Miracle-dz/UniFAR-FTUs huggingface dataset:
Conversational Hate-Speech detection in Code-Mixed Hindi-English Tweets

Hate speech in social media has increased due to the increased use of online forums for sharing the opinion among the people. Especially, people prefer expressing the views in their native language while posting such objectionable contents in many social media platforms. It is a challenging task to have an automated system to identify such hate and offensive tweets in many regional languages due to the rich linguistics nature. Recently, this problem has become too complicated, due to the use of multi-lingual and code-mixed tweets. The code-mixed data includes the mixing of two languages on the granular level. A word that might not be a part of either language may be found in the data. To address the above challenges in Hindi-English tweets, we propose an efficient method by combining the IndicBERT with an effective ensemble based method. We have applied different methodologies to find a way to accurately classify whether the given tweet is considered to be Hate Speech or Not in code-mixed Hinglish dataset. Three different models namely, IndicBERT, XLM Roberta and Masked LM were used to embed the tweet data. Then various classification methods such as Logistic Regression, Support Vector Machine, Ensembling and Neural Networks based method were applied to perform classification. From extensive experiments on the data set, embedding the code-mixed data with IndicBERT and Ensembling was found to be the best method, which resulted in an macro F1-score of 62.53%. This work was submitted to the shared task of the HASOC 2021 [1] [2] Hate Speech and Offensive Content Identification in English and Indo-Aryan Languages Competition by team TNLP.
AcX: System, Techniques, and Experiments for Acronym Expansion

In this information-accumulating world, each of us must learn continuously. To participate in a new field, or even a sub-field, one must be aware of the terminology including the acronyms that specialists know so well, but newcomers do not. Building on state-of-the art acronym tools, our end-to-end acronym expander system called AcX takes a document, identifies its acronyms, and suggests expansions that are either found in the document or appropriate given the subject matter of the document. As far as we know, AcX is the first open source and extensible system for acronym expansion that allows mixing and matching of different inference modules. As of now, AcX works for English, French, and Portuguese with other languages in progress. This paper describes the design and implementation of AcX, proposes three new acronym expansion benchmarks , compares state-of-the-art techniques on them, and proposes ensemble techniques that improve on any single technique. Finally, the paper evaluates the performance of AcX and related work MadDog system in end-to-end experiments on a new human-annotated dataset of Wikipedia documents. Our experiments show that AcX outperforms MadDog but that human performance is still substantially better than the best automated approaches. Thus, achieving Acronym Expansion at a human level is still a rich and open challenge.
Deep learning for stochastic precipitation generation – deep SPG v1.0

Abstract. We present a deep-neural-network-based single-site stochastic precipitation generator (SPG), capable of producing realistic time series of daily and hourly precipitation. The neural network outputs a wet-day probability and precipitation distributions in the form of a mixture model. The SPG was tested in four different locations in New Zealand, and we found it accurately reproduced the precipitation depth, the autocorrelations seen in the original data, the observed dry-spell lengths, and the seasonality in precipitation. We present two versions of the hourly and daily SPGs: (i) a stationary version of the SPG that assumes that the statistics of the precipitation are time independent and (ii) a non-stationary version that captures the secular drift in precipitation statistics resulting from climate change. The latter was developed to be applicable to climate change impact studies, especially studies reliant on SPG projections of future precipitation. We highlight many of the pitfalls associated with the training of a non-stationary SPG on observations alone and offer an alternative method that replicates the secular drift in precipitation seen in a large-ensemble regional climate model. The SPG runs several orders of magnitude faster than a typical regional climate model and permits the generation of very large ensembles of realistic precipitation time series under many climate change scenarios. These ensembles will also contain many extreme events not seen in the historical record.
Accurately calibrated XRF-CS record of Ti/Al reveals Early Pleistocene aridity/humidity variability over North Africa and its close relationship to low-latitude insolation

