Miracle-dz/UniFAR-FTUs huggingface dataset:
Retrieval of tropospheric aerosol, NO2 and HCHO vertical profiles from MAX-DOAS observations over Thessaloniki, Greece

Abstract. In this study we focus on the retrieval of aerosol and trace gas vertical profiles from Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations for the first time over Thessaloniki, Greece. We use two independent inversion algorithms for the profile retrievals: The Mexican MAX-DOAS Fit (MMF) and the Mainz Profile Algorithm (MAPA). The former is based on the Optimal Estimation Method (OEM), while the latter follows a parameterization approach. We evaluate the performance of MMF and MAPA and we validate their retrieved products with ancillary data measured by other co-located reference instruments. We find an excellent agreement between the tropospheric column densities of NO2 retrieved by MMF and MAPA (Slope = 1.009, Pearson's correlation coefficient R = 0.982) and a good correlation for the case of HCHO (R = 0.927). For aerosols, we find better agreement for the aerosol optical depths (AODs) in the visible (i.e., at 477 nm), compared to the UV (360 nm) and we show that the agreement strongly depends on the O4 scaling factor that is used in the analysis. The trace gas differential slant column densities (dSCDs), simulated by the forward models, are also in good agreement, except for HCHO, where larger scatter is observed due to the increased spectral noise of the measurements in the UV. The agreement for NO2 and HCHO surface concentrations is similar to the comparison of the integrated columns with slightly decreased correlation coefficients. The AODs retrieved by the MAX-DOAS are validated by comparing them with AOD values measured by a CIMEL sun-photometer and a Brewer spectrophotometer. Four different flagging schemes were applied to the data in order to evaluate their performance. Qualitatively, a generally good agreement is observed for both wavelengths, but we find a systematic bias from the CIMEL and Brewer measurements, due to the limited sensitivity of the MAX-DOAS in retrieving information at higher altitudes, especially in the UV. An in-depth validation of the aerosol vertical profiles retrieved by the MAX-DOAS is not possible since only in very few cases the true aerosol profile is known during the period of study. However, we examine four cases, where the MAX-DOAS provided a generally good estimation of the shape of the profiles retrieved by a co-located multi-wavelength lidar system. The NO2 surface concentrations are validated against in situ observations and the comparison of both MMF and MAPA revealed good agreement with correlation coefficients of R = 0.78 and R = 0.73, respectively. Finally, the effect of the O4 scaling factor is investigated by intercomparing the integrated columns retrieved by the two algorithms and also by comparing the AODs derived by MAPA for different values of the scaling factor with AODs measured by the CIMEL and the Brewer.
Circadian Blood Pressure Variability in Hypertensive Patients with Coronary Heart Disease.

Introduction and objectives: Coronary heart disease is one of the complications of hypertension. Ambulatory blood pressure monitoring allows studying the different circadian patterns of blood pressure, but there is not enough evidence linking coronary heart disease with different circadian patterns. This research was carried out with the purpose of characterizing the circadian patterns of blood pressure in patients with essential hypertension and coronary heart disease. Methods: Descriptive and transversal research in 68 hypertensive patients with coronary heart disease who underwent ambulatory blood pressure monitoring. The different circadian patterns of blood pressure were related to the different forms of coronary heart disease and to the control of blood pressure. Results: In the sample, women (60.3%) predominated over men (39.7%). The ages were between 45 to 59 (63.3%) and those 60 and over (36.7%). 44.1% did not have their blood pressure under control, 45.6% were overweight and 38.2% were obese. The abnormal patterns were dipper 42.6%, non-dipper 41.2%, extreme dipper 7.4% and riser 8.8%. Morning surge was observed in 29 patients (42.6%), statistically significant in relation to the control of blood pressure (p = 0.033), but not with the different types of coronary heart disease studied. Conclusions: A statistically significant relationship was found between morning surge and control of blood pressure.
Toward Critical Reﬂection: Observing Practices of Noticing to Develop Interventions in Personal Informatics

