Reviewerly/exHarmony huggingface dataset:
TERRA FORMA: Developing the observation platform of the Anthropocene&amp;#160;

&amp;lt;p&amp;gt;The Anthropocene, a new geological period when human actions are altering the habitability of the Earth for all forms of life, raises new challenges in terms of knowledge integration that fragmented approaches cannot overtake. Due to complex interactions within geo-eco-socio-systems (GESS), a &amp;amp;#8220;whole system&amp;amp;#8221; approach is required to answer societal concerns around soil capital, water resources, chemical pressure and biodiversity.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;To address these challenges, the TERRA FORMA project will design and test in-situ observation plateform coupling sensor viewpoints on human, biotic and abiotic dynamics. This project builds on pioneering and mature technological advances (optical sensors, 3D printing, IoT, AI) to design and probe a scalable network of smart sensors. We will develop a new generation of smart, connected, low-cost, low-impact and socially appropriated environmental sensors, adapted to field conditions, dedicated to capture the behavior, metabolism and trajectory of GESS emerging from states and fluxes of liquid, gas and solid matter and biota. These new technologies will contribute to shed light on &amp;amp;#8220;essential variables&amp;amp;#8221; for GESS and evaluate the descriptive and predictive potential of models over a wide range of contexts. TERRA FORMA gathers scientists, in an interdisciplinary effort at the crossroad of Earth, environmental, technological, computer and social sciences.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;In this presentation, we will show how instrumental developments (spectroscopy, lab on a chip, &amp;amp;#8230;) and methodological developments (biogeophysics, &amp;amp;#8230;) contributes to the construction of the observation plateform.&amp;lt;/p&amp;gt;
Quality Assessment of SARAH-3: The new regional satellite-based Surface Solar Radiation data set from the CM SAF

&amp;lt;p&amp;gt;The incoming surface solar radiation has been defined as an essential climate variable by GCOS. Long term monitoring of this part of the earth&amp;amp;#8217;s energy budget is required to gain insights on the state and variability of the climate system. In addition, climate data sets of surface solar radiation have received increased attention over the recent years as an important source of information for solar energy assessments, for crop modeling, and for the validation of climate and weather models.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) is deriving climate data records (CDRs) from geostationary and polar-orbiting satellite instruments. Within the CM SAF these CDRs are accompanied by operational data at a short time latency to be used for climate monitoring. All data from the CM SAF are freely available via www.cmsaf.eu.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Here we present the new edition of the SARAH climate data record of surface solar radiation from the CM SAF. The regional SARAH-3 climate data record (Surface Solar Radiation Dataset &amp;amp;#8211; Heliosat) is based on observations from the series of Meteosat satellites. SARAH-3 provides high-resolution data (temporal and spatial) of the surface solar radiation (global and direct) and the sunshine duration from 1983 to 2020 for the full view of the Meteosat satellite (i.e, Europe, Africa, parts of South America, and the Atlantic ocean). For the first time, this edition of the SARAH data record also provides user-oriented data of spectral radiation, namely the photosynthetic active radiation (PAR) and the daylight (DAL); UV radiation parameters are also available upon request.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;In this contribution we introduce the results from the comparison of the satellite-derived surface radiation with available surface measurements; the evaluation addresses the accuracy and the temporal stability of the satellite data using data from regional and global networks, e.g., BSRN, GEBA, ECA&amp;amp;D, CLIMAT, as well as, in the case of PAR and DAL, from individual stations. We present the improvements of the edition 3 of the SARAH data record compared to previous editions, in particular over snow-covered surfaces. The high accuracy and stability of these data records allow the assessment of the spatial and temporal variability and trends.&amp;lt;/p&amp;gt;
Knowledge hidden in plain sight &amp;#8211; Extending article metadata to support meta-analysis and knowledge accumulation

&amp;lt;p&amp;gt;The number of publications in the field of Hydrology (and in other geoscience fields) is rising at an almost exponential rate. In 2021 alone, more than 25 000 articles were listed in Web of Science on the topic of Water Resources. There is a tremendous wealth of knowledge and data hidden in these articles, which capture our experience in studying places, datasets or models. Hidden, because we currently do not possess (or at least, do not use) the necessary tools to access this knowledge resource in an effective manner. It is increasingly difficult for an individual researcher to build on existing knowledge. New ways to approach this problem are urgently needed. &amp;amp;#160;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;One approach to address this problem of literature explosion might be to extend article metadata to include geoscience-specific information that can facilitate knowledge search, accumulation and synthesis in a domain specific manner. Imagine one could easily find all studies performed in a specific location/ climate/ land use thus allowing a full picture of the hydrology of that region/ climate/ land use. It is important for any geoscience, a field strongly depending on experience, that knowledge is not &amp;amp;#8220;forgotten&amp;amp;#8221; in a mountain of publications but can easily be integrated into larger understanding.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;So what meta-information would be most useful in knowledge synthesis? Study location? Spatial and/or temporal scale? Models used? Here, we would like to (re-)start the discussion on geoscience-relevant metadata enrichment. With the recent advancement in text mining scholarly literature, it is critical to have this discussion now or fall behind.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The Geosciences strongly depend on experiences we gain, which we largely share through the articles we publish. Knowledge accumulation in our science is hindered if this exchange of knowledge becomes ineffective. We are afraid it already has!&amp;lt;/p&amp;gt;
Social Media and its Impact on Indian Youth: A Sociological Study

