Miracle-dz/UniFAR-FTUs huggingface dataset:
On Credibility of Adversarial Examples Against Learning-Based Grid Voltage Stability Assessment

Voltage stability assessment is essential for maintaining reliable power grid operations. Stability assessment approaches using deep learning address the shortfalls of the traditional time-domain simulation-based approaches caused by increased system complexity. However, deep learning models are shown to be vulnerable to adversarial examples in the field of computer vision. While this vulnerability has been noticed by the power grid cybersecurity research, the domain-specific analysis on the requirements imposed upon effective attack implementation is still lacking. Although these attack requirements are usually reasonable in computer vision tasks, they can be stringent in the context of power grids. In this paper, we conduct a systematic investigation on the attack requirements and credibility of six representative adversarial example attacks based on a voltage stability assessment application for the New England 10-machine 39-bus power system. We show that (1) compromising about half the transmission system buses’ voltage traces is a rule-of-thumb attack requirement; (2) the universal adversarial perturbations regardless of the original clean voltage trajectory possess the same credibility as the widely studied false data injection attacks on power grid state estimation, while the input-specific adversarial perturbations are less credible; (3) the prevailing strong adversarial training thwarts the universal perturbations but fails in defending certain input-specific perturbations. To advance defense to cope with both universal and input-specific adversarial examples, we propose a new approach that simultaneously estimates the predictive uncertainty of any given input of voltage trajectory and thwarts the attacks effectively.
Development and analysis of models for service migration to the MEC server based on hysteresis approach

Online video services are among the most popular ways of content consumption. Video hosting servers have a very high load every day, which we propose to reduce by migrating the application with the video content in demand to the local Multi-access Edge Computing (MEC) server of the target. This makes it possible to improve the quality of services (QoS) provided to users by reducing the transmission delay. Therefore, an architecture has been proposed that allows, at times of increased demand for the same video content, to migrate the video service application to the edge servers of the network operator. To evaluate the performance of this approach, a mathematical model was developed in the form of a queuing system. The results of the numerical experiment make it possible to optimize the time of using local MEC servers to provide video content.
Trajectories of low‐income mothers’ and fathers’ engagement in learning activities and child socioemotional skills in middle childhood

Using Fragile Families and Child Wellbeing data ( N = 3259), the current study examined Black and Latinx mothers’ and fathers’ trajectories of engagement in learning activities (e.g., storytelling) from infancy to age 5, and whether those trajectories predicted socioemotional skills at age 9, predictors of the trajectories (poverty, mother-father nonresidence, temperament, race/ethnicity), and moderators of the trajectories. Mothers’ and fathers’ learning activities decreased significantly over time as children got older. Higher rates of decline in fathers’ engagement in learning activities over time significantly predicted lower socioemotional skills. Mother-father nonresidence during infancy was associated significantly with higher rates of decline in mothers’ and fathers’ learning activities. Difficult temperament moderated the association between fathers’ trajectories and child outcomes.
OMOP CDM Can Facilitate Data-Driven Studies for Cancer Prediction: A Systematic Review

The current generation of sequencing technologies has led to significant advances in identifying novel disease-associated mutations and generated large amounts of data in a high-throughput manner. Such data in conjunction with clinical routine data are proven to be highly useful in deriving population-level and patient-level predictions, especially in the field of cancer precision medicine. However, data harmonization across multiple national and international clinical sites is an essential step for the assessment of events and outcomes associated with patients, which is currently not adequately addressed. The Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) is an internationally established research data repository introduced by the Observational Health Data Science and Informatics (OHDSI) community to overcome this issue. To address the needs of cancer research, the genomic vocabulary extension was introduced in 2020 to support the standardization of subsequent data analysis. In this review, we evaluate the current potential of the OMOP CDM to be applicable in cancer prediction and how comprehensively the genomic vocabulary extension of the OMOP can serve current needs of AI-based predictions. For this, we systematically screened the literature for articles that use the OMOP CDM in predictive analyses in cancer and investigated the underlying predictive models/tools. Interestingly, we found 248 articles, of which most use the OMOP for harmonizing their data, but only 5 make use of predictive algorithms on OMOP-based data and fulfill our criteria. The studies present multicentric investigations, in which the OMOP played an essential role in discovering and optimizing machine learning (ML)-based models. Ultimately, the use of the OMOP CDM leads to standardized data-driven studies for multiple clinical sites and enables a more solid basis utilizing, e.g., ML models that can be reused and combined in early prediction, diagnosis, and improvement of personalized cancer care and biomarker discovery.
MeltPondNet: A Swin Transformer U-Net for Detection of Melt Ponds on Arctic Sea Ice

