Miracle-dz/UniFAR-FTUs huggingface dataset:
NOVO PEPTIDE SEQUENCING WITH DATABASE SEARCH OF TANDEM MASS SPECTRA *

Database search tools identify peptides by matching tandem mass spectra against a protein database. We study an alternative approach when all plausible de novo interpretations of a spectrum (spectral dictionary) are generated and then quickly matched against the database. We present a new MS-Dictionary algorithm for efficiently generating spectral dictionaries and demonstrate that MSDictionary can identify spectra that are missed in the database search. We argue that MS-Dictionary enables proteogenomics searches in six-frame translation of genomic sequences that may be prohibitively time-consuming for existing database search approaches. We show that such searches allow one to correct sequencing errors and find programmed frameshifts. Molecular & Cellular Proteomics 8:53–69, 2009.
Comparing the performance of a deep convolutional neural network with orthopaedic surgeons on the identification of total hip prosthesis design from plain radiographs.

PURPOSE A crucial step in the preoperative planning for a revision total hip replacement (THR) surgery is the accurate identification of the failed implant design, especially if one or more well-fixed/functioning components are to be retained. Manual identification of the implant design from preoperative radiographic images can be time-consuming and inaccurate, which can ultimately lead to increased operating room time, more complex surgery, and increased healthcare costs. METHOD In this study, we present a novel approach to identifying THR femoral implants' design from plain radiographs using a convolutional neural network (CNN). We evaluated a total of 402 radiographs of nine different THR implant designs including, Accolade II (130 radiographs), Corail (89 radiographs), M/L Taper (31 radiographs), Summit (31 radiographs), Anthology (26 radiographs), Versys (26 radiographs), S-ROM (24 radiographs), Taperloc Standard Offset (24 radiographs), and Taperloc High Offset (21 radiographs). We implemented a transfer learning approach and adopted a DenseNet-201 CNN architecture by replacing the final classifier with nine fully connected neurons. Furthermore, we used saliency maps to explain the CNN decision-making process by visualizing the most important pixels in a given radiograph on the CNN's outcome. We also compared the CNN's performance with three board-certified and fellowship-trained orthopaedic surgeons. RESULTS The CNN achieved the same or higher performance than at least one of the surgeons in identifying eight out of nine THR implant designs and underperformed all of the surgeons in identifying one THR implant design (Anthology). Overall, the CNN achieved a lower cohen's kappa (0.78) than surgeon 1 (1.00), the same cohen's kappa as surgeon 2 (0.78), and a slightly higher cohen's kappa than surgeon 3 (0.76) in identifying all the nine THR implant designs. Furthermore, the saliency maps showed that the CNN generally focused on each implant's unique design features to make a decision. Regarding the time spent performing the implant identification, the CNN accomplished this task in ~0.06 seconds per radiograph. The surgeon's identification time varied based on the method they utilized. When using their personal experience to identify the THR implant design, they spent negligible time. However, the identification time increased to an average of 8.4 minutes (standard deviation 6.1 minutes) per radiograph when they used another identification method (online search, consulting with the orthopaedic company representative, and using image atlas), which occurred in about 17% of cases in the test subset (40 radiographs). CONCLUSIONS CNNs such as the one developed in this study can be used to automatically identify the design of a failed THR femoral implant pre-operatively in just a fraction of a second, saving time and in some cases improving identification accuracy.
Addenda and Errata Biological Crystallography Addenda and Errata Pushing the Boundaries of Molecular Replacement with Maximum Likelihood. Erratum