Personal informatics technologies, such as Fitbit or mobile diary applications, are designed to help people reﬂect on their behavior and to promote positive behavior change. Although self-reﬂection is an indispensable component of the interactions with these systems, enabling critical reﬂection , as a means to empower people is often overlooked. We argue that this is because the notion of progress are the dominant narrative mechanisms in the designs of most personal informatics systems. How can we design PI interventions to cultivate the art of noticing [16] for enhancing critical thinking on and around self-tracking data and processes? In this position paper, we (1) make a case for incorporating interaction techniques that foster critical reﬂection in PI systems and (2) present an overview of how we are embodying this perspective in an ongoing research project in which we are conducting Participatory Design workshops to inform the design of personal informatics systems to mitigate or reduce the stresses that are a precursor to burnout. We speciﬁcally focus on how we are applying the concept of noticing as a means for scaffolding critical reﬂection in the design of this study.
Land use and land cover dynamics in a sustainable development project in the Transamazon highway region, Pará state, Brazil

The Transamazon highway region in the state of Pará is critical for Amazon deforestation due to socioeconomic transformations it has undergone. This work analyzes spatial and temporal changes in land use and its impacts on land cover in the Virola-Jatobá Sustainable Development Project (PDS) in Anapu-Pará, from 1984 to 2015. The study was mainly conducted through processing and analyzing Landsat scenes using the Spring platform. Very modest rates of deforestation were registered in the initial years analyzed. More substantial increments were reached seven years after the formation of the PDS, but nevertheless still at a low level. Consequently, forest is the predominant land cover in the PDS, followed by pasture, because agricultural areas are modest. In general, forested land presented high stability rates. Among other land use classes, pastures also presented significant stability, although the class weedy pasture showed some instability.
Research on variability in Statistical Education: a systematic review of literature

This article is a clipping of a master's dissertation, which aimed to investigate the reasoning about variability according to the perspective of Statistical Education. This work describes the Systematic Review of Literature performed in order to verify researches that present resources which help the process of teaching and learning of concepts involving the study of variability. The sources of literature used were national and international periodicals in Educational area in the last 10 years (2008-2018) published in Brazilian Portuguese, European Portuguese, Spanish and English. These journals were evaluated by the CAPES WebQualis system in the 20132016 quadrennium as A1, A2, B1, B2, and B3. The Systematic Review of Literature has shown that there is little research addressing the reasoning about variability in Basic Education, an important skill for the development of statistical literacy in student education.
Recurring Contingent Payment for Proofs of Retrievability

Fair exchange protocols let two mutually distrusted parties exchange digital data in a way that neither can cheat. At CCS 2017, Campanelli et al. proposed two blockchain-based protocols for the fair exchange of digital coins and a certain service, i.e., “proofs of retriev-ability” (PoR), that take place between a buyer and seller. In this work, we identify two serious issues of these schemes; namely, (1) a malicious client can waste the seller’s resources , and (2) real-time leakage of information to non-participants in the exchange. To rectify the issues, we propose “ recurring contingent PoR payment ” (RC-PoR-P). It lets the fair exchange reoccur while ensuring that the seller’s resources are not wasted, and the parties’ privacy is preserved. We implemented the RC-PoR-P. Our cost analysis indicates that the RC-PoR-P is eﬃcient. The RC-PoR-P is the ﬁrst of its kind that oﬀers all the above features.
Effects of Parental Acceptance-Rejection, Psychological Adjustment, Academic Self-Concept, and Learning Motivation on Adolescents’ Academic Achievement

The present study tested whether a set of variables in a hypothesized model derived from Interpersonal Acceptance-Rejection Theory influence academic achievement. More specifically, the study examined the extent to which perceived parental acceptance/rejection [2] contributed to academic performance of Portuguese teenage students. Additionally, the study tested the mediating role of certain variables, namely psychological adjustment [2], academic self-concept [38,39], and motivation for learning [7] Path analysis revealed that perceived parental acceptance/rejection influenced psychological adjustment; in sum, it supports the significance of the direct effect relationship established between perceived maternal and paternal acceptance/rejection and psychological adjustment/maladjustment of the children. Furthermore, students’ psychological adjustment influenced their academic self-concept and academic self-concept influenced both the motivation for learning and students’ academic performance.
DMSO_A_255842 1743..1752

