Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of transgene insertion loci and copy number on Dnmt3L gene silencing through antisense transgene-derived PIWI-interacting RNAs

PIWI-interacting RNAs (piRNAs), which are germ cell-specific small RNAs, are essential for spermatogenesis. In fetal mouse germ cells, piRNAs are synthesized from sense and antisense RNAs of transposable element sequences for retrotransposon silencing. In a previous study, we reported that transgenic mice expressing antisense-Dnmt3L under the control of the Miwi2 promoter (Tg-Miwi2P-asDnmt3L) exhibited piRNA-mediated DNMT3L down-regulation. In this study, two transgene integration loci (B3 and E1) were identified on chromosome 18 of the Tg-Miwi2P-asDnmt3L mice; these loci were weak piRNA clusters. Crossbreeding was performed to obtain mice with the transgene cassette inserted into a single locus. DNMT3L was silenced and spermatogenesis was severely impaired in mice with the transgene cassette inserted at the B3 locus (Tg-B mice). In contrast, spermatogenesis in mice bearing the transgene at the E1 locus (Tg-E mice) was normal. The number of piRNAs for Dnmt3L in Tg-B mice was eightfold higher than that in Tg-E mice. Therefore, both gene silencing and impaired spermatogenesis depended on the transgene copy number rather than on the insertion loci. Additionally, the endogenous Dnmt3L promoter was not methylated in Tg mice, suggesting that Dnmt3L silencing was caused by post-transcriptional gene silencing. Based on these data, we discuss a piRNA-dependent gene silencing mechanism against novel gene insertions.
Removal of movement-induced EEG artifacts: current state of the art and guidelines

Objective: Electroencephalography (EEG) is a non-invasive technique used to record cortical neurons’ electrical activity using electrodes placed on the scalp. It has become a promising avenue for research beyond state-of-the-art EEG research that is conducted under static conditions. EEG signals are always contaminated by artifacts and other physiological signals. Artifact contamination increases with the intensity of movement. Approach: In the last decade (since 2010), researchers have started to implement EEG measurements in dynamic setups to increase the overall ecological validity of the studies. Many different methods are used to remove non-brain activity from the EEG signal, and there are no clear guidelines on which method should be used in dynamic setups and for specific movement intensities. Main results: Currently, the most common methods for removing artifacts in movement studies are methods based on independent component analysis. However, the choice of method for artifact removal depends on the type and intensity of movement, which affects the characteristics of the artifacts and the EEG parameters of interest. When dealing with EEG under non-static conditions, special care must be taken already in the designing period of an experiment. Software and hardware solutions must be combined to achieve sufficient removal of unwanted signals from EEG measurements. Significance: We have provided recommendations for the use of each method depending on the intensity of the movement and highlighted the advantages and disadvantages of the methods. However, due to the current gap in the literature, further development and evaluation of methods for artifact removal in EEG data during locomotion is needed.
The HUNT study: Association of comorbidity clusters with long‐term survival and incidence of exacerbation in a population‐based Norwegian COPD cohort

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease often viewed as part of a multimorbidity complex. There is a need for better phenotyping of the disease, characterization of its interplay with other comorbidities and its association with long‐term outcomes. This study aims to examine how clusters of comorbidities are associated with severe exacerbations and mortality in COPD.
Beyond words: Conceptual framework for the study and practice of hypnotherapeutic imagery

ABSTRACT This paper provides a conceptual framework for the study and clinical application of hypnotherapeutic imagery (HTI). Using the grounded theory method of conceptual analysis, a unified theoretical framework is constructed from a multidisciplinary review of literature (i.e., this new theory is based on the collection and analysis of independently sourced data). The aim is to enumerate the chorographical features of HTI simulations within the mental landscape, rather than seeking to predict them. This is achieved using a combination of ontological, epistemological, and methodological inquires. Because mental simulation is both symptomatic of mental disorders and a psychotherapeutic agent, used across various treatment modalities, an attempt is made to isolate those variables that differentiate HTI from other instances of mental simulation. Lastly, applied principles from multiple disciplines are used to formulate HTI methodology designed to effectively enhance intuitive understanding and unconscious problem-solving.
Autologous haematopoietic stem cell transplantation versus low‐dose immunosuppression in secondary–progressive multiple sclerosis

Effectiveness of autologous haematopoietic stem cell transplantation (AHSCT) in relapsing–remitting multiple sclerosis (MS) is well known, but in secondary–progressive (SP)‐MS it is still controversial. Therefore, AHSCT activity was evaluated in SP‐MS using low‐dose immunosuppression with cyclophosphamide (Cy) as a comparative treatment.
Chest computed tomography features of heart failure: A prospective observational study in patients with acute dyspnea

