Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of public and mental health of medical staff in medical professional environment using random forest model

The objective is to investigate, using the random forest method, the factors that influence the psychological status of primary care practitioners in a professional medical environment. To rank and assess the significance of independent variables, a random forest model was used. Finally, a regression model was created based on the variables screened and logistic regression. During the period of newly developing infectious diseases, the majority of primary medical personnel experienced psychological issues. The PHQ-9 total score model of depression showed the smallest out-of-bag error rate when four independent factors were examined. When there were five independent components, the Anxiety screening Scale (GAD-7) total score model had the lowest out-of-bag error rate. The somatization Symptom Self-rating Scale (SSS) total score model exhibited the lowest out-of-bag error rate when there was only one independent variable. Those with high viral exposure were 4.35 times more likely to develop depression than those with low viral exposure, according to the PHQ-9 multivariate Logistic Regression model. Those with high viral exposure were 3,8 times more likely to develop generalized anxiety disorder than those with low viral exposure, according to a multivariate logistic regression model applying the Gad-7 scale. A multivariate logistic regression model of the SSS scale revealed that those with a bachelor's degree were 7.85 times more likely to acquire somatization symptoms than those with an associate's degree or less. Because it has a high reference value for relevance ranking and variable screening, evaluating data with the Random Forest model and Logistic Regression is an efficient process.
Go-to-Controller is Better: Efficient and Optimal LPM Caching with Splicing

Data center networks must support huge forwarding policies as they handle the traffic of the various tenants. Since such policies cannot be stored within the limited memory available at commodity switches, SDN controllers can manage the memory available at the switch as a cache, updating and changing the forwarding rules in the cache according to the policy and workloads dynamics. Most policies, such as Longest-prefix-match (LPM) policies, include dependencies between the forwarding rules, which introduce consistency constraints on the structure of the cached content, affecting the performance in terms of throughput and delay. Previous work suggested the concept of splicing to address such deficiencies, where modified Go-to-Controller rules can be inserted into the cache to improve performance while maintaining consistency. We present the first optimal algorithm for determining the cache content with splicing, as well as several efficient heuristics with some performance guarantees. We evaluate our solutions using traces derived from real systems and traffic, and show that splicing can reduce the cache miss ratio by as much as 30%, without increasing the cache size. We further propose a new metric which can provide a quick estimate as to the potential benefits of splicing compared to classical LPM-caching. The full version of our work appeared in [2].
AcTrak: Controlling a Steerable Surveillance Camera using Reinforcement Learning

Steerable cameras that can be controlled via a network, to retrieve telemetries of interest have become popular. In this paper, we develop a framework called AcTrak, to automate a camera’s motion to appropriately switch between (a) zoom ins on existing targets in a scene to track their activities, and (b) zoom out to search for new targets arriving to the area of interest. Specifically, we seek to achieve a good trade-off between the two tasks, i.e., we want to ensure that new targets are observed by the camera before they leave the scene, while also zooming in on existing targets frequently enough to monitor their activities. There exist prior control algorithms for steering cameras to optimize certain objectives; however, to the best of our knowledge, none have considered this problem, and do not perform well when target activity tracking is required. AcTrak automatically controls the camera’s PTZ configurations using reinforcement learning (RL), to select the best camera position given the current state. Via simulations using real datasets, we show that AcTrak detects newly arriving targets 30% faster than a non-adaptive baseline and rarely misses targets, unlike the baseline which can miss up to 5% of the targets. We also implement AcTrak to control a real camera and demonstrate that in comparison with the baseline, it acquires about 2× more high resolution images of targets.
A 3-D finite element perturbational method for determining saturated values of transformer winding including experimental verification