Social media has become a very important part of life for many young generations in today’s world. There are many young people who keep on engaging themselves with social media without even caring to think about what would be the impact of social media on youth. Social media refers to all applications and websites or blogs that enable people around the globe to interconnect via the internet, chat, and share content, video call among much other functionality it offers to its users. For a person to be a member of any social media, he or she has to first signup and then sign in to access content and be able to share and chat with other users of that social media platform. Some of the common and widely used social media platforms/websites include Facebook, Twitter, WhatsApp, YouTube, Hike, Messenger, Signal, Telegram, Snap chat etc which become more popular and becomes the part of life.
Multi-strategy English Translation System Based on DTW Algorithm

With the continuous development of computer technology and the continuous in-depth study of English translation theory, an English Translation System (ETS) based on the combination of translation and computer has emerged. ETS can automatically perform English-Chinese translation through search. As a commonly used pattern recognition method, DTW algorithm is gradually applied to the field of English information retrieval and translation. Based on the advantages of the current translation methods, this paper designs a multi-strategy ETS based on the DTW algorithm. Based on the traditional DTW algorithm, this paper proposes a two-dimensional dynamic time warping algorithm (2D-DTW), which extends the distance-calculated samples from a spatial one-dimensional sequence to a spatial two-dimensional matrix. This article puts forward the goal of multi-strategy ETS, and plans the composition of the entire ETS realization. Finally, a translation quality evaluation experiment was carried out. The experimental results showed that the average BLEU of the system was 0.6681; the averages of Rec and Pre were 91.39% and 91.13%, respectively. This shows that ETS has better phrase recognition performance. While ensuring that the phrase translation is obtained, it also guarantees the quality of the translation.
Quantum-measurement-enhanced error correction for quantum receivers

We investigate how accuracy information available in quantum measurement can be used to enhance error correction codes using experimentally obtained state identification data. We test conventional and novel error correction protocols and find a significant reduction of errors in user data transmission. The error reduction and the energy use of error correcting codes compare favorably to that of quantum receivers without error correction. Ordinarily, quantum receivers identify the maximally likely input state out of M possible states. We take advantage of the full vector of Bayesian probabilities available for each act of measurement that supplements the conventional state discrimination.
Mining an English-Chinese parallel Dataset of Financial News

Parallel text datasets are a valuable for educational purposes, machine translation, and cross-language information retrieval, but few are domain-oriented. We have created a Chinese–English parallel dataset in the domain of finance technology, using the <em>Financial Times</em> website, from which we grabbed 60,473 news items from between 2007 and 2021. This dataset is a bilingual Chinese–English parallel dataset of news in the domain of finance. It is open access in its original state without transformation, and has been made not for machine translation as has been used, but for intelligent mining, in which we conducted many experiments using up-to-date text mining techniques: clustering (topic modeling, community detection, <em>k</em>-means), topic prediction (naive Bayes, SVM, LSTM, Bert), and pattern discovery (dictionary based, time series). We present the usage of these techniques as a framework for other studies, not only as an application but with an interpretation.
PWSNAS: Powering Weight Sharing NAS With General Search Space Shrinking Framework

Neural architecture search (NAS) depends heavily on an efficient and accurate performance estimator. To speed up the evaluation process, recent advances, like differentiable architecture search (DARTS) and One-Shot approaches, instead of training every model from scratch, train a weight-sharing super-network to reuse parameters among different candidates, in which all child models can be efficiently evaluated. Though these methods significantly boost search efficiency, they inherently suffer from inaccurate and unstable performance estimation. To this end, we propose a general and effective framework for powering weight-sharing NAS, namely, PWSNAS, by shrinking search space automatically, i.e., candidate operators will be discarded if they are less important. With the strategy, our approach can provide a promising search space of a smaller size by progressively simplifying the original search space, which can reduce difficulties for existing NAS methods to find superior architectures. In particular, we present two strategies to guide the shrinking process: detect redundant operators with a new angle-based metric and decrease the degree of weight sharing of a super-network by increasing parameters, which differentiates PWSNAS from existing shrinking methods. Comprehensive analysis experiments on NASBench-201 verify the superiority of our proposed metric over existing accuracy-based and magnitude-based metrics. PWSNAS can easily apply to the state-of-the-art NAS methods, e.g., single path one-shot neural architecture search (SPOS), FairNAS, ProxylessNAS, DARTS, and progressive DARTS (PDARTS). We evaluate PWSNAS and demonstrate consistent performance gains over baseline methods.
The life cycle of a foreland basin: Insights from the Alborz Mountains (Arabia-Eurasia collision zone)

