Miracle-dz/UniFAR-FTUs huggingface dataset:
Machine learning-based event recognition in SiFi Compton camera imaging for proton therapy monitoring

Objective. Online monitoring of dose distribution in proton therapy is currently being investigated with the detection of prompt gamma (PG) radiation emitted from a patient during irradiation. The SiPM and scintillation Fiber based Compton Camera (SiFi-CC) setup is being developed for this aim. Approach. A machine learning approach to recognize Compton events is proposed, reconstructing the PG emission profile during proton therapy. The proposed method was verified on pseudo-data generated by a Geant4 simulation for a single proton beam impinging on a polymethyl methacrylate (PMMA) phantom. Three different models including the boosted decision tree (BDT), multilayer perception (MLP) neural network, and k-nearest neighbour (k-NN) were trained using 10-fold cross-validation and then their performances were assessed using the receiver operating characteristic (ROI) curves. Subsequently, after event selection by the most robust model, a software based on the List-Mode Maximum Likelihood Estimation Maximization (LM-MLEM) algorithm was applied for the reconstruction of the PG emission distribution profile. Main results. It was demonstrated that the BDT model excels in signal/background separation compared to the other two. Furthermore, the reconstructed PG vertex distribution after event selection showed a significant improvement in distal falloff position determination. Significance. A highly satisfactory agreement between the reconstructed distal edge position and that of the simulated Compton events was achieved. It was also shown that a position resolution of 3.5 mm full width at half maximum (FWHM) in distal edge position determination is feasible with the proposed setup.
Symptom-Based Cluster Analysis Categorizes Sjögren's Disease Subtypes and Highlights the Discordance Between Disease Severity and Treatment: an International Cohort Study.

OBJECTIVE Symptom relief is critical for successful drug development in Sjӧgren's. Yet, patient experiences with Sjӧgren's-related symptoms are understudied. Our objective was to determine how pain, dryness, and fatigue, the cardinal symptoms of Sjӧgren's, drive cluster phenotypes. METHODS We used data from the Sjögren's International Collaborative Clinical Alliance (SICCA) registry and a Sjӧgren's Foundation survey. We performed hierarchical clustering by symptoms of dryness, fatigue, and pain. Using international and US cohorts, we performed multiple logistic regression analysis to compare the clusters including differences in symptoms, quality of life (QoL), medication use, and systemic manifestations. RESULTS Four similar clusters were identified among 1,454 SICCA registrants and 2,920 Sjӧgren's Foundation survey participants. The SICCA clusters were: low symptom burden in all categories (LSB; 10% prevalence), dry, low pain (30%), dry, high pain (23%), and high symptom burden in all categories (HSB; 37%). Sjögren's Foundation clusters included: LSB (23%), dry, low pain (14%), dry, high pain (21%), and HSB (42%). The HSB cluster had more total symptoms and lower QoL but lower disease severity than the others. Despite milder laboratory and organ involvement, the HSB cluster received immunomodulatory treatment most often. CONCLUSIONS We identified four symptom-based Sjӧgren's clusters and showed that symptom burden and immunomodulatory use do not correlate with Sjӧgren's end-organ or laboratory abnormalities. Findings highlight a discordance between objective measures and treatments and offer updates to proposed symptom-based clustering approaches.
Electric field aspects in hypoglossal nerve stimulation for obstructive sleep apnea: A bilateral electrophysiological evaluation of unilateral electrode configuration changes

Hypoglossal nerve stimulation is an established treatment option for obstructive sleep apnea in selected patients. A unilateral hypoglossal nerve stimulation system was approved a decade ago, yet the physiological effect of unilateral hypoglossal stimulation on bilateral tongue motion remains unclear. This study examined how electrode configuration, stimulation cuff position, or body mass index influenced the contralateral genioglossus electromyography (EMG) signal. Twenty‐nine patients underwent three EMG recordings in a polysomnographic setting after being implanted with a unilateral hypoglossal nerve stimulator for at least 6 months. The ratio of EMG signals between the ipsi‐ and contralateral sides was evaluated. No difference in EMG signals was demonstrated based on electrode configurations, stimulation‐cuff position, body‐mass‐index, or sleep apnea severity, even in patients with right tongue protrusion only. Our findings may be explained by a significant level of cross‐innervation and by a smaller and less variable circumferential electric field than expected based on prior biophysical models. A patient's individual anatomy needs to be considered during therapy titration in order to achieve an optimal response.
Idaho Nuclear Technology and Engineering Center Low-Activity Waste Process Technology Program FY-98 Status Report

