Miracle-dz/UniFAR-FTUs huggingface dataset:
Altering the Expression in Mice of Genes by Modifying Their 3 (cid:1) Regions

previously developed a “gene titration” method in which homologous recombinationin stem(ES) cells is usedto deleteor duplicatea chosengene at itsnormal chromosomal location without the sequence of the gene product of nearby cis -acting control ele-Masao the ES cells modified in this way have one, two (wild- type), three, or four functional copies of the gene of interest. A linear and strictly proportional relationship between the number of copies of a gene and the steady-state level of its product was observed in mice resulting from several experiments of this type (Krege et al., 1997; Summary Oliver al., 1998). This agrees with previous observations in humans that heterozygotes for a completely Polymorphic differences altering expression of genes nonfunctional mutation usually have close to 50% nor- without changing their products probably underlie hu-mal levels of gene product (Harris, 1970), while trisomic man quantitative traits affecting risks of serious dis-individuals have close to 150% normal levels (Epstein, eases, but methods for investigating such quantitative 1989). Fifty percentexpressionis consequentlyregularly differences in animals are limited. Accordingly, we observed at the mRNA level in mice heterozygous for a have developed a procedure for changing the expres-gene deletion “knock out. ” However, in the three- and sion in mice of chosen genes over a 100-fold range four copy animals, the chromosome with the duplicated while retaining their chromosomal Region for a Target Gene fluorescence of the modified ES cells for seven of our In order to design a modification to obtain a desired tested series of 3 (cid:1) regions with that from cardiomyo-change in the expression of a chosen target gene, it is cytes and trophoblastocytes derived from these ES necessary to compare the “strength” of the natural cells. The rank order of the seven 3 (cid:1) regions in the parent 3 (cid:1) UTR and GRE from the target gene with that of pre- ES cells and in the two types of differentiated cells gen-viously tested 3 (cid:1) regions. We illustrate this aspect of our erated from them is identical.
PULSE PRESSURE FOR PICKING THE OPTIMUM CARDIAC STRATEGY WITH TYPE2 DIABETES AND CORONARY ARTERY DISEASE PATIENTS

: Pulse pressure may be potentially useful for selecting effective cardiac treatment strategies. This study aimed to assess the association between the cardiac treatment strategies and risk of major adverse cardiovascular events (MACE) in patients with type 2 diabetes and coronary artery disease (CAD), based on low or high levels of pulse pressure. We analyzed data from the Bypass Angioplasty Revascularization Investigation 2 Diabetes trial and calculated hazard ratios (HRs) for MACE with 95% confidence intervals (95%CIs) using the Cox proportional hazard model. The risk of MACE in patients with type 2 diabetes and CAD was compared between the early revascularization and medical therapy groups separately in patients with pulse pressures b 60 mmHg (n = 1378) and ≥ 60 mmHg (n= 916). During a maximal follow-up of 6 years, 389 patients experienced MACE. In patients with pulse pressure b 60 mmHg, the risk of MACE was significantly higher in the early revascularization group (HR: 1.37, 95%CI: 1.04– 1.81, P = 0.02) and was specifically and significantly higher in the percutaneous coronary intervention group (HR: 1.66, 95%CI: 1.17–2.34, P = 0.004) than in the medical therapy group. In contrast, the risk of MACE in patients with pulse pressure ≥ 60 mmHg was significantly lower in the early revascularization group (HR: 0.72, 95%CI: 0.53–0.96, P = 0.02) and was specifically lower in the coronary artery bypass graft surgery group (HR: 0.49, 95%CI: 0.30–0.82, P =0.006) than in the medical therapy group. Pulse pressure may be used to determine optimal cardiac treatment strategies in patients with type 2 diabetes and CAD.
Exploring Data Driven Graphics for Interactivity