Background Pulmonary congestion is a key component of heart failure (HF) that chest computed tomography (CT) can detect. However, no guideline describes which of many anticipated CT signs are most associated with HF in patients with undifferentiated dyspnea. Methods In a prospective observational single-center study, we included consecutive patients ≥ 50 years admitted with acute dyspnea to the emergency department. Patients underwent immediate clinical examination, blood sampling, echocardiography, and CT. Two radiologists independently evaluated all images. Acute HF (AHF) was adjudicated by an expert panel blinded to radiology images. LASSO and logistic regression identified the independent CT signs of AHF. Results Among 232 patients, 102 (44%) had AHF. Of 18 examined CT signs, 5 were associated with AHF (multivariate odds ratio, 95% confidence interval): enlarged heart (20.38, 6.86–76.16), bilateral interlobular thickening (11.67, 1.78–230.99), bilateral pleural effusion (6.39, 1.98–22.85), and increased vascular diameter (4.49, 1.08–33.92). Bilateral ground-glass opacification (2.07, 0.95–4.52) was a consistent fifth essential sign, although it was only significant in univariate analysis. Eighty-eight (38%) patients had none of the five CT signs corresponding to a 68% specificity and 86% sensitivity for AHF, while two or more of the five CT signs occurred in 68 (29%) patients, corresponding to 97% specificity and 67% sensitivity. A weighted score based on these five CT signs had an 0.88 area under the curve to detect AHF. Conclusions Five CT signs seem sufficient to assess the risk of AHF in the acute setting. The absence of these signs indicates a low probability, one sign makes AHF highly probable, and two or more CT signs mean almost certain AHF.
Racial justice allyship requires civil courage: A behavioral prescription for moral growth and change.

In racialized societies, race divides people, prioritizes some groups over others, and directly impacts opportunities and outcomes in life. These missed opportunities and altered outcomes can be rectified only through the deliberate dismantling of explicit, implicit, and systemic patterns of injustice. Racial problems cannot be corrected merely by the good wishes of individuals-purposeful actions and interventions are required. To create equitable systems, civil courage is vital. Civil courage differs from other forms of courage, as it is directed at social change. People who demonstrate civil courage are aware of the negative consequences and social costs but choose to persist based on a moral imperative. After defining allyship and providing contemporary and historical examples of civil courage, this paper explains the difficulties and impediments inherent in implementing racial justice. To enable growth and change, we introduce ten practical exercises based on cognitive-behavioral approaches to help individuals increase their awareness and ability to demonstrate racial justice allyship in alignment with valued behaviors. We explain how these exercises can be utilized to change thinking patterns, why the exercises can be difficult, and how psychologists and others might make use of them to expand the capacity for civil courage in the service of racial justice. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
Nehir Tipi Hidroelektrik Santrallerinin Havzalar Üzerindeki Ekohidrolojik Etkileri

In the construction phase of a hydroelectric power plants (HEPP) many negative effects including soil compaction, road construction, modification in flow regime, degradation of aquatic habitats, power transfer lines and roads, and impacts on wildlife are expected on ecosystems. Streams and stream habitats are affected from all these immediately. In our country the dam-type hydro power plant is used heavily where the energy production is closely related to water holding capacity, but this type of energy production give rise to high. Therefore instead of this type of energy production is used of the efforts of different hydraulic evaluation possibilities. This is an example of runoff type hydroelectric power plants which is related to natural flow characteristics during energy producing. With the effect of different energy cost, some changes has been occurred in the energy sources policies (privatization, legislation changes). A useful tool of field surveys together with ecohydrological study is required to reveal these effects and the integration level of the stream. These suggest that a watershed based scientific evaluation that ensures the sustainability of ecosystems is a ecohydrological research gap in our country. An evaluation will be improved to reveal the ecohydrological effects of run-of-river type hydroelectric power plants as an outcome of this study.
PID controller design in networked control systems

The paper addresses the PID control design and implementation based on the model predictive control approach that is able to deal with data dropouts in the control system. In model predictive control the future control inputs sequence up to a given horizon are calculated at each sampling instant. In case the current output value is not available, the value of future control input calculated at previous sampling instant can be used instead. The proposed control strategy is implemented by switching between two or more PID controllers. The closed loop stability is analyzed provided the switching occurs arbitrarily often. The effectiveness of the proposed strategy is demonstrated by the real-time control of simple laboratory plant.
Out-of-Domain Discourse Dependency Parsing via Bootstrapping: An Empirical Analysis on Its Effectiveness and Limitation