The Low-Activity Waste Process Technology Program at the Idaho Nuclear Technology and Engineering Center (INTEC) anticipates that large volumes of low-level/low-activity wastes will need to be grouted prior to near-surface disposal. During fiscal year 1998, three grout formulations were studied for low-activity wastes derived from INTEC liquid sodium-bearing waste. Compressive strength and leach results are presented for phosphate bonding cement, acidic grout, and alkaline grout formulations. In an additional study, grout formulations are recommended for stabilization of the INTEC underground storage tank residual heels.
In silico folding of hydrophobic peptides that form β‐hairpin structures in solution

Peptides designed with residues that have a high propensity to occur in β‐turns form β‐hairpin structures in apolar as well as in polar organic solvents such as dimethyl sulfoxide (DMSO). Due to limited solubility, their conformations have not been investigated experimentally in water. We have examined the conformations of four of such designed peptides that fold into well‐defined β‐hairpin structures facilitated by β‐turns, in the crystalline state and in solution, by molecular dynamics simulations (MDS). The peptides folded into β‐hairpin structures in water, starting from the fully extended conformation. However, in DMSO, neither folding nor unfolding was observed during MDS, when the starting structures were unfolded and folded, respectively. The lack of folding in DMSO was investigated by constructing folding free energy landscapes by umbrella sampling. The folding free energy landscape is smooth in water, whereas in DMSO, folded and unfolded structures are separated by high‐energy barriers. The folding free energy is less in DMSO compared with water due to a more stable unfolded structure in DMSO compared with water, which in turn is due to stabilisation of the unfolded state by hydrophobic interactions in DMSO. This finding will be helpful to researchers to accurately model and/or design small peptide structures in water and organic solvents.
A Small Molecule Selected from a DNA‐Encoded Library of Natural Products That Binds to TNF‐α and Attenuates Inflammation In Vivo

Abstract Tumor necrosis factor α (TNF‐α) inhibitors have shown great success in the treatment of autoimmune diseases. However, to date, approved drugs targeting TNF‐α are restricted to biological macromolecules, largely due to the difficulties in using small molecules for pharmaceutical intervention of protein–protein interactions. Herein the power of a natural product‐enriched DNA‐encoded library (nDEL) is exploited to identify small molecules that interfere with the protein–protein interaction between TNF‐α and the cognate receptor. Initially, to select molecules capable of binding to TNF‐α , “late‐stage” DNA modification method is applied to construct an nDEL library consisted of 400 sterically diverse natural products and pharmaceutically active chemicals. Several natural products, including kaempferol, identified not only show direct interaction with TNF‐α, but also lead to the blockage of TNF‐α/TNFR1 interaction. Significantly, kaempferol attenuates the TNF‐α signaling in cells and reduces the 12‐O‐tetradecanoylphorbol‐13‐acetateinduced ear inflammation in mice. Structure‐activity‐relationship analyses demonstrate the importance of substitution groups at C‐3, C‐7, and C‐4' of kaempferol. The nDEL hit, kaempferol, represents a novel chemical scaffold capable of specifically recognizing TNF‐α and blocking its signal transduction, a promising starting point for the development of a small molecule TNF‐α inhibitor for use in the clinical setting.
Planar 2D wireframe DNA origami

Two-dimensional (2D) DNA origami is widely used for applications ranging from excitonics to single-molecule biophysics. Conventional, single-layer 2D DNA origami exhibits flexibility and curvature in solution; however, that may limit its suitability as a 2D structural template. In contrast, 2D wireframe DNA origami rendered with six-helix bundle edges offers local control over duplex orientations with enhanced in-plane rigidity. Here, we investigate the 3D structure of these assemblies using cryo–electron microscopy (cryo-EM). 3D reconstructions reveal a high degree of planarity and homogeneity in solution for polygonal objects with and without internal mesh, enabling 10-Å resolution for a triangle. Coarse-grained simulations were in agreement with cryo-EM data, offering molecular structural insight into this class of 2D DNA origami. Our results suggest that these assemblies may be valuable for 2D material applications and geometries that require high structural fidelity together with local control over duplex orientations, rather than parallel duplex assembly.
ADALINE and Its Application in Power Quality Disturbances Detection and Frequency Tracking

Based on some problems of the methods that are used to analyze power quality issues,a kind of artificial neural networks,ADALINE,and its new algorithm for analysis of power quality were presented.The new algorithm has the advantages of being simply calculated and easily implemented through hardware.The simulation results of voltage quality disturbances detection and frequency tracking show that the new ADALINE and its algorithm can be applied to the precise analysis for power quality.
Effect of Different Wheat-Based Diets and Corn Meal Addition on Development Parameters of Ephestia kuehniella (Zeller, 1879) (Lepidoptera: Pyralidae)