The goal of rendering in computer graphics is the synthesis of photorealistic images from abstract virtual scene descriptions. Among the many rendering methods, path tracing along with physically accurate material modeling has emerged as the industry standard for photorealistic image synthesis. Path tracing is, however a computationally expensive operation. Moreover, physically accurate material modeling requires iterative parameter tuning and visualization using path tracing. This quickly becomes a bottleneck for the tuning of a large number of parameters found in most physically accurate material models, and artists end up spending a lot of time waiting for path tracing to converge. This dissertation proposes to leverage the learning power of neural networks to plausibly approximate path tracing for: (a) quick material visualization while editing, (b) out-of-the box material recovery using inverse rendering. The traditional workflow for tuning material parameters and visualization is typically followed by modifications to lighting for better understanding the behaviour of the material. We thus incorporate the ability to modify the environment lighting in our neural material visualization framework. This significantly aids in understanding the behaviour of the material thus aiding the process of parameter tuning, which we demonstrate with a user study. Most real-world materials are spatially varying, which is that their behaviour varies across the surface of the geometry. While previous works in this area dealt with uniform materials, we propose improvements for handling spatially varying materials. We design our neural network architecture to be light-weight, having 10× lesser trainable parameters than the state-of-the-art, while also producing better visualizations. We also build a tool to demonstrate real-time parameter tuning and visualization of materials. Finally, we extend the above work to handle general 3D scenes in specific lighting scenarios. This is done by training a small fully connected neural network on a simple scene in the local tangent frame. Training in the local tangent frame decouples geometric complexity from training which implies that the network generalizes to any geometry. We embed this network in a standard path tracer to evaluate direct illumination at each path vertex. We thus not only obtain noise free direct illumination but also out-of-the box gradients of the rendering process, which can be used for inverse rendering. We show that these gradients can be used for plausibly recovering the material of a target scene. We conclude by discussing various practical aspects of our method.
Effect of Play Context on Engagement in Preschool Children with Autism Spectrum Disorder: A Critical Review and Pilot Study

This study reports a critical review and pilot study examining the effects of play context on engagement in preschool children with Autism Spectrum Disorder (ASD). Specifically, the aim of the review and pilot study is to compare gross motor and symbolic play contexts. For the critical review, studies evaluated included one case control study, one mixed group design, and one within groups design. Findings regarding context effects from the critical review were inconclusive. In the pilot study, participation data were gathered from parent-child dyads (n=71) involving preschool children with ASD. Results from the pilot study suggest that a gross motor play context may be more conducive to supporting children with ASD to engage with their caregivers than a symbolic play context.
Metrics for Evaluating Quality of Embeddings for Ontological Concepts

Although there is an emerging trend towards generating embeddings for primarily unstructured data and, recently, for structured data, no systematic suite for measuring the quality of embeddings has been proposed yet. This deﬁciency is further sensed with respect to embeddings generated for structured data because there are no concrete evaluation metrics measuring the quality of the encoded structure as well as semantic patterns in the embedding space. In this paper, we introduce a framework containing three distinct tasks concerned with the individual aspects of ontological concepts: (i) the categorization aspect, (ii) the hierarchical aspect, and (iii) the relational aspect. Then, in the scope of each task, a number of intrinsic metrics are proposed for evaluating the quality of the embeddings. Furthermore, w.r. t. this framework, multiple experimental studies were run to compare the quality of the available embedding models. Employing this framework in future research can reduce misjudgment and provide greater insight about quality comparisons of embeddings for ontological concepts. We positioned our sampled data and code at https://github.com/alshargi/Concept2vec under GNU General Public License v3.0.
AN INVESTIGATION INTO THE EFFECTS OF LEVELS OF LONELINESS AND OPTIMISM AMONG STUDENTS AT THE FACULTY OF SPORTS SCIENCES

The aim of this study is to explore the effects of optimism and loneliness levels of the students at the Faculty of Sports Sciences. For the purposes of data collection, two instruments were used: the ‘UCLA Scale’ which was developed by Russel et al [7] revised by Russel et al [8] and adapted into Turkish by Demir [9]; and the Optimism Scale which was developed by Balcı and Yılmaz [10] in order to explore students’ levels of loneliness and optimism. These questionnaires were administered to a total of 375 students consisting of 224 male and 151 female students. For data analysis, the SPSS statistical packet program was used for frequency analysis, and independent t-tests, one-way ANOVA and Tukey test were run to find out the source of the difference among different groups of participants. In addition, correlation analysis was performed to reveal the relationship between the students’ Levels of Optimism and Loneliness. Significant differences have been seen in the levels of optimism and loneliness among participants according to gender. (p<0,05) According to this, averages of female students are higher than male students in levels of loneliness. In terms of levels of optimism, averages of male student are higher than female students.
Scaling Crowd+AI Sidewalk Accessibility Assessments: Initial Experiments Examining Label Quality and Cross-city Training on Performance

Increasingly, crowds plus machine learning techniques are being used to semi-automatically analyze the accessibility of built environments; however, open questions remain about how to effectively combine the two. We present two experiments examining the effect of crowdsourced data in automatically classifying sidewalk accessibility features in streetscape images. In Experiment 1, we investigate the effect of validated data—which has been voted correct by the crowd but is more expensive to collect—compared with a larger but noisier aggregate dataset. In Experiment 2, we examine whether crowdsourced labeled data gathered in one city can be used as effective training data for another. Together, these experiments contribute to the growing literature in Crowd+AI approaches for semi-automatic sidewalk assessment and help identify pertinent challenges.
A Systematic Review of the De ﬁ nitions, Determinants, and Clinical Outcomes of Antimicrobial De-escalation in the Intensive Care Unit