Discourse parsing has been studied for decades. However, it still remains challenging to utilize discourse parsing for real-world applications because the parsing accuracy degrades significantly on out-of-domain text. In this paper, we report and discuss the effectiveness and limitations of bootstrapping methods for adapting modern BERT-based discourse dependency parsers to out-of-domain text without relying on additional human supervision. Specifically, we investigate self-training, co-training, tri-training, and asymmetric tri-training of graph-based and transition-based discourse dependency parsing models, as well as confidence measures and sample selection criteria in two adaptation scenarios: monologue adaptation between scientific disciplines and dialogue genre adaptation. We also release COVID-19 Discourse Dependency Treebank (COVID19-DTB), a new manually annotated resource for discourse dependency parsing of biomedical paper abstracts. The experimental results show that bootstrapping is significantly and consistently effective for unsupervised domain adaptation of discourse dependency parsing, but the low coverage of accurately predicted pseudo labels is a bottleneck for further improvement. We show that active learning can mitigate this limitation.
Transition-Metal-Doping of CaO as Catalyst for the OCM Reaction, a Reality Check

In this study, first-row transition metal-doped calcium oxide materials (Mn, Ni, Cr, Co., and Zn) were synthesized, characterized, and tested for the OCM reaction. Doped carbonate precursors were prepared by a co-precipitation method. The synthesis parameters were optimized to yield materials with a pure calcite phase, which was verified by XRD. EPR measurements on the doped CaO materials indicate a successful substitution of Ca2+ with transition metal ions in the CaO lattice. The materials were tested for their performance in the OCM reaction, where a beneficial effect towards selectivity and activity effect could be observed for Mn, Ni, and Zn-doped samples, where the selectivity of Co- and Cr-doped CaO was strongly reduced. The optimum doping concentration could be identified in the range of 0.04-0.10 atom%, showing the strongest decrease in the apparent activation energy, as well as the maximum increase in selectivity.
To Help or Not to Help? Prosocial Behavior, Its Association With Well-Being, and Predictors of Prosocial Behavior During the Coronavirus Disease Pandemic

The coronavirus disease (COVID-19) pandemic fundamentally disrupted humans’ social life and behavior. Public health measures may have inadvertently impacted how people care for each other. This study investigated prosocial behavior, its association well-being, and predictors of prosocial behavior during the first COVID-19 pandemic lockdown and sought to understand whether region-specific differences exist. Participants (N = 9,496) from eight regions clustering multiple countries around the world responded to a cross-sectional online-survey investigating the psychological consequences of the first upsurge of lockdowns in spring 2020. Prosocial behavior was reported to occur frequently. Multiple regression analyses showed that prosocial behavior was associated with better well-being consistently across regions. With regard to predictors of prosocial behavior, high levels of perceived social support were most strongly associated with prosocial behavior, followed by high levels of perceived stress, positive affect and psychological flexibility. Sociodemographic and psychosocial predictors of prosocial behavior were similar across regions.
Revisiting PathFinder Routing Algorithm

PathFinder, a popular routing algorithm widely used in the state-of-the-art FPGA compilation tools such as VTR 8, has been reported to have a non-negligible variation in the routing quality under routing resource constraints. Several workaround methods have been proposed to mitigate this undesired effect while keeping the algorithm unchanged. In this paper, we take a fresh look at the PathFinder algorithm itself and identify that its inappropriate definition of routing congestion problems causes an issue in its congestion coefficient updating strategy and eventually leads to the variation in the routing quality under different routing orders. This problem is aggravated in VTR~8 and inevitably degrades the routing quality as the predefined routing order is not optimal in most cases. Based on these findings, we propose an enhanced PathFinder algorithm with redefined routing congestion problems to address the issue in the congestion coefficient updating strategy and algorithmically resolve the routing quality variation issue. This enhanced algorithm can be easily integrated into VTR~8 to benefit every researcher in our community. Evaluation results show that it reduces the longest critical path delay and the variation by up to 49.4% and 96.2% under routing resource constraints, respectively. The variation can be fully eliminated when sufficient routing iterations are performed.
Logic Scaling Options for the Next 10 Years: From FinFet to CFET, from Dual Damascene to Semi Damascene

