Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamical heterogeneity and universality of power-grids

While weak, tuned asymmetry can improve, strong heterogeneity destroys synchronization in the electric power system. We study the level of heterogeneity, by comparing large high voltage (HV) power-grids of Europe and North America. We provide an analysis of power capacities and loads of various energy sources from the databases and found heavy tailed distributions with similar characteristics. Graph topological measures, community structures also exhibit strong similarities, while the cable admittance distributions can be well fitted with the same power-laws (PL), related to the length distributions. The community detection analysis shows the level of synchronization in different domains of the European HV power grids, by solving a set of swing equations. We provide numerical evidence for frustrated synchronization and Chimera states and point out the relation of topology and level of synchronization in the subsystems. We also provide empirical data analysis of the frequency heterogeneities within the Hungarian HV network and find q-Gaussian distributions related to super-statistics of time-lagged fluctuations, which agree well with former results on the Nordic Grid.
Scattering with Neural Operators

Recent advances in machine learning establish the ability of certain neural-network architectures called neural operators to approximate maps between function spaces. Motivated by a prospect of employing them in fundamental physics, we examine applications to scattering processes in quantum mechanics. We use an iterated variant of Fourier neural operators to learn the physics of Schr\"odinger operators, which map from the space of initial wave functions and potentials to the final wave functions. These deep operator learning ideas are put to test in two concrete problems: a neural operator predicting the time evolution of a wave packet scattering off a central potential in $1+1$ dimensions, and the double-slit experiment in $2+1$ dimensions. At inference, neural operators can become orders of magnitude more efficient compared to traditional finite-difference solvers.
Electronic structure of GaSb/AlGaSb quantum dots formed by filling droplet-etched nanoholes

Epitaxially-grown semiconductor quantum dots (QDs) provide an attractive platform for the development of deterministic sources of high-quality quantum states of light. Such non-classical light sources are essential for quantum information processing and quantum communication. QDs emitting in the telecom wavelengths are especially important for ensuring compatibility with optical fiber systems required to implement quantum communication networks. To this end, GaSb QDs fabricated by filling local-droplet etched nanoholes are emerging as a viable approach, yet the electronic properties of such nanostructures have not been studied in detail. In this article, an insight into the electronic structure and carrier dynamics in GaSb/AlGaSb QDs is provided through a systematic experimental analysis of their temperature-dependent photoluminescence behavior. A steady-state rate equation model is used to reveal the relevant energy barriers for thermally activated carrier capture and escape processes. Furthermore, results of detailed theoretical simulations of quantum-confined energy states using the multi-band k.p model and the effective mass method are presented. The purpose of the simulations is to reveal the direct and indirect energy states, carrier wavefunctions, and allowed optical transitions for GaSb QDs with different physical dimensions.
Environmental impacts of coastal aquaculture development

Management measures to mitigate deteriorating water quality/ and the adverse environmental impacts of aquaculture development are to be dealt with as a priority area and a holistic approach is needed. Environmental baseline studies are necessary to establish and assess environmental quality and to be able to quantify this quality in economic terms.
Is it an i or an l: Test-time Adaptation of Text Line Recognition Models

Recognizing text lines from images is a challenging problem, especially for handwritten documents due to large variations in writing styles. While text line recognition models are generally trained on large corpora of real and synthetic data, such models can still make frequent mistakes if the handwriting is inscrutable or the image acquisition process adds corruptions, such as noise, blur, compression, etc. Writing style is generally quite consistent for an individual, which can be leveraged to correct mistakes made by such models. Motivated by this, we introduce the problem of adapting text line recognition models during test time. We focus on a challenging and realistic setting where, given only a single test image consisting of multiple text lines, the task is to adapt the model such that it performs better on the image, without any labels. We propose an iterative self-training approach that uses feedback from the language model to update the optical model, with confident self-labels in each iteration. The confidence measure is based on an augmentation mechanism that evaluates the divergence of the prediction of the model in a local region. We perform rigorous evaluation of our method on several benchmark datasets as well as their corrupted versions. Experimental results on multiple datasets spanning multiple scripts show that the proposed adaptation method offers an absolute improvement of up to 8% in character error rate with just a few iterations of self-training at test time.
Detection of internal N7-methylguanosine (m7G) RNA modifications by mutational profiling sequencing