In eastern Mediterranean Sea sediments, the titanium to aluminum ratio (Ti/Al) captures relative variability in eolian to riverine derived material, and predominantly integrates climate signals over the Saharan and Sahel regions. Long Ti/Al time series can, therefore, provide valuable records of North African humidity/aridity changes. X-ray fluorescence core scanning (XRF-CS) can generate near-continuous Ti/Al records with relatively modest effort and in an acceptable amount of 20 time, provided that accurate Ti/Al values are acquired. Calibration of the raw XRF-CS data to those of established analytical methods is an important pathway to obtain this required accuracy. We assess how to obtain reliable XRF-CS Ti/Al calibration by using different sets of calibration reference samples for a long sediment record from ODP Site 967 (eastern Mediterranean). The accuracy of reference concentrations and the number of reference samples are important components for reliable calibration. The acquired continuous Ti/Al record allows detailed time-series analysis over the past 3 Ma. A near- 25 direct control of low-latitude insolation on the timing and amplitude of North African aridity/humidity is observed from 3 to ~1.2 Ma. It is evident from our Ti/Al record that the most arid North African intervals (i.e., with longest period and highest amplitude) occur after the mid-Pleistocene transition (MPT; ~1.2-0.7 Ma). Concurrently, correlation between North African aridity/humidity (Ti/Al) and higher latitude climate signals (ice-volume variability) increases around the MPT. These findings support the growing consensus that African climate became more sensitive to remote high-latitude climate when a 30 threshold ice volume was reached during the MPT.
Design and Implementation of a Multisensor Coaxial Monitoring System With Correction Strategies for Selective Laser Melting of a Maraging Steel

Development of monitoring devices becomes crucially important in selective laser melting due to the high process complexity and the high value of the products obtained. This work discusses the design of a coaxial monitoring system for SLM using multiple sensors. In particular, an optical model is developed for the propagation of the process emission from the workpiece to the monitoring module. The model is used to determine the field of view around the monitored zone. The lens arrangements and the optical filters are chosen according to the model results. They were implemented to construct a monitoring module consisting of two CCD cameras viewing visible and near-infrared wavelength bands, as well as a photodiode viewing the back-reflected laser emission, all integrated in a coaxial configuration. The system 1 Corresponding author information can be added as a footnote. 2 functionality is tested with a prototype SLM machine during the processing of 18Ni300 maraging steel, a material known to be prone to porosity. In particular, different remelting strategies were employed as possible correction strategies to reduce porosity. The signals were interpreted as being indicators of the change in absorptivity of the laser light by the powder bed, of the plasma and molten pool, as well as of the evolution of the temperature field.
FAST COMMUNICATION HIERARCHICAL LOW-RANK STRUCTURE OF PARAMETERIZED DISTRIBUTIONS∗

This note shows that the matrix forms of several one-parameter distribution families satisfy a hierarchical low-rank structure. Such families of distributions include binomial, Poisson, and χ 2 distributions. The proof is based on a uniform relative bound of a related divergence function. Numerical results are provided to conﬁrm the theoretical ﬁndings.
Negative Damping Mechanism Analysis of Power System Stabilizer Based on Damping Torque

Power system stabilizer plays an important role in suppressing the low frequency oscillations, but a PSS with poorly tuned parameters may produce negative damping and aggravate the system oscillation. The purpose of this paper is to study the mechanism of damping of a PSS in multi machine system and to analyze whether the PSS has produced negative damping. This paper adopts Park model for analysis. According to the concepts of complex frequency and generalized phasor, the correlation between the damping torque phasor and the real part of the complex eigenvalue is studied. With the auxiliary of Park equivalent circuits, the damping torque provided by the excitation system is separated from the electrical torque phasor. Then, the damping torque coefficient of the PSS is defined as an indicator of the damp effect of the stabilizer. Finally, the simulation results of single machine infinite bus system and 4-machine system demonstrate the validation of the proposed method for evaluating the damping effect of PSS on the system.
The Stability of Fiber Spectrographs in the Faint-source Regime