An overview of future logic scaling options both for devices and interconnects will be provided from technology point of view, including Front-End-Of-Line (FEOL), Middle-Of-Line (MOL) and Back-End-Of-Line (BEOL) modules [1-4]. The aim is to provide a perspective for the coming 10years in terms of CMOS scaling scenarios. To enable more efficient computing, both device and interconnect architectures are expected to change. The device trend from today's conventional FinFet to Nanosheet then Forksheet then to CFET and eventually to 2D materials will be explained [3, 5, 6]. This is alongside with the wide deployment of EUV lithography into BEOL, MOL, FEOL paving a cost-effective patterning. Track height scaling along with the use of scaling boosters is the natural path to follow. It is accompanied by significant changes in MOL and BEOL modules as well. One example is the potential inflection point from classical dual damascene modules towards metal patterning based self-aligned semi damascene. This in combination with airgaps can provide an attractive RC tradeoff. Another example is backside power delivery enabled by the use of nano-TSVs [7,8]. During the talk several more examples will be shown.
Online Video Exchanges in an English as a Foreign Language Writing Course

Writing has been argued to be the most difficult and complex language skill because it comprises multiple aspects, such as lexical and syntactic knowledge, etc. [1], not even to mention writing in a foreign language. The difficulties lead to the pursuit of an effective teaching approach for better acquisition. Task-based language teaching (TBLT), enabling students to practice target language in authentic and meaningful tasks [2], has been applied in writing instruction. In current digital era, integration of technology and TBLT in EFL contexts remains under-researched. This study explores the effects of TBLT with online video exchanges in an English as a foreign language (EFL) writing course on students’ descriptive writing performance. A quasi-experiment was conducted. Students of two writing courses were recruited and randomly assigned as experimental group and control group. The participants in the experimental group were engaged in the writing project to transform their descriptive writing assignments introducing local tourist attractions to videos and exchange them online with foreign virtual peers. A mixed research approach was adopted to analyze the data collected from participants’ compositions and self-reflection. The results revealed that TBLT is effective in developing EFL students’ descriptive writing proficiency. In addition to their writing achievement, the students enjoyed participating in the task while utilizing other multiple skills. Implications of this study for TBLT in EFL writing teaching practices are discussed as well.
PoSSUM: An Entity-centric Publish/Subscribe System for Diverse Summarization in Internet of Things

Users are interested in entity information provided by multiple sensors in the Internet of Things. The challenges regarding this environment span from data-centric ones due to data integration, heterogeneity, and enrichment, to user-centric ones due to the need for high-level data interpretation and usability for non-expert users, to system-centric ones due to resource constraints. Publish/Subscribe systems (PSSs) are suitable schemes for large-scale applications, but they are limited in dealing with the data and user challenges. In this article, we propose PoSSUM, a novel entity-centric PSS that provides entity summaries for user-friendly subscriptions through data integration, a novel Density-Based VARiance Clustering (DBVARC) for diverse entity summarization that is parameter-free and partly incremental, reasoning rules, and a novel Triple2Rank scoring for top-k filtering based on importance, informativeness, and diversity. We introduce a novel evaluation methodology that creates ground truths and metrics that capture the quality of entity summaries. We compare our approach with a previous dynamic approach and a static diverse entity summarization approach that we adapted to dynamic environments. The evaluation results for two use cases, Healthcare and Smart Cities, show that when users are provided with less information, their data diversity desire could reach up to 80%. Summarization approaches achieve from 80% to 99% message reduction, with PoSSUM having the best-ranking quality for more than half of the entities by a significant margin. PoSSUM has the highest conceptual clustering F-score, ranging from 0.69 to 0.83, and a redundancy-aware F-score up to 0.95, with cases, where it is almost two times better than the other approaches. PoSSUM takes 50% or less clustering processing time and it performs scoring significantly faster for larger windows. It also has comparable end-to-end latency and throughput values, and it occupies a third of the memory compared to the second-best approach.
A Framework for Identification and Validation of Affine Hybrid Automata from Input-Output Traces

Automata-based modeling of hybrid and cyber-physical systems (CPS) is an important formal abstraction amenable to algorithmic analysis of its dynamic behaviors, such as in verification, fault identification, and anomaly detection. However, for realistic systems, especially industrial ones, identifying hybrid automata is challenging, due in part to inferring hybrid interactions, which involves inference of both continuous behaviors, such as through classical system identification, as well as discrete behaviors, such as through automata (e.g., L*) learning. In this paper, we propose and evaluate a framework for inferring and validating models of deterministic hybrid systems with linear ordinary differential equations (ODEs) from input/output execution traces. The framework contains algorithms for the approximation of continuous dynamics in discrete modes, estimation of transition conditions, and the inference of automata mode merging. The algorithms are capable of clustering trace segments and estimating their dynamic parameters, and meanwhile, deriving guard conditions that are represented by multiple linear inequalities. Finally, the inferred model is automatically converted to the format of the original system for the validation. We demonstrate the utility of this framework by evaluating its performance in several case studies as implemented through a publicly available prototype software framework called HAutLearn and compare it with a membership-based algorithm.