Abstract Methylation of guanosine on position N7 (m7G) on internal RNA positions has been found in all domains of life and have been implicated in human disease. Here, we present m7G Mutational Profiling sequencing (m7G-MaP-seq), which allows high throughput detection of m7G modifications at nucleotide resolution. In our method, m7G modified positions are converted to abasic sites by reduction with sodium borohydride, directly recorded as cDNA mutations through reverse transcription and sequenced. We detect positions with increased mutation rates in the reduced and control samples taking the possibility of sequencing/alignment error into account and use replicates to calculate statistical significance based on log likelihood ratio tests. We show that m7G-MaP-seq efficiently detects known m7G modifications in rRNA with mutational rates up to 25% and we map a previously uncharacterised evolutionarily conserved rRNA modification at position 1581 in Arabidopsis thaliana SSU rRNA. Furthermore, we identify m7G modifications in budding yeast, human and arabidopsis tRNAs and demonstrate that m7G modification occurs before tRNA splicing. We do not find any evidence for internal m7G modifications being present in other small RNA, such as miRNA, snoRNA and sRNA, including human Let-7e. Likewise, high sequencing depth m7G-MaP-seq analysis of mRNA from E. coli or yeast cells did not identify any internal m7G modifications.
HIV_A_252391 221..231

Adnan Kemal* Melese Sinaga Teshome* Mohammed Ahmed 3 Meseret Molla Tabarak Malik 4 Jemmal Mohammed Kalkidan Hassen Abate* 1Department of Public Health, College of Health Science, Defense University, Addis Ababa, Ethiopia; 2Department of Nutrition and Dietetics, Jimma University, Jimma, Ethiopia; 3Department of Public Health, College of Health Science, Woldia University, Woldia, Ethiopia; 4Department of Biochemistry, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia; 5Department of Ophthalmology, Jimma University, Jimma, Ethiopia
Determination of eight artificial sweeteners in wastewater by hydrophilic interaction liquid chromatography-tandem mass spectrometry

The development of a method for the simultaneous determination of eight artificial sweeteners, namely aspartame (ASP), alitame (ALI), neotame (NEO), acesulfame (ACS), saccharin (SAC), cyclamate (CYC), sucralose (SCL) and neohesperidin dihydrochalcone (NHDC), under hydrophilic interaction liquid chromatography (HILIC) conditions is presented herein. The ionization of all the compounds was achieved by negative electrospray. Two silica-based columns, a fully porous (XBridge HILIC) and a fused-core one (Kinetex HILIC), were compared. For HILIC optimization, the effect of the following parameters was studied: the mobile phase, column temperature, pH and ionic strength of the ammonium formate buffer. The optimized mobile phase was 5 mM ammonium formate buffer pH 3.5–methanol–acetonitrile (15/10/75 v/v), with a flow rate of 100 μL min−1 at 50 °C. The asymmetry factor of the peaks was lower on the Kinetex HILIC column than that on the XBridge HILIC. The predominant retention mechanism of all the analytes on silica columns seems to be partition to the aqueous layer. The method was validated in tap water and wastewater samples using Kinetex HILIC. Three deuterated internal standards were used, one for each category of sweeteners (dipeptides, sulfamates and sugars). The instrumental limits of detection ranged from 0.24 (SAC) to 4.4 (SCL) μg L−1. The recoveries in influent samples ranged from 39% (CYC) to 97% (NEO), while recoveries were better for the other two matrices. Inter-day precision (%RSD, n = 6) ranged from 4.2% (SAC) to 20% (ALI) in influent samples. The method was applied to influents and effluents from the wastewater treatment plant of Athens for seven consecutive days and high levels of sucralose and sulfamates were found.
A ug 2 02 1 Spectral density of random graphs : convergence properties and application in model fitting