The use of optical fibers in astronomical instrumentation offers high-multiplex and light-gathering flexibility. However, with most previous fiber spectrographs optimized for large fields of view on modest-aperture telescopes, the performance of fibers in the context of faint targets on large telescopes remains largely untested. In this paper, we evaluate aspects of fiber stability, especially as they apply in the context of precision sky subtraction of faint sources at modest spectral resolution (R ∼ 3000). After introducing a framework for describing potential systematic errors, we use publicly available data from existing instruments, including instrumentation used by the fourth-generation Sloan Digital Sky Survey’s MaNGA project (MaNGA: Mapping Nearby Galaxies at Apache Point Observatory) and the Very Large Telescope’s FLAMES: Fiber Large Array Multi Element Spectrograph. We isolate sources of fiber systematics and estimate the observed amplitude of persistent residuals as well as stochastic noise contributions resulting from changing fiber stresses. Comparing these levels against their impact on various sky subtraction schemes demonstrates that 0.1% precision sky subtraction with fiber instruments is possible. As a demonstration, we show that the MaNGA instrument can deliver 0.2% residuals on bright near-IR sky lines with nonlocal sky subtraction, if pseudo-slit limitations are addressed by allocating 50% of its fibers to sky. We further highlight recently published deep exposures that achieved a 1σ background level of 27.6 AB per square arc second, equivalent to a precision of 0.2% of the sky background continuum.
Design and Implementation of AGV Calling System Based on Android

This paper designs and implements an AGV calling application based on Android. In the actual working environment, administrators need to call automatic guided vehicles to perform tasks and monitor them anytime and anywhere, so the AGV calling application based on Android came into being. Five business function modules of the system are realized: calling module, map monitoring module, task list module, node configuration module and communication configuration module. The application software is developed using Android Studio development tool, with the use of Vue framework and front-end HTML5+CSS+JavaScript technology to achieve interface rendering. TCP and HTTP protocols are used in the connection between the system and the central control system.
A Water Gauge Scale Capturing Method in Tidal Well Based on Image Recognition

Tide level observation data is an important technical support data for the delimitation of warning tide level and disaster prevention. The performance of the tidal well is tested by regularly checking the external water gauge, so as to maintain the tidal follow-up and wave dissipation of the tidal well. The check of water gauge inside and outside the well shall be carried out once a month. It is time-consuming and labour consuming. The paper proposes a real-time borehole water gauge capturing algorithm in tidal well based on image recognition. Experiments have proved that the method can recognize the water gauge scale effectively. The comparison experiments with the other standard measurement method are done. It can be seen from the comparison chart that the error between the water gauge scale and the tide level value is ± 1cm, which meets the national standard.
The Method for Automatic Adjustment of AGV’s PID Based on Deep Reinforcement Learning

This paper proposes a method for automatic adjustment of PID(Proportion Integration Differentiation) based on deep reinforcement learning in order to solve the problem of smooth movement of AGV(Automated Guided Vehicle). First, based on reinforcement learning, the problem of AGV smooth operation is transformed into the solution of PID adjustment operation sequence. The action value model is constructed using the Deep Q-Learning Network(DQN) algorithm. Then, take the AGV adjustment PID as the research object. The goal is to achieve smooth movement of AGV. The specific design of AGV automatic PID adjustment method based on deep reinforcement learning is introduced. Finally, the simulation data is used to train the AGV action value network model. The method is validated in the ROS(Robot Operating System) simulation environment. Then compare with the actual environment. The results show that the automatic adjustment method of AGV’s PID based on deep reinforcement learning can adjust PID to the optimum without manual work. It can make AGV run smoothly. The feasibility and effectiveness of the method are illustrated and the problem of automatic PID determination in AGV movement control is solved.
What do healthcare workers know about sudden infant death syndrome?: the results of the Italian campaign ‘GenitoriPiù’