1Department of Cardiology, Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, School of Medicine, South China University of Technology, Guangzhou 510080, People’s Republic of China; 2Department of Epidemiology, Centre for Global CardioMetabolic Health, Brown University, Providence, Rhode Island, NY, USA
HyperLogLog: Exponentially Bad in Adversarial Settings

Computing the count of distinct elements in large data sets is a common task but naive approaches are memory-expensive. The HyperLogLog (HLL) algorithm (Flajolet et al., 2007) estimates a data set's cardinality while using significantly less memory than a naive approach, at the cost of some accuracy. This trade-off makes the HLL algorithm very attractive for a wide range of applications such as database management and network monitoring, where an exact count may not be needed. The HLL algorithm and variants of it are implemented in systems such as Redis and Google Big Query. Recently, the HLL algorithm has started to be proposed for use in scenarios where the inputs may be adversarially generated, for example counting social network users or detection of network scanning attacks. This prompts an examination of the performance of the HLL algorithm in the face of adversarial inputs. We show that in such a setting, the HLL algorithm's estimate of cardinality can be exponentially bad: when an adversary has access to the internals of the HLL algorithm and has some flexibility in choosing what inputs will be recorded, it can manipulate the cardinality estimate to be exponentially smaller than the true cardinality. We study both the original HLL algorithm and a more modern version of it (Ertl, 2017) that is used in Redis. We present experimental results confirming our theoretical analysis. Finally, we consider attack prevention: we show how to modify HLL in a simple way that provably prevents cardinality estimate manipulation attacks.
Procrash: A Solution To Procrastination by Limiting Online Distractions using Optical Character Recognition

For this project, I decided to relieve the tension of procrastination that commonly happens in students and adults. To find a solution to this, I created a program that uses Google Cloud Vision API (Optical Character Recognition) to detect the distracting forms of media such as Twitter, YouTube, and Facebook, and counts the number of times the user visits these websites. After a certain number of visits, the program sends a notification to remind the user to stay focused. If the user ignores the notification message while staying on the unapproved website, the program forces the tab to close. This application was applied to a small user study where a qualitative evaluation of the approach was conducted. After collecting data for two weeks, it concluded that the program was able to effectively reduce and limit the uses of online distractions, allowing the user to manage their time more efficiently by staying off websites they should not visit.
The role of thermal annealing on the microstructures of (Ti, Fe)-alloyed Si thin-film anodes for high-performance Li-ion batteries

Here, we studied the effect of thermal annealing on the microstructure and cyclic stability of a (Ti, Fe)-alloyed Si thin-film fabricated by a simple sputtering deposition method for Li-ion battery (LIB) anodes. The anode samples annealed at different temperatures (300–600 °C) were subjected to microstructure analysis and LIB performance test. The (Ti, Fe)-alloyed Si thin-film anode delivered a high capacity of 1563 mA h g−1 for 100 cycles at 0.1 A g−1 with nearly 100% capacity retention. Post-mortem analysis using field emission scanning electron microscopy (FESEM) and transmission electron microscopy (TEM) disclosed the microstructural changes of the cycled anodes, revealing that (Ti, Fe) silicides served as a structural buffer against the large volume change of active Si during cycling for enhanced LIB performance.
BMAC and Adipose-Derived MSCs Treatment for Knee Osteoarthritis: A Systematic Review