Antimicrobial de-escalation (ADE) is a strategy to reduce the spectrum of antimicrobials and aims to prevent the emergence of bacterial resistance. We present a systematic review describing the de ﬁ nitions, determinants and outcomes associated with ADE. We included 2 randomized controlled trials and 12 cohort studies. There was considerable variability in the de ﬁ nition of ADE. It was more frequently performed in patients with broad-spectrum and/or appropriate antimicrobial therapy ( P = .05 to .002), when more agents were used ( P = .002), and in the absence of multidrug-resistant pathogens ( P < .05). Where investigated, lower or improving severity scores were consistently associated with ADE ( P = .04 to <.001). The pooled effect of ADE on mortality is protective (relative risk, 0.68; 95% con ﬁ dence interval, .52 – .88). Because the determinants of ADE are markers of clinical improvement and/or of lower risk of treatment failure this effect on mortality cannot be retained as evidence. None of the studies were designed to investigate the effect of ADE on antimicrobial resistance. 19 – 24]. Four studies included shortening the duration of antimicrobial therapy in the de ﬁ nition of ADE [15, 16, 19, 24]. Leone and colleagues [23] used the concept of a “ pivotal ” antimicrobial, usually an extended-spectrum β -lactam, together with an agent used to treat methicillin-resistant Staphylococcus au-reus (MRSA) and a “ companion ” antimicrobial (aminoglycoside or ﬂ uoroquinolone or macrolide). ADE was de ﬁ ned as switching from the pivotal antibiotic to a narrower agent, stopping the companion antibiotic at day 3 of therapy, and ceasing anti-MRSA therapy when not required. None of the studies described the ADE (vs non-ADE) status as rated by blinded investigators.
Evaluating the value of the option to build a new transmission line under demand uncertainty by Jay Sandeep Ghodke

A transmission expansion project is inherently challenging given the large-scale capital commitment needed and the complexity of electric power flow given various uncertain factors ranging from supply and demand as well as cost and price. Hence, it is highly desirable to economically quantify the option/right/permit value to construct a transmission project under uncertainty. Towards this aim, in this paper, we formulate and solve a real option problem to quantify such a construction option when demand shows volatility over time. Specifically, our paper assumes that the demand follows a geometric Brownian motion (gBm) process and shows how the value of the construction option of a transmission line can be derived based on the optimal thresholds of demand to construct or to wait given the optimal power flow calculations and the resulting locational marginal prices. The key features of our model and analysis are illustrated via an extensive numerical example. In particular, this framework shows the economic ramifications of using locational marginal prices as a performance criterion.
90 mg Orally Twice Daily Does Not Inﬂuence Postoperative Morphine Requirements After Major Chest Surgery

BACKGROUND: Cyclooxygenase 2 inhibition has proven analgesic efficacy in a variety of surgical procedures. We postulated that perioperative cyclooxygenase 2 inhibi- tion significantly reduces postoperative morphine requirements after major thoracic surgery and investigated the site of this potential analgesic effect. METHODS: Ninety-two patients participated in this single-center, double-blind, randomized, placebo-controlled, parallel-group trial. Patients between the ages of 18 and 80 yr undergoing a thoracotomy or median sternotomy were randomized to receive either nimesulide or placebo in combination with a standard analgesic regimen perioperatively. Nimesulide was administered orally the evening before surgery and at 12-h intervals for 5 days postoperatively. The primary efficacy variables were morphine consumption and pain scores for the first 48 h postoperatively. The secondary efficacy variable was the effect of nimesulide on cycloox- ygenase activity in cerebrospinal fluid (CSF). RESULTS: Pain scores at rest or with movement, and total morphine consumption for the first 48 h postoperatively, were not statistically different between the groups. The mean difference in total morphine consumption up to 48 h postoperatively between the nimesulide and placebo group was a 9.0 mg reduction (95% CI: (cid:1) 28.9 to 10.9 mg) ( P (cid:2) 0.37). Adjusted mean ( se ) CSF 6-keto-PGF1 (cid:1) (6-keto-PGF1 (cid:1) ) concentrations increased by 54.7 (25.7) pg/mL from preoperatively to Day (cid:3) 2 postoperatively in the placebo group, whereas adjusted mean ( se ) CSF 6-keto-PGF1 (cid:1) concentration decreased by 0.6 pg/mL (18.2 pg/mL) in the nimesulide group. These changes were not statistically different between the groups ( P (cid:2) 0.095). CONCLUSION: Nimesulide, at a dose of 90 mg twice daily in combination with a standard analgesic regimen, does not influence pain scores, morphine require- ments, or CSF prostaglandin levels after major thoracic surgery.
(2016). Diophantine quintuples containing triples of the first kind. Periodica Mathematica 235-242.