A method is presented in this paper for the calculation of saturated transformer winding inductances. The method is mainly based on an energy perturbation technique in conjunction with non linear three dimensional finite element vector potential field solutions. The concepts of apparent, effective and incremental inductances were utilized in the methodology presented. The method presented was successfully applied in the calculation of apparent, effective and incremental inductance values of the primary winding of a single phase transformer. Very good agreement between calculated and measured values of inductance was accomplished. The work presented provides methodologies by which one would be able to determine, in conjunction with nonlinear three dimensional field solutions, these values of inductances. These inductance values are very important in the dynamic analysis of electrical devices, steady state calculation as well as energy storage and other related analysis and preformance studies.
3D refraction-corrected transmission reconstruction for 3D ultrasound computer tomography

Speed of sound imaging is an important modality used in medical ultrasound applications. We developed a 3D ultrasound computer tomograph (3D USCT) which is capable of reflection and transmission tomography. Most 3D tomography reconstruction methods like the algebraic reconstruction technique rely on the assumption that the transmission rays propagate straightly from emitter to receiver, which is not valid for ultrasound. Due to refractions in the tissue the rays are bent rather than straight. To overcome this problem we use a 3D Eikonal solver that calculates the bent ray paths for the transmission pulses and include it into our Compressive Sampling reconstruction framework. Using an iterative scheme we show results for synthetic and real data. The shape and the outline of the phantoms reconstructed with the bent-ray method match the reflection reconstructions better and for synthetic data the speed of sound is closer to the speed of sound in the phantom by approximately 1.2 m/s.
Two-layer hydraulics: a functional approach

A new approach for investigating two-layer hydraulic exchange flows in channels is introduced. The approach is based on the functional formalism of Gill (1977) and applied to the flow through a contraction in width and to flow over a simple sill. The sill geometry is an extension of that looked at by earlier workers, in particular Farmer & Armi (1986) who used a Froude-number-plane approach. In the present paper a simple relationship between the composite Froude number and the hydraulic functional is derived, though the functional approach may also be applied to channels where a Froude number is not readily defined. The ability to trace roots of this functional from one reservoir to the other is a prerequisite for the flow to be realizable. Two hydraulic transitions are required for the flow to be fully controlled and the exchange flow rate to be maximal. If only one hydraulic transition is present, the flow is governed by the conditions in one of the reservoirs and the exchange flow rate is found to be submaximal. The flow along a channel is found to be very sensitive to small departures from symmetry about a horizontal plane. The response of the interface to the introduction of a net (barotropic) flow is found to be a discontinuous function of the strength of the forcing for some range of sill heights.
Speculative protocols for actively replicated transactional systems

Nowadays, the role of transactions has become twofold: they are used in order to guarantee consistency and atomicity in applications manipulating data; they are used as a means to synchronize the activities of threads working concurrently within any software layer. Overall, the concept of transaction, historically related to support data manipulation in the context of database systems, has been widened so to encapsulate synchronization aspects in the context of parallel and concurrent applications. The latter aspect found its expression via Software Transactional Memory (STM) technologies, which have been oriented to mask the complexity of synchronization to the application programmers, thus moving along the path of bringing the power of multi/many-core architectures into the hand of ordinary, non-specialized, software developers. Such a widened scope of transactions, together with significant technological innovations possibly impacting the execution profile/cost of traditional database transactions (e.g. the advent of SSD storage systems) and the level of transaction parallelism (e.g. the advent of many-core architectures), raise the need for reconsidering the design of protocols supporting fault tolerance. In this thesis, I focus on fault tolerant protocols based on the active replication paradigm, which is done by systematically exploiting speculative computation approaches. More in detail, I worked on innovative speculative transactional replication protocols relying on Optimistic Atomic Broadcast group communication primitives, which have been used as a building block for replicas coordination. Some proposed results are mostly oriented to theory, while others have a more strict relation with pragmatic aspects associated with the design/implementation of replicated transactional systems. Most of the material presented in this document can also be found in the following technical articles:
Knöpfologie in der Dopplersonografie

Zusammenfassung Für eine optimale sonografische Dopplerbildgebung müssen die Geräteeinstellungen an die spezielle Anwendung, patientenindividuelle Gegebenheiten und die Sehgewohnheiten des Untersuchers adaptiert werden. Dieser Beitrag ermöglicht dem Anwender, „sein“ Gerät vom Einschalten über die Dopplerbildoptimierung bis zur Speicherung immer gut handhaben zu können – ohne alle technischen oder physikalischen Details hinter den „Knöpfen“ zu kennen.
This paper is included in the Proceedings of the 21st USENIX Conference on File and Storage Technologies.