In the calculations testing maximum-likelihood molecular-replacement methods reported in the paper by Read [(2001). Acta Cryst. D57, 1373±1382] simulated data constructed to test isomorphous replacement methods in the presence of known errors were used inadvertently. The test calculations have been repeated using the measured data, and the results are given. In the reported calculations testing maximum-likelihood molecular-replacement methods (Read, 2001) on the structure of Streptomyces griseus trypsin (SGT), I inadvertently used simulated data computed from the ®nal re®ned structure of SGT (Read & James, 1986). The simulated data had been constructed to test isomorphous replacement methods in the presence of known errors. The test calculations have been repeated using the measured data, and the results are given in new Tables 1 and 2. The original conclusions are upheld, except that in a translation search with an orientation in error by 6.9 , the correct translation no longer has the highest likelihood score. However, when this translation search is repeated, increasing the assumed r.m.s. error of the molecular-replacement model from the default value of 1.4 to 2.0 A Ê to compensate for the effect of orientation error, the correct translation again has the highest likelihood score. As before, the discrimination from incorrect translations is poor with the most inaccurate orientation.
Exploring the item-sets of the Recovering Quality of Life (ReQoL) measures using factor analysis

Purpose This paper presents two studies exploring the latent structure of item sets used in the development of the Recovering Quality of Life mental health outcome measures: ReQoL-10 and ReQoL-20. Method In study 1, 2262 participants completed an initial set of 61 items. In study 2, 4266 participants completed a reduced set of 40 items. Study 2 evaluated two formats of the questionnaires: one version where the items were intermingled and one where the positively worded and negatively worded items were presented as two separate blocks. Exploratory and confirmatory factor analyses were conducted on both datasets where models were specified using ordinal treatment of the item responses. Dimensionality based on the conceptual framework and methods effects reflecting the mixture of positively worded and negatively worded items were explored. Factor invariance was tested across the intermingled and block formats. Results In both studies, a bi-factor model (study 1: RMSEA = 0.061; CFI = 0.954; study 2: RMSEA = 0.066; CFI = 0.971) with one general factor and two local factors (positively worded questions and negatively worded questions) was preferred. The loadings on the general factor were higher than on the two local factors suggesting that the ReQoL scale scores can be understood in terms of a general factor. Insignificant differences were found between the intermingled and block formats. Conclusions The analyses confirmed that the ReQoL item sets are sufficiently unidimensional to proceed to item response theory analysis. The model was robust across different ordering of positive and negative items.
Fame and Marginality: The Archaeology of the Montagne Sainte Victoire (Provence, France)

This article presents the results of a landscape archaeology project from Provence in the south of France. Data from field survey and excavation are discussed. Settlement patterns and human/landscape dynamics from the protohistoric periods through to the end of the Roman period are assessed. Trends in settlement expansion and contraction are analyzed along with the relationships that might have existed between this area and urban centers at Aix-en-Provence and Massilia (Marseille). Geoarchaeological work informs our appreciation of this enigmatic and dynamic landscape. This supposedly marginal micro-region 15 km to the east of Aix is characterized by a series of erosion surfaces and stable, economically productive plains. This contribution considers the relationship between settlements and the geomorphic system, and makes a first attempt at an assessment of the evolution of organization and management of this landscape. The conclusion to this article reasserts the potential for dynamic and rich discourses that landscape archaeology can engender in the study of period "transitions" and human/environment relationships.
Effect of cloud cover and atmospheric circulation patterns on the observed surface solar radiation in Europe

[1] This study aims at quantifying the most important factors affecting variations in downward surface shortwave radiation (DSW) in Europe including cloud cover and atmospheric circulation patterns. The role of observed cloud cover on DSW was analyzed through generalized linear models using DSW measurements obtained from the Global Energy Balance Archive during 1971–1996. Stations of DSW in Europe were selected to assess how they were affected by clouds. Overall cloud cover had a statistically significant negative relationship and a non-significant positive relationship on DSW for relatively nearby and distant cloud cover stations, respectively. The exception was west-central Europe where a significant negative effect over the whole continent was found suggesting an association with larger cloud structures. This showed that point DSW measurements can be spatially representative for larger scale variability. In line with other studies we found a strong seasonal effect of cloud cover on DSW mainly in northern Europe in spring and summer and in southern Europe in winter and autumn. The North Atlantic Oscillation was most important in winter with a significant negative effect in northern to central Europe and a positive non-significant effect in the south. The Mediterranean Oscillation exhibited mainly a positive effect in winter with significance in southern Europe and non-significance in central Europe. The North Sea Caspian Pattern primarily showed a positive effect with significance in east-central and northern Europe in spring and summer. The interrelationship found between these climatic variables could improve the understanding of a linkage to temperature and precipitation patterns in Europe.
Mixing estimates from a large‐scale hydrographic survey in the North Atlantic