Abstract The expansion of Integrated Pest Management (IPM), including biological control, has had several positive consequences for the agricultural environment and participants in the production chain. To enable successful operation and applications of biological control, production of insects used for rearing natural enemies (parasitoids and predators) must be optimized to reduce time and costs and improve production both qualitatively and quantitatively. The present study evaluated the effect of wheat varieties, the main component of artificial diets for Ephestia kuehniella, on the reproductive performance and biological parameters of this flour moth, which is used for mass production of Trichogramma spp. (Hymenoptera: Trichogrammatidae) and other parasitoids and predators. Four varieties of wheat were compared: BRS 327, BRS Marcante, BRS Parrudo, and KBR, with and without the addition of corn E. kuehniella reared on 97% BRS 327 wheat flour + 3% nutritional yeast had the best biological parameters and substitution of corn for about half of the wheat increased the number of eggs per female.
Does emotional processing predict 18-month post-therapy outcomes in the experiential treatment of major depression?

Abstract Objective: This study tested whether emotion-focused therapy’s (EFT) emotion processing theory serves as a predictor of 18-month post-therapy outcomes for major depressive disorder (MDD), independent of experiential therapy received. Method: We examined sequences of emotion episodes using the THEME™ sequential analysis of emotional processing in 55 clients who provided 18-month post-therapy Beck Depression Inventory reports after receiving experiential treatment in the York I and II trials, either emotion-focused or client-centered therapy. Archival Classification of Affective Meaning States (CAMS) ratings of emotion episodes of clients’ working-phase sessions were analyzed using THEME™ sequential analyses of emotions coded during emotion episodes. Results: According to THEME™, poor outcome clients (Beck Depression Inventory at 18 months ≥ 10) expressed more emotion episode sequences containing secondary, or self-protective emotions, than good outcome clients. Good outcome clients expressed more emotion sequences with needs, hurt/grief, and assertive anger than poor outcome clients. Conclusions: EFT sequential emotional processing theory appears to offer good basic assumptions for experiential long-term therapy outcomes after receiving therapy for MDD. Generalization of the theory for other treatments is desired.
Distinct landscapes of deleterious variants in DNA damage repair system in ethnic human populations

Deleterious variants in the DNA damage repair system can cause genome instability and increase cancer risk. The highly ethnic-specific DDR deleterious variation from this study suggests its potential relationship with different disease susceptibility in ethnic human populations. Deleterious variants in DNA damage repair (DDR) system can cause genome instability and increase cancer risk. In this study, we analyzed the deleterious variants in DDR system in 16 ethnic human populations. From the genetic variants in 169 DDR genes involved in nine DDR pathways collected from 158,612 individuals of different ethnic background, we identified 1,781 deleterious variants in 81 DDR genes in eight DDR pathways (https://genemutation.fhs.um.edu.mo/dbddr-global/). Our analysis showed although the quantity of deleterious variants was loaded at a similar level, the landscape of the variants differed substantially among different populations that two-third of the variants were present in single ethnic populations, and the rest was mostly shared between the populations with closer geographic and genetic relationship. The highly ethnic-specific DDR deleterious variation suggests its potential relationship with different disease susceptibility in ethnic human populations.
Current Status and Challenges of Analytical Methods for Evaluation of Size and Surface Modification of Nanoparticle-Based Drug Formulations

The present review discusses the current status and difficulties of the analytical methods used to evaluate size and surface modifications of nanoparticle-based pharmaceutical products (NPs) such as liposomal drugs and new SARS-CoV-2 vaccines. We identified the challenges in the development of methods for (1) measurement of a wide range of solid-state NPs, (2) evaluation of the sizes of polydisperse NPs, and (3) measurement of non-spherical NPs. Although a few methods have been established to analyze surface modifications of NPs, the feasibility of their application to NPs is unknown. The present review also examined the trends in standardization required to validate the size and surface measurements of NPs. It was determined that there is a lack of available reference materials and it is difficult to select appropriate ones for modified NP surface characterization. Research and development are in progress on innovative surface-modified NP-based cancer and gene therapies targeting cells, tissues, and organs. Next-generation nanomedicine should compile studies on the practice and standardization of the measurement methods for NPs to design surface modifications and ensure the quality of NPs.
Constructing Program Management Framework A System of Systems Approach

Abstract — Programs are aimed at achieving long term objectives that create value to stakeholders. They consist of a portfolio of projects, each of which aims at achieving specific sub-goals. A program emerges as a system of systems (SoS) when these projects are connected in a systemic way to accomplish program objectives. This entails that programs have an architecture that defines how the various projects interact to accomplish the overall objectives. Current program management approaches, however, largely treat programs as a collection of projects that are managed operationally to optimize outcomes at each level, rather than as a system to be architected. This paper develops a systemic architecture for programs in terms of three interconnected facets: value realization, program construction and program execution, and highlights the role of program worldview in this. Each of these facets brings out some aspects of the way in which projects relate to each other within a program. We propose an iterative framework in which models are developed for addressing each facet, but there is also an overall structure of activity and information flows that facilitates interplay and co-evolution of the models. The result is a holistic approach to managing programs as a system of systems, at a level over and above project management.
Semantic Modeling of Bridge Deterioration Knowledge for Supporting Big Bridge Data Analytics