Deep learning training (DLT) applications exhibit unique I/O workload behaviors that pose new challenges for storage system design. DLT is I/O intensive since data samples need to be fetched continuously from a remote storage. Accelera-tors such as GPUs have been extensively used to support these applications. As accelerators become more powerful and more data-hungry, the I/O performance lags behind. This creates a crucial performance bottleneck, especially in distributed DLT. At the same time, the exponentially growing dataset sizes make it impossible to store these datasets entirely in memory. While today’s DLT frameworks typically use a random sampling policy that treat all samples uniformly equally, recent findings indicate that not all samples are equally important and different data samples contribute differently towards improving the accuracy of a model. This observation creates an opportunity for DLT I/O optimizations by exploiting the data locality enabled by importance sampling. To this end, we design and implement S HADE , a new DLT-aware caching system that detects fine-grained importance variations at per-sample level and leverages the variance to make informed caching decisions for a distributed DLT job. S HADE adopts a novel, rank-based approach, which captures the relative importance of data samples across different mini-batches. S HADE then dynamically updates the importance scores of all samples during training. With these techniques, S HADE manages to significantly improve the cache hit ratio of the DLT job, and thus, improves the job’s training performance. Evaluation with representative computer vision (CV) models shows that S HADE , with a small cache, improves the cache hit ratio by up to 4 . 5 × compared to the LRU caching policy.
On the Spiral Structure of NGC 5248: An Analytic Approach

An improved nonlinear asymptotic theory of spiral density waves is developed. It extends the theory developed by Yuan & Kuo to a global theory, not just one limited to the vicinity of the resonance. It can then be applied to the recent high-resolution observations of CO and HST NICMOS of nearby spiral galaxies. As an example, we apply the theory to the nearby grand-design spiral galaxy NGC 5248, which has excellent CO observations in the central regions and exhibits a continuous optical spiral pattern from about 7 kpc to about 100 pc. Using the improved nonlinear asymptotic theory, we confirm the earlier results that the inner two-arm spiral structure of NGC 5248 is driven by a slowly rotating bar potential at the outer inner Lindblad resonance and is a continuation of the outer optical spiral arms. Using the new theory, we calculate the streamlines, surface density, and line-of-sight velocity contours of the bar-driven flow in the central gas disk, and these results are in good agreement with the observations.
Syndapin Regulates the RAP-1 GTPase to Control Endocytic Recycling via RHO-1 and Non-Muscle Myosin II

After endocytosis, many plasma membrane components are recycled via narrow-diameter membrane tubules that emerge from early endosomes to form recycling endosomes, eventually leading to their return to the plasma membrane. We previously showed that the F- BAR and SH3 domain Syndapin/PACSIN-family protein SDPN-1 is required in vivo for basolateral endocytic recycling in the C. elegans intestine. Here we sought to determine the significance of a predicted interaction between the SDPN-1 SH3 domain and a target sequence in PXF-1/PDZ- GEF1/RAPGEF2, a known exchange factor for Rap-GTPases. We found that endogenous mutations we engineered into the SDPN-1 SH3 domain, or its binding site in the PXF-1 protein, interfere with recycling in vivo, as does loss of the PXF-1 target RAP-1. Rap-GTPases have been shown in several contexts to negatively regulate RhoA activity. Our results show that RHO- 1/RhoA is enriched on SDPN-1 and RAP-1 positive endosomes in the C. elegans intestine, and loss of SDPN-1 or RAP-1 elevates RHO-1(GTP) levels on intestinal endosomes. Furthermore, we found that depletion of RHO-1 suppressed sdpn-1 mutant recycling defects, indicating that control of RHO-1 activity is a key mechanism by which SDPN-1 acts to promote endocytic recycling. RHO-1/RhoA is well-known for controlling actomyosin contraction cycles, although little is known of non-muscle myosin II on endosomes. Our analysis found that non-muscle myosin II is enriched on SDPN-1 positive endosomes, with two non-muscle myosin II heavy chain isoforms acting in apparent opposition. Depletion of nmy-2 inhibited recycling like sdpn-1 mutants, while depletion of nmy-1 suppressed sdpn-1 mutant recycling defects, indicating actomyosin contractility in controlling recycling endosome function.
New Features Surrounding the Cdc42-Ste20 Module that Regulates MAP Kinase Signaling in Yeast