A large‐scale hydrographic survey from 2003 (RV Meteor cruise M59/2) is used to map turbulent mixing by means of eddy diffusivities from finescale shear and strain in the subpolar North Atlantic, covering various hydrographic and bathymetric conditions. Results from the analysis indicate small (O(10−5) m2s−1) diffusivities below the Labrador Sea Water layer at mid‐depth in the open ocean. Higher values exceeding 10−4 m2s−1 are found in the abyss close to rough topography and over the flanks of the Mid‐Atlantic Ridge. The strongest mixing with diffusivities of 10−3 m2s−1 occurs in the Deep Western Boundary Current off Flemish Cap. The results of this study convey the need to map mixing globally from existing sets of CTD/LADCP data as well as its feasibility: the similarities and differences in mixing patterns as compared to other studies indicate that large scale patterns of small scale processes are still not well known and understood.
On the relationship between the causal‐inference and meta‐analytic paradigms for the validation of surrogate endpoints

The increasing cost of drug development has raised the demand for surrogate endpoints when evaluating new drugs in clinical trials. However, over the years, it has become clear that surrogate endpoints need to be statistically evaluated and deemed valid, before they can be used as substitutes of “true” endpoints in clinical studies. Nowadays, two paradigms, based on causal‐inference and meta‐analysis, dominate the scene. Nonetheless, although the literature emanating from these paradigms is wide, till now the relationship between them has largely been left unexplored. In the present work, we discuss the conceptual framework underlying both approaches and study the relationship between them using theoretical elements and the analysis of a real case study. Furthermore, we show that the meta‐analytic approach can be embedded within a causal‐inference framework on the one hand and that it can be heuristically justified why surrogate endpoints successfully evaluated using this approach will often be appealing from a causal‐inference perspective as well, on the other. A newly developed and user friendly R package Surrogate is provided to carry out the evaluation exercise.
Benchmark of thirteen bioinformatic pipelines for metagenomic virus diagnostics using datasets from clinical samples

Metagenomic sequencing is increasingly being used in clinical settings for difficult to diagnose cases. The performance of viral metagenomic protocols relies to a large extent on the bioinformatic analysis. In this study, the European Society for Clinical Virology (ESCV) Network on NGS (ENNGS) initiated a benchmark of metagenomic pipelines currently used in clinical virological laboratories. Methods Metagenomic datasets from 13 clinical samples from patients with encephalitis or viral respiratory infections characterized by PCR were selected. The datasets were analysed with 13 different pipelines currently used in virological diagnostic laboratories of participating ENNGS members. The pipelines and classification tools were: Centrifuge, DAMIAN, DIAMOND, DNASTAR, FEVIR, Genome Detective, Jovian, MetaMIC, MetaMix, One Codex, RIEMS, VirMet, and Taxonomer. Performance, characteristics, clinical use, and user-friendliness of these pipelines were analysed. Results Overall, viral pathogens with high loads were detected by all the evaluated metagenomic pipelines. In contrast, lower abundance pathogens and mixed infections were only detected by 3/13 pipelines, namely DNASTAR, FEVIR, and MetaMix. Overall sensitivity ranged from 80% (10/13) to 100% (13/13 datasets). Overall positive predictive value ranged from 71-100%. The majority of the pipelines classified sequences based on nucleotide similarity (8/13), only a minority used amino acid similarity, and 6 of the 13 pipelines assembled sequences de novo. No clear differences in performance were detected that correlated with these classification approaches. Read counts of target viruses varied between the pipelines over a range of 2-3 log, indicating differences in limit of detection. Conclusion A wide variety of viral metagenomic pipelines is currently used in the participating clinical diagnostic laboratories. Detection of low abundant viral pathogens and mixed infections remains a challenge, implicating the need for standardization and validation of metagenomic analysis for clinical diagnostic use. Future studies should address the selective effects due to the choice of different reference viral databases.
The regional distribution of the dry-snow zone on the Antarctic Peninsula north of 70˚ S