Background: Knee osteoarthritis is the most common musculoskeletal progressive disorder that affects nearly 303 million people worldwide. This condition prevails in 10% males and 13% females among the elders above 60. Although there is conventional nonsurgical and surgical treatment available for knee osteoarthritis, there is a fascinating interest in bone marrow aspirate concentrate (BMAC) as well as adipose-derived mesenchymal stem cells (AD-MSC), including enzymatically treated stromal vascular fraction (SVF) and mechanically treated (microfat/nanofat) injections among physicians. Hence, this systematic review aims to determine the efficacy of BMAC and AD-MSCs (enzyme and mechanically treated) injections for knee osteoarthritis treatment. Methods: A systematic review was performed on the following data sources (PubMed, Scopus, Google Scholar, EMBASE, and Cochrane Library) published on March 31, 2021. The keywords or MeSH terms include 'Knee Osteoarthritis with 'Bone marrow aspirate concentrate' OR 'BMAC' or with 'Adipose-derived mesenchymal stem cells (AD-MSC)' or with 'Stromal vascular fraction' OR 'SVF' or 'Mechanically treated AD-MSC (mfat/nanofat)'. In addition, the retrieved articles were further reviewed to identify relevant research studies. Results: The authors reviewed and tabulated data based on the year of study, study type, therapy protocol, patient population, outcome measures, and interpretation. Among the 382 records screened, 43 studies (16 on BMAC and 27 on AD-MSCs) were included in the systematic review study. Among them, only 5 were randomized controlled trials. These selected studies demonstrated short-term positive outcomes such as improvement in knee pain and function with no adverse side effects. Moreover, researchers reported varied administration methods of BMAC or AD-MSC either as standalone or in combination with other conservative procedures such as PRP (Platelets Rich Plasma), HA (Hyaluronic acid), or surgery. Conclusions: BMAC and AD-MSC (enzymatically and mechanically treated) injections prove safer and more efficacious in patients with knee osteoarthritis for a shorter duration of 2 years. However, the available literature lacks high-quality studies with no varied clinical settings and long-term follow-up of more than two years.
Big Five Personality Detection Using Deep Convolutional Neural Networks

Personality is the most critical feature that tells us about an individual. It is the collection of the individual’s thoughts, opinions, emotions and more. Personality detection is an emerging field in research and Deep Learning models have only recently started being developed. There is a need for a larger dataset that is unbiased as the current dataset that is used is in the form of questionnaires that the individuals themselves answer, hence increasing the chance of unconscious bias. We have used the famous stream-of-consciousness essays collated by James Pennbaker and Laura King. We have used the Big Five Model often known as the five-factor model or OCEAN model. Document-level feature extraction has been performed using Google’s word2vec embeddings and Mairesse features. The processed data has been fed into a deep convolutional network and a binary classifier has been used to classify the presence or absence of the personality trait. Hold- out method has been used to evaluate the model, and the F1 score has been used as the performance metric.
Towards Biologically-Plausible Neuron Models and Firing Rates in High-Performance Deep Spiking Neural Networks

Spiking neural networks (SNNs) have the potential to reach the same accuracy level as their counterpart artificial neural networks (ANNs) through ANN-to-SNN conversion. However, this relies significantly on artificially modifying the voltage reset mechanism in the Integrate-and-Fire (IF) neuron model to support bias and batch normalization. This paper shows that our proposed MCR-Norm (minimum chain rule normalization) can enable the modeling of these two key elements by using the standard IF model. The SNNs built by the IF model can thus reach the same accuracy level as the SNNs built by the artificially modified IF model. While previous approaches tended to push deep SNNs towards very high firing rates, we found that the IF neuron is suitable to run in a low firing rate range. This is in line with biological observations and is also crucial to go beyond SNN simulation and apply it to real neuromorphic hardware. In addition, tuning the neural network inputs is dismissed in earlier work, but we claim that it is closely related to the success of parameter normalization inside the SNNs built by the standard IF model, and can be integrated naturally into MCR-Norm.
A Bph-Like Nitroarene Dioxygenase Catalyzes the Conversion of 3-Nitrotoluene to 3-Methylcatechol by <named-content content-type='genus-species'>Rhodococcus</named-content> sp. Strain ZWL3NT