High-resolution aerial photographs of Arctic region are a great source for different sea ice feature recognition, which are crucial to validate, tune, and improve climate models. Melt ponds on the surface of melting Arctic sea ice are of particular interest as they are sensitive and valuable indicators and are proxy to the processes in the Arctic climate system. Manual analysis of this remote sensing data is extremely difficult and time-consuming due to the complex shapes and unpredictable boundaries of the melt ponds, and that leads to the necessity for automatizing the processes. In this study, we propose a robust and efficient automatic method for melt pond region segmentation and boundary extraction from high-resolution aerial photographs. The proposed algorithm is based on a swin transformer U-Net in which we introduce novel cross-channel attention mechanisms into the decoder design. The framework operates with optical data and allows for classifying imagery into four classes, i.e., sea ice/snow, open water, melt pond, and submerged ice. We use aerial photographs collected during the Healy–Oden Trans Arctic Expedition over Arctic sea ice in the summer season of 2005 as test data. The experimental results show that the proposed method is suitable for precise automatic extraction of melt pond geometry, and it can also be extended for other optical data sources that involve melt ponds. The approach has a promising potential to be used to analyze melt ponds' corresponding changes between years.
Enhanced Velocity Vector Estimation Using Distributed Radar System

The velocity estimation of moving target in the distributed radar systems is obtained by transmitting a radio signal from the radar and measuring its Doppler frequency shift. However, the radar can only estimate the radial velocity of the target, which is the velocity component projected onto the direction between the radar and the target. As a result, the velocity estimation performance can be degraded when the target is moving in the lateral direction. Moreover, there is an upper limit in the maximum detectable velocity due to the limited sampling frequency, which is known as Doppler ambiguity. To address these problems, we propose a method of estimating the unambiguous velocity vector of the target by using the detection results of distributed multiple radars. First, the radial velocity of the target is measured along each radial direction of multiple radars toward the target to utilize the spatial diversity. Then, the detection results are combined and the target’s velocity vector is estimated by applying the least square method. In addition, by defining a set of candidate velocities and choosing the velocity which minimizes the sum of squared errors, the unambiguous velocity of the target is estimated. Simulation results verify that the proposed method can successfully estimate the unambiguous velocity vector of the target with a proper signal-to-noise ratio.
Detection and manipulation of nuclear spin states in fermionic strontium

Fermionic {sup 87}Sr has a nuclear spin of I=9/2, higher than any other element with a similar electronic structure. This large nuclear spin has many applications in quantum simulation and computation, for which preparation and detection of the spin state are requirements. For an ultracold {sup 87}Sr cloud, we show two complementary methods to characterize the spin-state mixture: optical Stern-Gerlach state separation and state-selective absorption imaging. We use these methods to optimize the preparation of a variety of spin-state mixtures by optical pumping and to measure an upper bound of the {sup 87}Sr spin-relaxation rate.
South African employees’ perceptions of the inclusion of traditional health practitioners’ services in workplace employee assistance programmes