Abstract In order to estimate the contribution of the Antarctic Peninsula to global sea-level rise as a result of the observed warming in this region, the spatial extent of snow-melt-producing areas needs to be quantified. By using the dry-snow line derived from synthetic aperture radar (SAR) imagery as the uppermost limit of frequent or occasional surface melt, an estimation of the spatial extent of areas with non-zero ablation rates is facilitated. Three calibrated RADARSAT ScanSAR mosaics covering the northern Antarctic Peninsula were analyzed applying a threshold of –14 dB to identify the dry-snow line. The area of the dry-snow radar zone was determined to be 23300±2000 km2.Areas affected frequently or occasionally by snowmelt cover 85 000±9000 km2. In addition, the dry-snow line as derived from multi-temporal ERS-1/-2 imagery serves as an indicator of climate variability in the uppermost areas of polar glaciers and ice sheets. The upward shift of the dry-snow line between 1992 and 1998 on the eastern side of the Antarctic Peninsula at 68˚ S is interpreted as a direct response to the increasing number of high-temperature events during the 1991–2000 decade.
Mother-daughter mutual arousal escalation and emotion regulation in adolescence

Emotion dysregulation is a core transdiagnostic risk factor for psychopathology and adolescence may be a sensitive period for the development of emotion regulation. Mothers may socialize emotion dysregulation by engaging in frequent interactions with their adolescents that involve mutual increases in arousal. This study examined mother-adolescent mutual arousal escalation in a conflict discussion task in adolescent girls. Further, we tested associations between mutual arousal escalation and adolescent emotion regulation. Participants comprised 84 adolescent girls (Mage=12.3[0.78]; 69% White) and their biological mothers. Dyads completed a 5m conflict discussion task, during which skin conductance level was collected as a measure of arousal. Adolescent emotion regulation outcomes included self-reported rumination and problem-solving, arousal habituation to a stressful speech task, and real-world use of positive and negative emotion regulation strategies. Multilevel models for distinguishable dyads indicated a significant random effect of time, with individual differences in arousal slope throughout the task for both adolescents and mothers. There were significant fixed and random effects of mother-to-adolescent cross-lagged arousal, indicating that mothers “transmitted” arousal to adolescents on average, and there was significant dyadic variability. Dyadic mutual arousal escalation predicted adolescent rumination, indicating that for dyads high in mutual arousal escalation and high in mutual arousal de-escalation, adolescents reported higher rumination. Mother arousal slope during the conflict task significantly predicted adolescent physiological regulation during the speech task; as mothers exhibited higher slopes on the speech task, adolescent slopes on the speech task were higher, reflecting less habituation. Higher mother-to-adolescent arousal transmission was associated with more use of positive and less use of negative emotion regulation strategies in the real world. Results suggest that mother-adolescent dyads vary in the degree to which they mutually escalate or de-escalate in arousal during stressful interactions, and in the degree to which mothers “transmit” arousal to adolescents. These differences in interaction style appear related to adolescents’ abilities to regulate their emotions. Adolescents in dyads who mutually escalate or de-escalate in arousal report more rumination, which may be indicative of a practiced dysregulatory response in stressful contexts (escalation) or a tendency toward cognitive processes that lead to withdrawal from aversive environments (de-escalation).
impact of light conditions on reading ability following multifocal pseudophakic corrections

