyze a dataset of retinal images using linear probes: linear regression models trained on some"target"task, using embeddings from a deep convolutional (CNN) model trained on some"source"task as input. We use this method across all possible pairings of 93 tasks in the UK Biobank dataset of retinal images, leading to ~164k different models. We analyze the performance of these linear probes by source and target task and by layer depth. We observe that representations from the middle layers of the network are more generalizable. We find that some target tasks are easily predicted irrespective of the source task, and that some other target tasks are more accurately predicted from correlated source tasks than from embeddings trained on the same task.
AAVAE: Augmentation-Augmented Variational Autoencoders

Recent methods for self-supervised learning can be grouped into two paradigms: contrastive and non-contrastive approaches. Their success can largely be attributed to data augmentation pipelines which generate multiple views of a single input that preserve the underlying semantics. In this work, we introduce augmentation-augmented variational autoencoders (AAVAE), a third approach to self-supervised learning based on autoencoding. We derive AAVAE starting from the conventional variational autoencoder (VAE), by replacing the KL divergence regularization, which is agnostic to the input domain, with data augmentations that explicitly encourage the internal representations to encode domain-speciﬁc invariances and equivariances. We empirically evaluate the proposed AAVAE on image classiﬁcation, similar to how recent contrastive and non-contrastive learning algorithms have been evaluated. Our experiments conﬁrm the effectiveness of data augmentation as a replacement for KL divergence regularization. The AAVAE outperforms the VAE by 30% on CIFAR-10 and 40% on STL-10. The results for AAVAE are largely comparable to the state-of-the-art for self-supervised learning ** .
A general sample complexity analysis of vanilla policy gradient

We adapt recent tools developed for the analysis of Stochastic Gradient Descent (SGD) in non-convex optimization to obtain convergence and sample complexity guarantees for the vanilla policy gradient (PG). Our only assumptions are that the expected return is smooth w.r. t. the policy parameters, that its $H$-step truncated gradient is close to the exact gradient, and a certain ABC assumption. This assumption requires the second moment of the estimated gradient to be bounded by $A\geq 0$ times the suboptimality gap, $B \geq 0$ times the norm of the full batch gradient and an additive constant $C \geq 0$, or any combination of aforementioned. We show that the ABC assumption is more general than the commonly used assumptions on the policy space to prove convergence to a stationary point. We provide a single convergence theorem that recovers the $\widetilde{\mathcal{O}}(\epsilon^{-4})$ sample complexity of PG to a stationary point. Our results also affords greater flexibility in the choice of hyper parameters such as the step size and the batch size $m$, including the single trajectory case (i.e., $m=1$). When an additional relaxed weak gradient domination assumption is available, we establish a novel global optimum convergence theory of PG with $\widetilde{\mathcal{O}}(\epsilon^{-3})$ sample complexity. We then instantiate our theorems in different settings, where we both recover existing results and obtain improved sample complexity, e.g., $\widetilde{\mathcal{O}}(\epsilon^{-3})$ sample complexity for the convergence to the global optimum for Fisher-non-degenerated parametrized policies.