Abstract This study investigated employees’ perceptions of incorporating traditional health practitioners’ services in employee assistance programmes in the South African context. A qualitative approach was used in which 49 participants completed a qualitative online questionnaire to share their perceptions. The study’s findings revealed that the wellness needs of African employees in the workplace were not being met; that employees were not aware of African traditional health practitioners’ services available on their company’s employee assistance programmes; and indicated the services of African traditional health practitioners that employees would like to be included in their company’s employee assistance programmes. These findings point to the need for organizations to provide more diverse and inclusive services through their employee assistance programmes.
In Situ Monitoring Technique of Self-Heating in Bulk MOSFETs at Cryogenic Temperatures using Subthreshold Current

This work proposes an evaluation technique of self-heating (SH) in a 65-nm bulk CMOS transistor at cryogenic temperature (4.2K). For the in-situ monitoring of self-heating in cryo-CMOS circuits, transient response of the subthreshold drain current is used, which makes it possible to estimate the temperature at on-state of MOSFETs. The relation between the temperature increase by self-heating and power consumption of MOSFET has been experimentally obtained, which will help a design of high performance cryo-CMOS circuits for quantum computer application.
REVISED SUPERNOVA RATES FROM THE IfA DEEP SURVEY

The IfA Deep Survey uncovered ∼ 130 thermonuclear supernova (TN SN, i.e., Type Ia) candidates at redshifts from z = 0.1 out to beyond z = 1. The TN SN explosion rates derived from these data have been controversial, conflicting with evidence emerging from other surveys. This work revisits the IfA Deep Survey to re-evaluate the photometric evidence. Applying the SOFT program to the light curves of all SN candidates, we derive new classification grades and redshift estimates. We find a volumetric rate for z ∼ 0.5 that is substantially smaller than the originally published values, bringing the revised IfA Deep rate into good agreement with other surveys. With our improved photometric analysis techniques, we are able to confidently extend the rate measurements to higher redshifts and we find a steadily increasing TN SN rate, with no indication of a peak out to z = 1.05.
Homeless and Beggar Handling Policy in Semarang: Problems and Challenges

The study is intended to analyze problems of welfare in Indonesian society, especially in the city of Semarang. The results of the study, Semarang City itself has the Regulation No. 5 of 2014 on the Handling of Street Children and Beggars, Tramps, and Displaced Persons (Pengemis, Gelandangan, dan Orang Terlantar, or PGOT) designed Parliament with the Mayor for the usefulness of ordering Semarang city free of street children, beggars, Displaced Persons, thus the Satpol PP Unit in disciplining beggars, vagrants, and displaced persons and street children rely on the local regulation in performing their duties. After the raids and controls carried out by the Satpol PP of Semarang City, then followed up by the Central Java Provincial Social Office to rehabilitate the beggars, the tramps, and the landed people not to return to the road, thus creating a comfortable urban area. Semarang City Government may be able to apply a theory of Socialist Furnace in realizing Semarang City which is comfortable, the furnace theory includes education stove, economic furnace, and health stove. The theory can be used as a reference in dealing with the problems mentioned above.
Preliminary Structure–Activity Relationship Study of the MMV Pathogen Box Compound MMV675968 (2,4-Diaminoquinazoline) Unveils Novel Inhibitors of Trypanosoma brucei brucei