Mitogen-activated protein kinase (MAPK) pathways regulate multiple cellular responses, including the response to stress and cell differentiation, and are highly conserved across eukaryotes from yeast to humans. In yeast, the canonical activation of several MAPK pathways includes the interaction of the small GTPase Cdc42p with the p21-activated kinase (PAK) Ste20p. We recently found that the active conformation of Cdc42p is regulated by turnover, which impacts the activity of the pathway that regulates filamentous growth (fMAPK). Here, we show that Ste20p is turned over by the 26S proteasome. Ste20p was stabilized when bound to Cdc42p, presumably to sustain MAPK pathway signaling. Ste20p is a major conduit by which signals flow through the fMAPK pathway; however, by genetic approaches we also identified a Ste20p-independent branch of the fMAPK pathway. Ste20p-dependent signaling required the 14-3-3 proteins, Bmh1p and Bmh2p, while Ste20p-independent signaling required the fMAPK pathway adaptor and Cdc42p-interacting protein, Bem4p. Ste20p-independent signaling was inhibited by one of the GTPase-activating proteins for Cdc42p in the fMAPK pathway, Rga1p, which also dampened basal but not active fMAPK pathway activity. Finally, the polarity adaptor and Cdc42p-interacting protein, Bem1p, which also regulates the fMAPK pathway, interacts with the tetra-span protein Sho1p, connecting a sensor at the plasma membrane to a protein that regulates the GTPase module. Collectively, these data reveal new regulatory features surrounding a Rho-PAK module that may extend to other pathways that control cell differentiation.
Rotamer Density Estimator is an Unsupervised Learner of the Effect of Mutations on Protein-Protein Interaction

Protein-protein interactions are crucial to many biological processes, and predicting the effect of amino acid mutations on binding is important for protein engineering. While data-driven approaches using deep learning have shown promise, the scarcity of annotated experimental data remains a major challenge. In this work, we propose a new approach that predicts mutational effects on binding using the change in conformational flexibility of the protein-protein interface. Our approach, named Rotamer Density Estimator (RDE), employs a flow-based generative model to estimate the probability distribution of protein side-chain conformations and uses entropy to measure flexibility. RDE is trained solely on protein structures and does not require the supervision of experimental values of changes in binding affinities. Furthermore, the unsupervised representations extracted by RDE can be used for downstream neural network predictions with even greater accuracy. Our method outperforms empirical energy functions and other machine learning-based approaches.
The influence of Sex on microRNA expression in Human Skeletal Muscle