All nitroarene dioxygenases reported so far originated from Nag-like naphthalene dioxygenase of Gram-negative strains, belonging to group III of aromatic ringhydroxylating oxygenases (RHOs). Gram-positive Rhodococcus sp. strain ZWL3NT utilizes 3-nitrotoluene (3NT) as the sole source of carbon, nitrogen, and energy for growth. It was also reported that 3NT degradation was constitutive and the intermediate was 3-methylcatechol. In this study, a gene cluster (bndA1A2A3A4) encoding a multicomponent dioxygenase, belonging to group IV of RHOs, was identified. Recombinant Rhodococcus imtechensis RKJ300 carrying bndA1A2A3A4 exhibited 3NT dioxygenase activity, converting 3NT into 3-methylcatechol exclusively, with nitrite release. The identity of the product 3-methylcatechol was confirmed using liquid chromatography-mass spectrometry. A time course of biotransformation showed that the 3NT consumption was almost equal to the 3-methylcatechol accumulation, indicating a stoichiometry conversion of 3NT to 3-methylcatechol. Unlike reported Nag-like dioxygenases transforming 3NT into 4-methylcatechol or both 4-methylcatechol and 3-methylcatechol, this Bph-like dioxygenase (dioxygenases homologous to the biphenyl dioxygenase from Rhodococcus sp. strain RHA1) converts 3NT to 3-methylcatechol without forming 4-methylcatechol. Furthermore, whole-cell biotransformation of strain RKJ300 with bndA1A2A3A4 and strain ZWL3NT exhibited the extended and same substrate specificity against a number of nitrobenzene or substituted nitrobenzenes, suggesting that BndA1A2A3A4 is likely the native form of 3NT dioxygenase in strain ZWL3NT. IMPORTANCE Nitroarenes are synthetic molecules widely used in the chemical industry. Microbial degradation of nitroarenes has attracted extensive attention, not only because this class of xenobiotic compounds is recalcitrant in the environment but also because the microbiologists working in this field are curious about the evolutionary origin and process of the nitroarene dioxygenases catalyzing the initial reaction in the catabolism. In contrast to previously reported nitroarene dioxygenases from Gram-negative strains, which originated from a Naglike naphthalene dioxygenase, the 3-nitrotoluene (3NT) dioxygenase in this study is from a Gram-positive strain and is an example of a Bph-like nitroarene dioxygenase. The preference of hydroxylation of this enzyme at the 2,3 positions of the benzene ring to produce 3-methylcatechol exclusively from 3NT is also a unique property among the studied nitroarene dioxygenases. These findings will enrich our understanding of the diversity and origin of nitroarene dioxygenase in
An application of persistent homology and the graph theory to linguistics: The case of Tifinagh and Phoenician scripts

Abstract As the origin of the Tifinagh script remains uncertain, this work aims at exploring its probable relatedness with the Phoenician script. Using tools from within topological data analysis and graph theory, the similarity between the two scripts is studied. The clustering of their letter shapes is performed based on the pairwise distances between their topological signatures. The ideas presented in this work can be extended to study the similarity between any two writing systems and as such can serve as the first step for linguists to determine the possibly related scripts before conducting further analysis.
Assessment of Persuasive Design Principles in E-Commerce Applications Based on Users’
Reviews

Different e-commerce applications aim to utilize different techniques and methods to enhance their usability and persuasive design experience. Persuasive design persuades users to use an application. Users also review the applications they use and provide comments based on their experiences. Therefore, this study aims to examine that to what extent the principles of the persuasive systems design (PSD) model have been implemented in a number of e-commerce applications in Saudi Arabia based on user reviews. Users’ reviews have been extracted using Appbot tool. Filtering and categorizing the collected users’ reviews took place before analyzing the data. The filtering and categorization were based on PSD model. The results demonstrate which principles of the PSD model are highly used in the selected applications based on users’ reviews. Tailoring, tunneling, and reductions principles have been reported to be positively utilized and implemented by the selected applications. Moreover, the findings report different users’ reviews on rewards and social supports principles.