New drugs are urgently needed for the treatment of human African trypanosomiasis (HAT). In line with our quest for novel inhibitors of trypanosomes, a small library of analogs of the antitrypanosomal hit (MMV675968) available at MMV as solid materials was screened for antitrypanosomal activity. In silico exploration of two potent antitrypanosomal structural analogs (7-MMV1578647 and 10-MMV1578445) as inhibitors of dihydrofolate reductase (DHFR) was achieved, together with elucidation of other antitrypanosomal modes of action. In addition, they were assessed in vitro for tentative inhibition of DHFR in a crude trypanosome extract. Their ADMET properties were also predicted using dedicated software. Overall, the two diaminoquinazoline analogs displayed approximately 40-fold and 60-fold more potency and selectivity in vitro than the parent hit, respectively (MMV1578445 (10): IC50 = 0.045 µM, SI = 1737; MMV1578467 (7): IC50 = 0.06 µM; SI = 412). Analogs 7 and 10 were also strong binders of the DHFR enzyme in silico, in all their accessible protonation states, and interacted with key DHFR ligand recognition residues Val32, Asp54, and Ile160. They also exhibited significant activity against trypanosome protein isolate. MMV1578445 (10) portrayed fast and irreversible trypanosome growth arrest between 4–72 h at IC99. Analogs 7 and 10 induced in vitro ferric iron reduction and DNA fragmentation or apoptosis induction, respectively. The two potent analogs endowed with predicted suitable physicochemical and ADMET properties are good candidates for further deciphering their potential as starting points for new drug development for HAT.
European Extremely Large Telescope Site Characterization. II. High Angular Resolution Parameters

This is the second article of a series devoted to European Extremely Large Telescope (E-ELT) site characterization. In this article we present the main properties of the parameters involved in high angular resolution observations from the data collected in the site testing campaign of the E-ELT during the design study (DS) phase. Observations were made in 2008 and 2009, in the four sites selected to shelter the future E-ELT (characterized under the ELT-DS contract): Aklim mountain in Morocco, Observatorio del Roque de los Muchachos (ORM) in Spain, Macón range in Argentina, and Cerro Ventarrones in Chile. The same techniques, instruments, and acquisition procedures were taken on each site. A multiple aperture scintillation sensor (MASS) and a differential image motion monitor (DIMM) were installed at each site. Global statistics of the integrated seeing, the free atmosphere seeing, the boundary layer seeing, and the isoplanatic angle were studied for each site, and the results are presented here. In order to estimate other important parameters, such as the coherence time of the wavefront and the overall parameter “coherence étendue,” additional information of vertical profiles of the wind speed was needed. Data were retrieved from the National Oceanic and Atmospheric Administration (NOAA) archive. Ground wind speed was measured by automatic weather stations (AWS). More aspects of the turbulence parameters, such as their seasonal trend, their nightly evolution, and their temporal stability, were also obtained and analyzed.
Topic modelling of legal documents using NLP and bidirectional encoder representations from transformers

Modeling legal text is a difficult task because of its unique features, such as lengthy texts, complex language structures, and technical terms. During the last decade, there has been a big rise in the number of legislative documents, which makes it hard for law professionals to keep up with legislation like analyzing judgements and implementing acts. The relevancy of topics is heavily influenced by the processing and presentation of legal documents in some contexts. The objective of this work is to understand the legal judgement corpus related to cases under the Hindu Marriage Act of India. The study looked into various methods to generate sentence embeddings from the judgement. This paper employs the power of the BERTopic algorithm for generating significant topics.
Transcriptomic Analysis to Unravel Potential Pathways and Genes Involved in Pecan (Carya illinoinensis) Resistance to Pestalotiopsis microspora

Fruit black spot (FBS), a fungal disease of pecan (Carya illinoinensis (Wangenh) K. Koch) caused by the pathogen Pestalotiopsis microspora, is a serious disease and poses a critical threat to pecan yield and quality. However, the details of pecan responses to FBS infection at the transcriptional level remain to be elucidated. In present study, we used RNA-Seq to analyze differential gene expression in three pecan cultivars with varied resistance to FBS infection: Xinxuan-4 (X4), Mahan (M), and Wichita (W), which were categorized as having low, mild, and high susceptibility to FBS, respectively. Nine RNA-Seq libraries were constructed, comprising a total of 58.56 Gb of high-quality bases, and 2420, 4380, and 8754 differentially expressed genes (DEGs) with |log2Fold change| ≥ 1 and p-value < 0.05 were identified between M vs. X4, W vs. M, and W vs. X4, respectively. Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathway analyses were performed to further annotate DEGs that were part of specific pathways, which revealed that out of 134 total pathways, MAPK signaling pathway, plant–pathogen interaction, and plant hormone signal transduction were highly enriched. Transcriptomic profiling analysis revealed that 1681 pathogen-related genes (PRGs), including 24 genes encoding WRKY transcription factors, potentially participate in the process of defense against Pestalotiopsis microspora infection in pecan. The correlation of WRKY TFs and PRGs was also performed to reveal the potential interaction networks among disease-resistance/pathogenesis-related genes and WRKY TFs. Expression profiling of nine genes annotated as TIFY, WRKY TF, and disease-resistance protein-related genes was performed using qRT-PCR, and the results were correlated with RNA-Seq data. This study provides valuable information on the molecular basis of pecan–Pestalotiopsis microspora interaction mechanisms and offers a repertoire of candidate genes related to pecan fruit response to FBS infection.
PPPC 4 DM ID: a poor particle physicist cookbook for dark matter indirect detection