A big size of bridge data is being constantly generated—from a variety of distributed sources and in heterogeneous formats—in the form of national bridge inventory (NBI) data, national bridge elements (NBE) data, bridge inspection and maintenance reports, traffic data, etc. Big bridge data analytics open unprecedented opportunities to leverage this large amount of data for improved bridge deterioration prediction and understanding, and enhanced maintenance decision making. In this paper, the authors propose a big bridge data analytics framework that consists of: (1) semantic data/information extraction and integration, (2) semantic data/information analysis and mining, and (3) semantic data/information retrieval and visualization. The big size of the data, in addition to it being scattered and heterogeneity of meaning and format, adds to the challenge of data integration and analysis. As such, at the cornerstone of this framework is an ontology of bridge deterioration knowledge, which aims to facilitate the semantic integration and analysis of the data based on content and domain-specific meaning, and to bridge the terminology gap across different sources. This paper focuses on providing an overview of the framework for big bridge data analytics and presenting the proposed bridge deterioration ontology as the first step towards implementing this framework.
A Method To Select Goals, Indicators and Strategies for IT Services

Background: Measurement is a key process to support organizations in management and improvement of processes, products and services. Indicators are measures used to monitor whether a goal is reached, increasing feedback and objectivity on judgment and helping organizations to focus attention and effort on what matters. IT services literature, such as libraries, frameworks, standards, and maturity models, requires proper identification of critical business process and definition of relevant measures to support decision-making. However, there is no clear direction about what should be those critical business processes and indicators. IT service departments often spend time and effort measuring without being sure about what the measurement results represent and organizations consider the indicators selection as a difficult task. Aims: We conducted this work aiming to answer the research question: “How to support selection of IT services indicators in different organizational levels and aligned to business goals? ” Method: Considering this scenario, we proposed SINIS, a method to help organizations select indicators for IT services in several levels in alignment to business goals. SINIS was created based on concepts from process improvement models and approaches related to IT Services Management. We evaluated SINIS in the IT Infrastructure and the IT Security areas of a global large company. Results: By using SINIS IT Infrastructure was able to define indicators and an appropriate set of strategies aligned with IT Service goals in which teams could focus work and IT Security was able to better understand and document indicators, associate them to business goals and strategies and discard those ones that were not considered useful. Conclusion: SINIS was evidenced as applicable to different IT Service areas, supporting definition of strategies and indicators for members to work on that could help attending IT service and business goals, instead of working in several and unfocused initiatives.
A Different Age for Leadership, Part 2

This is Part 2 of a 2-part article on the new andemerging characteristics and elements of leadershipfor changing, fast-paced organizations.As we leavethe 20th century workplace and are increasingly dri-ven by innovation and technological transformation,new roles are demanded from everyone.Leadershipexpression now calls for a different emphasis andskill-set from those that predominated in the past.Thefirst article (February 2003) focused on the context ofleadership affecting what leaders do and how theymust now behave.This article centers on the activitiesof leadership and the new learning and skill-set devel-opment that will increasingly be required of l eaders ina fundamentally altered work environment.Dramatically changing times have given leaders amore demanding and vital role to play in healthcare.Leaders need a clear vision of the direction ofchange and skill in identifying and responding tochange.
The Underwater Camera Calibration

In the underwater environment, the cameras are positioned in the waterproof capsule with flat glass interface, the direction of light propagation will be changed due to refraction in such multi-media environment. Making use of the pinhole camera model in this situation will cause error. So it is necessary to build new camera model and calibrate the camera correctly during the underwater image processing. In this paper, we analyze the refraction effect, and then build a modified camera model. Based on this model, we propose an underwater camera calibration algorithm, and complete the comparative experiments of camera calibration. The result of experiments shows that this underwater camera system can be calibrated properly and characterized the process of underwater imaging.
N ATURAL L ANGUAGE I NTERACTIVE I NTERFACE FOR SQL Q UERY G ENERATION

We contribute nalini, an natural-language based interactive interface for SQL query generation. Motivated by a lack of usability of existing systems, nalini was built with the intention of using it for complex query generation. The interface allows users to use natural language fragments with minimal structure; users separately describe each desired column in the output table and can optionally describe additional filters. We evaluated nalini with a first-use study with five participants, where participants were asked to generate queries from the TPC-H decision support benchmark. Our study showed that users were able to use nalini to generate complex queries, including TPC-H queries which cannot be generated by any of the leading natural-language-to-SQL tools, and points to promising areas of future work.