Random graph models are used to describe the complex structure of real-world networks in diverse fields of knowledge. Studying their behavior and fitting properties are still critical challenges, that in general, require model-specific techniques. An important line of research is to develop generic methods able to fit and select the best model among a collection. Approaches based on spectral density (i.e., distribution of the graph adjacency matrix eigenvalues) appeal to that purpose: they apply to different random graph models. Also, they can benefit from the theoretical background of random matrix theory. This work investigates the convergence properties of model fitting procedures based on the graph spectral density and the corresponding cumulative distribution function. We also review the convergence of the spectral density for the most widely used random graph models. Moreover, we explore through simulations the limits of these graph spectral density convergence results, particularly in the case of the block model, where only partial results have been established.
Patient-reported severity of dry eye and quality of life in diabetes

Purpose: The purpose of the study was to assess the relationship between patient-reported severity of dry eye disease (DED), quality of life (QoL), presence of diabetic retinopathy (DR) and length of disease duration in people with type 1 diabetes mellitus (DM1) and type 2 diabetes mellitus (DM2). Patients and methods: A survey of 152 people (110 with and 42 without diabetes). All participants completed the Ocular Surface Disease Index (OSDI) and Dry Eye-related Quality of Life Score (DEQS) questionnaires. Results: Forty-four percent of all diabetic subjects reported dry eye symptoms, compared to 29% in the control group. Patients with DM2 reported dry eye symptoms more frequently than those with DM1 (55% and 27% respectively, P = 0.001). Dry eye severity was linked to a significant deterioration in QoL in both types of diabetes (DM1, r = 0.609 and P = 0.036; DM2, r = 0.417 and P = 0.011). Irrespective of DR, the presence of DED was significantly higher in DM2 compared to DM1 (with DR, P = 0.011; without DR, P = 0.018). Conclusion: Dry eye symptoms are associated with reduced QoL and are more common in people with DM2 than in DM1, irrespective of DR status. Routine clinical screening for severe DED could potentially allow for a timely and more effective treatment and could contribute to mitigating the dry eye-associated reduction in QoL in those with DM2.
Acute tubulointerstitial nephritis and coronavirus

Coronavirus disease 2019 (COVID-19) is an ongoing pandemic that to date has spread to >100 countries. Acute kidney injury is not uncommon with this disease. The most common kidney biopsy finding is acute tubular injury. Glomerular diseases such as collapsing glomerulopathy and vasculitis, and thrombotic microangiopathy have been reported. Viral inclusion particles with distinctive spikes in the tubular epithelium and podocytes, and endothelial cells of the glomerular capillary loops, have been visualized by electron microscopy by some but disputed by others as non-viral structures. Interstitial infiltrates have not commonly been described in the published kidney biopsy series from patients with COVID-19. Medications used to treat COVID-19 can lead to interstitial nephritis, but very few have been reported. In summary, interstitial kidney disease is a rare finding in COVID-19.
Commentary: Lesbian, gay, bisexual, and transgender health: disparities we can change.

Note: The author provides commentary on the article ‘‘Lesbian, Gay, Bisexual, and Transgender Health: Disparities We Can Change,’’ also in this issue, by Fidelindo Lim, MA, RN. Indeed, Mr Lim has provided an overview of lesbian, gay, bisexual, and transgender (LGBT) health issues that, sadly, have been missing from nursing curricula for far too long. Faculty may recognize that it is time for LGBT issues to be integrated into their teaching plans but many simply do not know where to start. Here are common fears and barriers that I have encountered and some suggestions to help overcome the barriers.
Lesbian, Gay, Bisexual, and Transgender Health: Obstetrician-Gynecologists' Training, Attitudes, Knowledge, and Practice.