We correct a few mistakes of the original version of this work (notably related to the computations of extragalactic gamma rays), while at the same time improving and upgrading other aspects (notably as a consequence of the discovery of the higgs boson at the LHC). A brief list of the main changes is: - We include a higgs boson channel hh with mass mh = 125 GeV. All previous channels hmhm are removed. - We correct the formulae for the computation of extragalactic gamma rays (fixing in particular the redshift dependence) as well as the numerical computations (also including a corrected impact of absorption). - We provide a new version of the Optical Depth function, employing updated models of Extragalactic Background Light (EBL) and fixing the redshift dependence. All these corrections and updates are reflected on the numerical ingredients provided on the website; they correspond to Release 2.0.
Bandwidth Enhancement of the Millimeter-Wave Microstrip Linear Array With Loading of Shorting Pins

A broadband, series-fed, millimeter-wave (MMW) microstrip linear array is investigated. This array is evolved from a stub-loaded microstrip line, which has two resonant modes in the passband and an impedance bandwidth of about 26%. By simply inserting three pairs of shorting pins at the two ends of the microstrip line to regulate the field/current distributions, four additional resonances can be excited, significantly increasing the operating bandwidth to 63.5%. In addition, the original gain dips caused by anti-phase (equivalent) magnetic current disappear and the gain becomes quite stable, showing the maximum value of 12.82 dBi and a 3 dB bandwidth of 53.8%. Also, the first sidelobe level (FSLL) is lower than −10 dB from 26.6 to 44.2 GHz (49.7%) and lower than −20 dB from 26.6 to 30.7 GHz (14.3%). Therefore, the proposed array features great advantages, such as a simple structure and an enhanced bandwidth with good sidelobe suppression.
The Synthesis of Bio-Based Michael Donors from Tall Oil Fatty Acids for Polymer Development

In this study, the synthesis of a Michael donor compound from cellulose production by-products—tall oil fatty acids—was developed. The developed Michael donor compounds can be further used to obtain polymeric materials after nucleophilic polymerization through the Michael reaction. It can be a promising alternative method for conventional polyurethane materials, and the Michael addition polymerization reaction takes place under milder conditions than non-isocyanate polyurethane production technology, which requires high pressure, high temperature and a long reaction time. Different polyols, the precursors for Michael donor components, were synthesized from epoxidized tall oil fatty acids by an oxirane ring-opening and esterification reaction with different alcohols (trimethylolpropane and 1,4-butanediol). The addition of functional groups necessary for the Michael reaction was carried out by a transesterification reaction of polyol hydroxyl groups with tert-butyl acetoacetate ester. The following properties of the developed polyols and their acetoacetates were analyzed: hydroxyl value, acid value, moisture content and viscosity. The chemical structure was analyzed using Fourier transform infrared spectroscopy, gel permeation chromatography, size-exclusion chromatography and nuclear magnetic resonance. Matrix-assisted laser desorption/ionization analysis was used for structure identification for this type of acetoacetate for the first time.