We consider Diophantine quintuples { a, b, c, d, e } , sets of integers with a < b < c < d < e the product of any two elements of which is one less than a perfect square. Triples of the ﬁrst kind are sets { A, B, C } with C ≥ B 5 . We show that there are no Diophantine quintuples { a, b, c, d, e } such that { a, b, d } is a triple of the ﬁrst kind.
Separating Procedures and Criteria in A 3-Layer Approach

Computerized guidelines have been utilized for several decades by now. Systems based on computerized-guidelines often intertwine (1) medical knowledge representation, (2) guideline procedures and (3) hospital workflows. This induces several drawbacks. Most prominent problems include non-shareability of the computerized guideline between hospitals, limited accessibility of the computerized guideline for humans, and an unclear, often confusing combination of hospital-specific workflow and guideline-induced control flows. This article proposes a 3-layer modelling approach strictly distinguishing the aforementioned three aspects to overcome the respective problems. We applied the 3-layer approach to the implementation of a guideline-interpreting software module in the context of the Medical Informatics Initiative Germany (here: SMITH Project) and comment on the resulting implications for the software design of that module.
Experiment Design Methods for Development of Simplified Plasma Boundary Model Bachelor

Many physical phenomena in various applications can be computed using the laws of physics. However, these calculations can be computationally expensive. High computational demands are limiting for example when optimizing a physical process and it is needed to be evaluated many times. The goal of this thesis is to find a surrogate model approximating a complex numerical program requiring the least possible amount of evaluations. The main tool used to train the model is active learning in the form of Bayesian optimization. In the first chapters of the thesis, some of the commonly used surrogate models and experiment design methods are introduced. Afterward, plasma boundary modeling is presented as an example of a practical application of surrogate modeling. The result of the thesis is a comparison of selected methods on modeling of plasma momentum loss in tokamak.
Survey: Exploring Disfluencies for Speech-to-Speech Machine Translation

Disfluencies that appear in the transcriptions from automatic speech recognition systems tend to impair the performance of downstream NLP tasks like machine translation. Disfluency removal models can help alleviate this problem. However, the un-availability of labeled data in low-resource languages impairs progress. In this survey paper, we clearly state the problem in hand and the motivation behind doing disflu-ency removal. Next, we discuss speech-to-speech machine translation to understand where disfluency detection fits. Then, we cover the disfluency phenomenon in great detail. We also describe the prior works to solve the disfluency detection problem.
Neural Morphology Analysis - A Survey

Morphology analysis is a foundational NLP task with relevance in language documentation, machine translation, language modeling, etc. Building morphological analyzers is a resource intensive process limiting their availability to a few high web-resource languages. Neural models such as RNNs, transformers, etc have been applied recently to morphology analysis tasks. These meth-ods have shown great improvements over the baselines, especially in a resource scarce scenario. In this survey, we focus on supervised and unsupervised approaches that have been tried for morphology analysis. We also provide a survey of the current state of resources that are available for morphology analysis.
Learning Classifier Systems as Recommender Systems

A multitude of software domains, ranging from e-commerce services to personal digital assistants, rely on recommender systems (RS) to enhance their performance and customer experience. There are several established approaches to RS, including algorithms, namely, collaborative filtering, content-based filtering, and various hybrid systems that use different verticals of data, such as the user’s preferences, the metadata of items to be suggested, etc., to generate recommendations. Contrary to those, we adopt a classifier system to benefit from its rule-based knowledge representation and interwoven learning mechanisms. In this paper, we present our approach and elaborate on its potential use to flexibly and effectively guide a user through the application of an authoring platform.
Reproducibility of the coil positioning in magnet models through magnetic measurements.

— The random part of the integral field harmonics in a series of superconducting magnets has been used in the past to identify the reproducibility of the coil positioning. Using a magnetic model and a MonteCarlo approach, coil blocks are randomly moved and the amplitude that best fits the magnetic measurements is interpreted as the reproducibility of the coil position. Previous values for r.m.s. coil displacements for Nb-Ti magnets range from 0.05 to 0.01 mm. In this paper, we use this approach to estimate the reproducibility in the coil position for Nb 3 Sn short models that have been built in the framework of the FNAL core program (HFDA dipoles) and of the LARP program (TQ quadrupoles). Our analysis shows that the Nb 3 Sn models manufactured in the past years correspond to r.m.s. coil displacements of at least 5 times what is found for the series production of a mature Nb-Ti technology. On the other hand, the variability of the field harmonics along the magnet axis shows that Nb 3 Sn magnets have already reached values similar to thise obtained for Nb-Ti ones.