Introduction Sex differences in microRNA (miRNA) expression profiles have been found across multiple tissues. Skeletal muscle is one of the top tissues that underpin sex-based differences, yet there is limited research into whether there are sex differences in miRNA expression in skeletal muscle. Further, there is limited literature investigating potential differences between males and females in skeletal muscle miRNA expression following exercise, a well-known modulator of miRNA expression. Therefore, the aim of this study was to investigate the effect of sex on miRNA expression in skeletal muscle at baseline and after an acute bout of exercise. Methods MiRNAs were measured using Taqman®miRNA arrays in skeletal muscle of 42 healthy participants from the GeneSMART study (24 males and 20 females aged 18-45 yrs). Differentially expressed miRNAs were identified using mixed linear models adjusted for age. Experimentally validated miRNA gene targets enriched in skeletal muscle were identified in-silico. Over representation analysis was conducted to identify enriched pathways. TransmiR V.2 was used to identify transcription factor (TF)-miR regulatory networks using CHIP-derived data. We further profiled the effects of two sex-biased miRNAs overexpressed in human primary muscle cells lines derived from male and female donors to understand the transcriptome targeted by these miRNAs and investigate and potential sex-specific effects. Results A total of 80 miRNAs were differentially expressed in skeletal muscle between the sexes, with 61 miRNAs responding differently to the exercise between the sexes. Sex-biased miRNA gene targets were enriched for muscle-related processes including proliferation and differentiation of the muscle cells and numerous metabolic pathways, suggesting that miRNAs are playing a role in programming sex differences in skeletal muscle. Over-expression of sex-biased miRNAs miRNA-30a and miRNA-30c resulted in profound changes to gene expression profiles that were partly specific to the sex of the cell donor in human primary skeletal muscle cells. Conclusion We found sex-differences in the expression profile of skeletal muscle miRNAs at baseline and in response to exercise. These miRNAs target regulatory pathways essential to skeletal muscle development and metabolism, suggesting that miRNAs play a profound but highly complex role in programming sex-differences in the skeletal muscle phenotype.
Comparative analysis of SQUAMOSA PROMOTER BINDING PROTEIN-LIKE (SPL) gene family between bryophytes and seed plants

SQUAMOSA-PROMOTER BINDING PROTEIN-LIKE (SPL) genes encode plant-specific transcription factors which have been found to be conserved in green plants lineage. SPL proteins are important regulators of diverse plant developmental processes in bryophytes and vascular plants. In our study, we took advantage of available genome sequences of representatives of each bryophyte clade to investigate the relationships of SPL genes between bryophytes and model angiosperm Arabidopsis thaliana. We have identified four SPL genes in each of the two hornworts species, Anthoceros agrestis and Anthoceros punctatus, what is similar to the set of SPL genes present in the liverwort Marchantia polymorpha. Thus, the analyzed hornworts and liverwort genomes encode a minimal set of SPL genes in comparison to other land plants that may resemble an archetype of SPL genes present in the ancestor of land plants. The phylogenetic analysis revealed the presence of four SPL groups. Comparative gene structure analysis showed that SPLs share similar exon-intron organization within the same phylogenetic group with some exceptions in hornworts. While we have identified conserved protein motifs between bryophytes and Arabidopsis in three out of four phylogenetic groups, the motif content differed explicitly in the fourth group. Since current understanding of SPL genes mostly arises from seed plants, the presented comparative and phylogenetic analysis will provide better understanding of SPL gene family from the representatives of the oldest living land plants.
The formation and initial evolution of protostellar disks

The formation and evolution of an accretion disk formed during the collapse of a rotating cloud core are considered. The effect of the usual turbulent alpha-viscosity as well as the effective viscosity due to self-gravitation in the disk are taken into account. For observed values of the cloud's initial rotation rates, and for reasonable estimates of the efficiency of the various processes, it is found that the disks so formed are large (radii several hundred to a few thousand AU), relatively massive (comparable in mass to the central star), and long-lived (tens of infall time scales). 71 refs.
Operatives Management von Adnextumoren

SchülerRaumforderungen im Bereich der Adnexe stellen häufige Gründe für eine Konsultation eines Gynäkologen dar. Oftmals fällt die Einordnung der Befunde und somit die Festlegung des weiteren Vorgehens schwer. Im Folgenden werden verschiedene Tumoren im Bereich der Adnexe vorgestellt. Die entsprechenden diagnostischen und therapeutischen Strategien werden dargestellt und bieten einen Handlungsalgorithmus für den klinischen Alltag.