BACKGROUND Deficits in provider training may contribute to disparities impacting lesbian, gay, bisexual, transgender, and gender nonconforming (LGB-TGNC) individuals. METHODS We sent an anonymous online survey to randomly selected members of the American Congress of Obstetricians and Gynecologists and stratified responses by the history of training. We used logistic regression to predict impact of previous training on provider comfort with LGB-TGNC patients, and secondary outcomes, including provider practices, knowledge, and attitudes. RESULTS Two hundred twenty-eight of 428 (53.3%) surveys were completed. Of the 169 providers currently practicing gynecology, 72 respondents (42.6%) reported previous training in LGB-TGNC health. Those who self-identified or had a close contact identifying as LGB-TGNC were more likely to report previous training (68.1% vs. 49.5%, p = 0.02). When adjusting for demographic differences, providers reporting previous training were not more likely to be comfortable taking care of transgender/gender-nonconforming patients (aOR 1.8, 95% CI 0.95-3.40). They were more likely to report practice changes such as eliciting sexual orientation (aOR 2.15, 95% CI 1.08-4.28) and gender identity (aOR 3.02, 95% CI 1.07-8.52). Training was not independently associated with differences in provider knowledge (aOR 1.33, 95% CI 0.68-2.58) or likelihood of providing independent medical or surgical care for gender affirmation (aOR 1.64, 95% CI 0.78-3.45). CONCLUSIONS Less than half of board-certified obstetrician-gynecologists reported training in LGB-TGNC health, with evidence of a familiarity effect in who seeks training and provides care that accounts for differences in attitudes, knowledge, and practices. Training efforts to advance LGB-TGNC health must address bias and comfort in addition to clinical competencies.
Combined exposure to lifting and psychosocial strain at work and adverse pregnancy outcomes-A study in the Danish National Birth Cohort

Background Previous studies have investigated physical and psychosocial job exposures separately in relation to foetal growth. We therefore investigated if occupational lifting and psychosocial job strain interact to affect foetal growth and gestational length. We hypothesised that heavy lifting and high job strain would increase the risk of impacted foetal growth (small or large for gestational age) and preterm birth.
Devices in Heart Failure Patients-Who Benefits From ICD and CRT?

: Despite advances in heart failure treatment, this condition remains a relevant medical issue and is associated with a high morbidity and mortality. The cause of death in patients suffering from heart failure is not only a result of hemodynamic failure, but can also be due to ventricular arrhythmias. Implantable cardioverter defibrillators (ICDs) are these days the only tool to significantly reduce arrhythmic sudden death; but not all patients benefit to the same extend. In addition, cardiac resynchronization therapy (CRT) is another tool which is used in patients suffering from heart fialure. Even though both devices have been investigated in large randomized trials, both ICD and CRT remain underutilized in many countries. This brief review focuses on various aspects in this regard including a short overview on upcoming device novelties in the near future. Despite advances in heart failure treatment, this condition remains a relevant medical issue and is associated with a high morbidity and mortality. The cause of death in patients suffering from heart failure is not only a result of hemodynamic failure, but can also be due to ventricular arrhythmias. Implantable cardioverter deﬁbrillators (ICDs) are these days the only tool to signiﬁcantly reduce arrhythmic sudden death; but not all patients beneﬁt to the same extend. In addition, cardiac resynchronization therapy (CRT) is another tool which is used in patients suffering from heart ﬁalure. Even though both devices have been investigated in large randomized trials, both ICD and CRT remain underutilized in many countries. This brief review focuses on various aspects in this regard including a short overview on upcoming device novelties in the near future.
Prediction of outcome after moderate and severe traumatic brain injury: External validation of the International Mission on Prognosis and Analysis of Clinical Trials (IMPACT) and Corticoid Randomisation After Significant Head injury (CRASH) prognostic models*