Summary. The paper analyses the data resulting from the Italian campaign for newborns’ parents, ‘GenitoriPiù’, and focuses on the assessment of healthcare workers’ knowledge about sudden infant death syndrome. Considering two different response sets (dichotomous and polytomous), we used a Rasch model and a logistic quantile regression to analyse which demographic and professional backgrounds influenced the degree of knowledge of this topic. Significant differences between regions are evident, and the effect of training initiatives is proven as a way of rectifying these differences. With regard to professional background, the best‐prepared healthcare workers are paediatricians and healthcare workers working in birth centres and family planning clinics.
Melanonychia and use of nail biopsy to screen for subungual melanoma in a large ethnically diverse pediatric cohort: A cross-sectional study

Background There are no widely accepted pediatric guidelines on who should undergo biopsy of the nail apparatus to screen for subungual melanoma (SUM). Reported cases of pre-adolescent children diagnosed with SUM presenting as melanonychia remain controversial. Further, observed age differences in the incidence of acral lentiginous melanoma are complicated by reported ethnic differences in adult prevalence and survival rates. Methods We conducted a retrospective chart review of Rady Children's Hospital San Diego, a tertiary hospital system, with over 2 million patients in its electronic health records to identify patients diagnosed with melanonychia younger than 12 years and biopsies in these children, between January 1, 2010, and July 31, 2021. Results There were 623,805 patients younger than 12 years of age seen in the outpatient setting. Average age was 7.2 years for melanonychia diagnosis, and 5.1 years for those biopsied. Nail apparatus biopsies were performed in 22 different individuals and involved the hand 17/22 (77%) and the foot 5/22 (23%). The presence of Hutchinson's sign was documented in 9/22 (41%) patients. Males were diagnosed with melanonychia and underwent biopsy more often than females. Many of the biopsies were performed in Hispanic/Latino 11/22 (50%) and Asian/Pacific Islander 3/22 (14%) patients. Discussion Regardless of reported ethnicity, biopsy of nail apparatus is highly unlikely to uncover invasive ALM in children younger than 12 years. Prospective studies are needed to understand how incidence of melanonychia, age, gender, and ethnicity/race influence parental and clinicians' perceptions of melanoma risk.
Improvement in balance from diagnosis to return-to-play initiation following a sport-related concussion: BESS scores vs center-of-pressure measures

ABSTRACT Objective Accurate assessment of balance recovery throughout treatment of a sport-related concussion is imperative. This study examined differences in balance from diagnosis to return-to-play initiation in adolescent patients post-concussion. Second, this study investigated the extent to which the Balance Error Scoring System (BESS) correlated with center-of-pressure (COP) measures. Methods Forty participants performed the BESS while standing on a force platform such that COP data were obtained simultaneously. Spatial and velocity COP-based measures were computed for the double-stance conditions. Results BESS scores and COP-based measures indicated improved balance performance between visits. Specifically, 62.5/65.0% of participants exhibited improved firm/foam BESS final scores, respectively, and 56.4–71.8% exhibited improved COP-based measures. However, once normative ranges were referenced to identify maintained performance, the percentage of participants who substantially improved differed from initial findings (BESS: 2.5/7.5%, COP: 48.7–69.2%). Additionally, positive correlations between balance measures were primarily found at diagnosis (r=0.33–0.53), while only three correlations were maintained at return-to-play initiation (r=0.34–0.39). Conclusions BESS scores successfully identified poor balance performance at diagnosis when symptoms were most pronounced, but failed to accurately depict performance once balance impairment, indicated by COP-based measures, became less apparent. Further work is needed to implement more advanced balance assessments into clinical environments.
Quasi-Z-source network DC–DC converter with different techniques to achieve a high voltage gain

A new step-up DC–DC converter is presented, based on quasi-Z-source network intended for photovoltaic applications. The proposed converter combines voltage multiplier cells to the secondary winding of the coupled inductor which is included in the second inductor of the quasi-Z-source network. In the output of the quasi-Z-source network, a switched capacitor is connected. This converter shows attractive characteristics such as high voltage gain, low voltage stresses on their components, continuous input current. A detailed description of the operating principles of the proposed converter is presented and experimental results on a 250 W prototype show that a high efficiency above 91.4% can be achieved.
Atractylodes-I overcomes the oxidative stress-induced colonic mucosal epithelial cells dysfunction to prevent irritable bowel syndrome via modulating the miR-34a-5p-LDHA signaling pathway.