&amp;lt;p&amp;gt;Flexural foreland basins represent first-order geological archives that preserve the record of orogenic processes. These detrital archives provide critical insights into tectonic, climatic and environmental evolution as well as variations in source lithologies, isostasy, eustasy and dynamic lithospheric processes. In this study, we combine published geological data (e.g., facies analysis, magnetostratigraphy, sediment provenance, and carbon and oxygen isotopic records from authigenic minerals) with new zircon U-Pb geochronologic and zircon and apatite (U-Th)/He thermochronologic data from the southern foreland basin of the Alborz Mountains in northern Iran. This orogen, resulting from the Neogene Arabia-Eurasia collision zone, experienced topographic growth and exhumation since ~20 Ma and foreland deposition of a thick pile (&amp;gt; 7 km) of continental red beds.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The foreland-basin fill consists of three major systematic coarsening-upward cycles that each exhibits fine-grained siliciclastic strata at the base with high sediment accumulation rates and younger detrital zircon U-Pb and (U-Th)/He ages (mostly Eocene), followed by coarse-grained sedimentary strata with decreased sediment accumulation rates and older detrital zircon U-Pb and (U-Th)/He ages (&amp;gt; 100 Ma).&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The base of each cycle is interpreted as a pulse of enhanced subsidence driven by tectonic loading associated with the growth of new thrust sheets experiencing erosional unroofing. The top of each cycle is interpreted to reflect wanning tectonic subsidence in response to local intra-basinal uplift (cycle 1) as documented by the sedimentary stratal pattern; uplift of the proximal foreland (cycle 3) as suggested by the age distribution of the detrital zircon U-Pb ages, the shift from fluvial to alluvial fan deposits and recycled apatite (U-Th)/He ages from the deepest exhumed red beds. Within these systematic trends, the top of cycle 2 represents an exception as it appears to record an enhanced phase of sediment supply triggered by wetter climatic conditions as documented by oxygen isotope data from paleosols samples.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Overall, our multidisciplinary approach provides a comprehensive overview of the history of a collisional foreland basin, from the forcing mechanisms controlling its stratigraphic architecture and sedimentary composition to its final incorporation into the orogenic wedge associated with basin uplift and erosion.&amp;lt;/p&amp;gt;
Moderation of Leadership Style: Management Accounting Information Systems and Management Control Systems on Managerial Performance

This study aims to determine and analyze the effect of management accounting information systems and control systems on managerial performance with leadership style as a moderating variable at PT. Pa'baeng-baeng branch pawnshop. The data collection technique used in this research is the survey technique by distributing questionnaires and studying documentation. The population and samples used in this study were 30 respondents. The data analysis technique used is multiple linear regression analysis were processed using assistance Software SPSS26. This study indicates that the management accounting information system and control system have a positive and significant effect on managerial performance at PT. Pa'baeng-baeng branch pawnshop. These results suggest that the leadership style variable only weakens the influence of the management accounting information system and management control system on organizational performance at PT. Pa'baeng-baeng branch pawnshop. The company is expected to maintain and carry out its functions systematically so that the management accounting information system and management control system can run effectively. The company is also likely to continue improving managerial performance with variables other than the management accounting information system and control systems, such as performance measurement system variables, information technology, etc. For further researchers, this research is expected to be used as a reference to be used as material for research development by using other variables outside of this research and using more and more varied research indicators and adapted to the situation and condition of the object of study.
RESECAN: citizen-driven seismology on an active volcano (Cumbre Vieja, La Palma Island, Canaries)