Objective: The International Mission on Prognosis and Analysis of Clinical Trials and Corticoid Randomisation After Significant Head injury prognostic models predict outcome after traumatic brain injury but have not been compared in large datasets. The objective of this is study is to validate externally and compare the International Mission on Prognosis and Analysis of Clinical Trials and Corticoid Randomisation after Significant Head injury prognostic models for prediction of outcome after moderate or severe traumatic brain injury. Design: External validation study. Patients: We considered five new datasets with a total of 9,036 patients, comprising three randomized trials and two observational series, containing prospectively collected individual traumatic brain injury patient data. Measurements and Main Results: Outcomes were mortality and unfavorable outcome, based on the Glasgow Outcome Score at 6 months after injury. To assess performance, we studied the discrimination of the models (by area under the receiver operating characteristic curves), and calibration (by comparison of the mean observed to predicted outcomes and calibration slopes). The highest discrimination was found in the Trauma Audit and Research Network trauma registry (area under the receiver operating characteristic curves between 0.83 and 0.87), and the lowest discrimination in the Pharmos trial (area under the receiver operating characteristic curves between 0.65 and 0.71). Although differences in predictor effects between development and validation populations were found (calibration slopes varying between 0.58 and 1.53), the differences in discrimination were largely explained by differences in case mix in the validation studies. Calibration was good, the fraction of observed outcomes generally agreed well with the mean predicted outcome. No meaningful differences were noted in performance between the International Mission on Prognosis and Analysis of Clinical Trials and Corticoid Randomisation After Significant Head injury models. More complex models discriminated slightly better than simpler variants. Conclusions: Since both the International Mission on Prognosis and Analysis of Clinical Trials and the Corticoid Randomisation After Significant Head injury prognostic models show good generalizability to more recent data, they are valid instruments to quantify prognosis in traumatic brain injury.
Macrophages and Alcohol-Related Liver Inflammation.

Recent studies have suggested that macrophages have a critical role in the development of alcohol-induced inflammation in the liver. To define the precise pathogenic function of these cells during alcoholic liver disease (ALD), it is extremely important to conduct extensive studies in clinical settings that further elucidate the phenotypic diversity of macrophages in the context of ALD. Research to date already has identified several characteristics of macrophages that underlie the cells' actions, including macrophage polarization and their phenotypic diversity. Other analyses have focused on the contributions of resident versus infiltrating macrophages/monocytes, as well as on the roles of macrophage mediators, in the development of ALD. Findings point to the potential of macrophages as a therapeutic target in alcoholic liver injury. Future studies directed toward understanding how alcohol affects macrophage phenotypic switch in the liver and other tissues, whether the liver microenvironment determines macrophage function in ALD, and if targeting of macrophages alleviates alcoholic liver injury, will provide promising strategies to manage patients with alcoholic hepatitis.
Herpes zoster and postherpetic neuralgia surveillance using structured electronic data.

OBJECTIVE To develop electronic algorithms for rapid, automated surveillance for herpes zoster and postherpetic neuralgia (PHN) using codified electronic health data. PATIENTS AND METHODS We attempted to identify every case of herpes zoster and PHN arising between January 1 and December 31, 2008, within the electronic medical record of a 560,000-patient ambulatory practice using an array of diagnosis codes; intervals between herpes zoster encounters; and prescriptions for analgesics, anticonvulsants, and antidepressants. We assessed the sensitivity and positive predictive value (PPV) of each screening criterion by medical record review and then integrated multiple criteria into combination algorithms to optimize sensitivity and PPV. We applied the optimized algorithms to the practice's historical data spanning January 1, 1996, to December 31, 2008, to assess for changes in the annual incidence of PHN. RESULTS The International Classification of Diseases, Ninth Revision, code 053 detected herpes zoster with 98% sensitivity and 93% PPV. A combination algorithm including diagnosis codes, visit intervals, and prescriptions detected PHN with 86% sensitivity and 78% PPV. Between 1996 and 2008, the age- and sex-adjusted annual incidence of PHN rose from 0.18 to 0.47 cases per 1000 patients, and the proportion of herpes zoster patients progressing to PHN rose from 5.4% to 17.6%. CONCLUSION Novel algorithms incorporating multiple streams of electronic health data can reasonably detect herpes zoster and PHN. These algorithms could facilitate meaningful public health surveillance using electronic health data. The incidence of PHN may be increasing.