BACKGROUND Irritable bowel syndrome (IBS) is a known brain-gut disorder. Currently, the molecular and cellular mechanisms of IBS remain unclear. Atractylenolide-I (ATL-I) is majorly bioactive component extracted from Rhizoma Atractylodes Macrocephalae. METHODS Studies have revealed that ATL-I functioned as an anti-tumor drug in various cancers. However, the effects and molecular mechanisms of ATL-I on the pathological processes of colonic mucosal epithelial cells (CMECs) during IBS remain unclear. This study reports ATL-I effectively alleviated the oxidative stress-induced colonic mucosal epithelial cell dysfunction. In colonic mucosal tissues from IBS patients, we detected upregulated miR-34a-5p and suppressed glucose metabolism enzymes expressions. Under H2O2 treatment which mimics in vitro oxidative stress, miR-34a-5p was induced and glucose metabolism was inhibited in colon mucosal epithelial cell line, NCM460. Meanwhile, ATL-I treatment effectively overcame the oxidative stress-induced miR-34a-5p expression and glucose metabolism in NCM460 cells. RESULT By bioinformatics analysis, Western blot and luciferase assay, we illustrated that miR-34a-5p directly targeted the 3'UTR region of glucose metabolism key enzyme, lactate dehydrogenase-A (LDHA) in colonic mucosal epithelial cells. Rescue experiments validated that miR-34a-5p inhibited glucose metabolism through targeting LDHA. Finally, we demonstrated that ATL-I treatment reversed the miR-34a-5p-inhibited glucose metabolism and -exacerbated colonic mucosal epithelial cell dysfunction under oxidative stress through modulating the miR-34a-5p-LDHA pathway. CONCLUSION Summarily, our study reports the roles and mechanisms of ATL-I in the oxidative stress-induced colonic mucosal epithelial cell dysfunction during IBS through regulating the miR-34a-5p-LDHA-glucose metabolism axis.
Quantitative System Modeling Bridges the Gap between Macro‐ and Microscopic Stomatal Model

An understanding of stomatal function is vital for the carbon and water cycle in nature. In the past decades, various stomatal models with different functions have been established to investigate and predict stomatal behavior and its association with plants’ responses to the changing climate, but with limited biological information provided. On the other hand, many stomatal models at the molecular level focus on simulating and predicting molecular practices and ignore the dynamic quantitative information. As a result, stomatal models are often divided between the microscopic and macroscopic scales. Quantitative systems analysis offers an effective in silico approach to explore the link between microscopic gene function and macroscopic physiological traits. As a first step, a systems model, OnGuard, is developed for the investigation of guard cell ion homeostasis and its relevance to the dynamic stomatal movements. The system model has already yielded a series of important predictions to guide molecular physiological studies in stomata. It also exhibits great potential in breeding practice, which represents a key step toward “Breeding by design” of improving plant carbon–water use efficiency. Here, the development of stomatal models is reviewed, and the future perspectives on stomatal modeling for agricultural and ecological applications are discussed.
Proceedings of the 2017 model-based enterprise (MBE) summit

ion, i.e. products flowing through processes being executed by resources configured in a facility (PPRF), and they appear together in integrated models of the enterprise. For example, production systems might integrate storage and fulfillment capabilities as well as material handling and transportation systems, and supply chains might integrate flows between warehouses, transportation systems, and manufacturing or health care fa-