&amp;lt;p&amp;gt;During the last decades, countless seismic sensors have been deployed throughout the planet by different countries and institutions. In recent years, it has been possible to manufacture low-cost MEMS accelerometers thanks to nanotechnology and large-scale development. These devices can be easily configured and accurately synchronized by GPS. Customizable microcontrollers like Arduino or RaspBerryPI can be used to develop low-cost seismic stations capable of local data storage and real-time data transfer. Such stations have a sufficient signal quality to be used for complementing conventional seismic networks.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;In recent years Instituto Volcanol&amp;amp;#243;gico de Canarias (INVOLCAN) has developed a proprietary low-cost seismic station to implement the Canary Islands School Seismic Network (Red S&amp;amp;#237;smica Escolar Canaria - RESECAN) with multiple objectives:&amp;lt;/p&amp;gt;&amp;lt;ul&amp;gt;&amp;lt;li&amp;gt;supporting the teaching of geosciences.&amp;lt;/li&amp;gt; &amp;lt;li&amp;gt;promoting the scientific vocation.&amp;lt;/li&amp;gt; &amp;lt;li&amp;gt;strengthening the resilience of the local communities by improving awareness toward volcanism and the associated hazards.&amp;lt;/li&amp;gt; &amp;lt;li&amp;gt;Densifying the existing seismic networks.&amp;lt;/li&amp;gt; &amp;lt;/ul&amp;gt;&amp;lt;p&amp;gt;On Sept. 19&amp;lt;sup&amp;gt;th&amp;lt;/sup&amp;gt; 2021, a volcanic eruption started on the Cumbre Vieja volcano in La Palma. The eruption was proceeded and accompanied by thousands of earthquakes, many of them felt with intensities up to V MCS. Exploiting the attention drawn by the eruption, INVOLCAN started the deployment of low-cost seismic stations in La Palma in educational centres. In this preliminary phase, we selected five educational centres on the island.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The project's objective is to create and distribute low-cost stations in various educational institutions in La Palma and later on the whole Canary Islands Archipelago, supplementing them with educational material on the topics of seismology and volcanology. Each school will be able to access the data of its station, as well as those collected by other centres, being able to locate some of the recorded earthquakes. The data recorded by RESECAN will also be integrated into the broadband seismic network operated by INVOLCAN (Red S&amp;amp;#237;smica Canaria, C7). RESECAN will be an instrument of scientific utility capable of contributing effectively to the volcano monitoring of the Canary Islands, reinforcing its resilience with respect to future volcanic emergencies.&amp;lt;/p&amp;gt;
Real Time Face Mask Detection-A Survey

After the breakout of the worldwide pandemic COVID-19, there arises a severe need of protection mechanisms, face mask being the primary one. According to the World Health Organization, the corona virusCOVID-19 pandemic is causing a global health epidemic, and the most successful safety measure is wearing a face mask in public places. Convolutional Neural Networks (CNNs) have developed themselves as a dominant class of image recognition models. The aim of this research is to examine and test machine learning capabilities for detecting and recognize face masks worn by people in any given video or picture or in real time. This project develops a real-time, GUI-based automatic Face detection and recognition system. It can be used as an entry management device by registering an organization’s employees or students with their faces, and then recognizing individuals when they approach or leave the premises by recording their photographs with faces.The proposed methodology makes uses of Principal Component Analysis (PCA) and HAAR Cascade Algorithm. Based on the performance and accuracy of our model, the result of the binary classifier will be indicated showing a green rectangle superimposed around the section of the face indicating that the person at the camera is wearing a mask, or a red rectangle indicating that the person on camera is not wearing a mask along with face identification of the person. Face detection and face recognition are very important technologies these days, furthermore we noticed that they got have a variety of uses such as cellphones, army uses, and some high risk information offices. We decided to make a device that detects and recognize the face as a student attendance system and can be a substitute for the regular paper attendance system and finger print attendance system. The main function in our project is going to be done using LabVIEW because, LabVIEW is a very helpful programming tool in regards of facial uses and very helpful in other uses. Our project is based on a main program in LabVIEW that detects and recognize faces with giving scores and parameters, furthermore the subsystems are an Excel sheet that is integrated with the program, and a messaging device that is for either a message for absent students or to the student’s parent.
Smart Contract Solutions for Transactional Inefficiency in Medical Device Procurement

The annual ConV2X is a leading international health tech symposium driving real world evidence, strategy, research, operations and trends to create a blueprint for a new digital health era. The 2021 symposium&nbsp; fetured a scientific program of academic/research presentations in addition to business and industry talks. The research track&nbsp; focused on exploring and sharing developments in blockchain and emerging technologies in health and clinical medicine. Submissions were based on original research, conceptual frameworks, proposed applications, position papers, case studies, and real-world implementation. Selection was based on a peer-review process. Faculty, students, and industry researchers were encouraged to submit abstracts to present&nbsp; ideas before an informed and knowledgeable audience of industry leaders, policy makers, funders, and researchers. This presentation was selected by the scientific reveiw committee. Submission Review Committee Dave Kochalko, CEO of ARTiFACTS Anjum Khurshid, UT Austin Carlos Caldas, UT Engineering Gil Alterovitz, Harvard Medical School Kayo Fujimoto, UT Health Houston Lei Zhang, University of Glasglow Sean Manion, CSciO of ConsenSys Health Vijayakuman Varadarajan, University of South Wales Vikram Dhillon, Wayne State University Yuichi Ikeda, Kyoto University