Purpose: To examine the impact of light intensity and temperature on reading performance following bilateral pseudophakic multifocal presbyopic correction. Patients and methods: This is a prospective clinic-based trial conducted at the Department of Ophthalmology in the University Hospital of Alexandroupolis, Greece. Three groups of patients were formed (G1: patients with bilateral bifocal implantation, G2: patients with bilateral trifocal implantation, and control group: patients with bilateral pseudophakic monofocal implantation). Reading ability was quantified with the Greek version of MNREAD chart with minimal reading speed at 80 words/min for the following light intensities (25, 50, and 75 Foot-Candles [FC]) and temperatures (3,000, 4,000, and 6,000 K). Preferred light conditions for reading were assessed, as well. ClinicalTrials.gov Identifier: NCT03226561. Results: Control group demonstrated significantly lower reading ability at all light combinations with maximal ability at 75 FC and 6,000 K (0.58 ± 0.18 logMAR). Bifocal group presented a light-dependent reading ability that ranged from 0.45 ± 0.08 logMAR (25 FC and 3,000 K) to 0.40 ± 0.11 logMAR (75 FC and 4,000 or 6,000 K). Trifocal participants presented the best reading ability that was light intensity-independent; however, their performance was reduced at 6,000 K. G1 and G2 preferred primarily intermediate light temperature, while control participants preferred cold light temperature. Conclusion: Multifocal pseudophakic corrections improve reading ability; however, they present variable efficacy according to the light conditions.
Estimating traveltimes and groundwater flow patterns using 3D time-lapse crosshole ERT imaging of electrical resistivity fluctuations induced by infiltrating river water

ABSTRACTThe infiltration of river water into aquifers is of high relevance to drinking-water production and is a key driver of biogeochemical processes in the hyporheic and riparian zone, but the distribution and quantification of the infiltrating water are difficult to determine using conventional hydrological methods (e.g., borehole logging and tracer tests). By time-lapse inverting crosshole ERT (electrical resistivity tomography) monitoring data, we imaged groundwater flow patterns driven by river water infiltrating a perialpine gravel aquifer in northeastern Switzerland. This was possible because the electrical resistivity of the infiltrating water changed during rainfall-runoff events. Our time-lapse resistivity models indicated rather complex flow patterns as a result of spatially heterogeneous bank filtration and aquifer heterogeneity. The upper part of the aquifer was most affected by the river infiltrate, and the highest groundwater velocities and possible preferential flow occurred at shallow t.
An Explainable Intelligence Driven Query Prioritization Using Balanced Decision Tree Approach for Multi-Level Psychological Disorders Assessment

Human emotions affect psychological health to a great level. Positive emotions relate to health improvement; whereas negative emotions may aggravate psychological disorders such as anxiety, stress, and depression. Although there exist several computational methods to predict psychological disorders, most of them provide a black-box view of uncertainty. This research involves developing a novel predictive model for multi class psychological risk recognition with an accurate explainable interface. Standard questionnaires are utilized as data set and a new approach called a Q-Prioritization is employed to drop insignificant questions from the data set. Moreover, a novel balanced decision tree method based on repetitive oversampling is applied for the training and testing of the model. Predictive nature along with its contributing factors are interpreted with three techniques such as permuted feature importance, contrastive explanation, and counterfactual method, which together form a reasoning engine. The prediction outcome generated an impressive performance with an aggregated accuracy of 98.25%. The mean precision, recall, and F-score metric recorded were 0.98, 0.977, and 0.979, respectively. Also, it was noted that without applying Q-Prioritization, the accuracy significantly drops to 90.25%. The error rate observed with our model was only 0.026. The proposed multi-level psychological disorder predictive model can successfully serve as an assistive deployment for medical experts in the effective treatment of mental health.