Miracle-dz/UniFAR-FTUs huggingface dataset:
Industrial application of CFD: a review of few examples

The paper reviews six examples of CFD applications, useful for: minerals, power generation and oil & gas industry. The review starts with the multiphase modeling of gas injection into a liquid bath, where the CFD results were validated against experimental data. The example is very useful for metal extraction/refining industry. Simulation of a mineral concentrator bin is presented next, where multiphase modeling was used to find out the cause of blocking of the slurry pump. The 3 example presents two alternative designs, evaluated for better extraction of dust from an underground mine crushing-plant. Multiphase modeling with boiling-heat transfer was used in the next example for investigating a low pressure water cooling system in slag fumers. The next example reviews full scale coal combustion modelling of a tangentially fired boiler with mill ducting. Finally a successful modeling of a gas liquid separator is presented. The CFD software FIRE (AVL 2009) was used in most of the investigations. Geometry dimensions and process data were suppressed as necessary for confidentiality reasons. Example-1. Gas injections into liquid baths using Top Submerged Lances (TSL) There are various methods for gas injection into molten baths including Top Submerged Lance (TSL) technology, which uses a submerged vertical lance within an upright cylindrical furnace (Huda et al 2009, Floyd 1996). Through the lance, oxygen enriched air is injected with swirl into the molten bath which provides intense mixing of the bath and excellent contact between phases. Floyd (2005) has described the details of the Top Submerged Lance technology and its development since the 1970s. This paper reviews the fluid flow phenomena in a cylindrical bath stirred by Top Submerged Lance (TSL) gas injection, investigated by using CFD for an isothermal air-water system (Huda et al 2009). The multiphase flow simulation, based on the Euler-Euler approach, elucidated the effect of swirl and non-swirl flow inside the bath (Fig. 1). The effects of lance submergence level and air flow rate were also investigated in the study. The simulation results for velocity fields (Fig. 1(c)) and generation of turbulence in the bath were validated against existing experimental data from the previous model experimental study of Morsi et al. (2000). Figure 1(a) Volume fraction of liquid (TSL) (Huda et al 2009). Example-2. The mineral concentrator bin The mineral concentrator bin reviewed here was reported to show problems of accumulation of solids on the upper slanting walls. Investigations were carried out to find out the possible cause of this unusual accumulation of solids. CFD simulations were carried out for the exact operating configuration and geometries modified to overcome the problem. A quarter of the geometry was used in the model due to structural beams inside. Figure 2(a) shows the grid and Figure2 (b) shows the accumulation of solids on the upper slanting walls, which will grow with time and eventually slump into the bottom, causing blockage problem for the slurry pump suction, located at the bottom of the bin.
Safety Analysis of Autonomous Railway Systems: An Introduction to the SACRED Methodology

As the railway industry increasingly seeks to introduce autonomy and machine learning (ML), several questions arise. How can safety be assured for such systems and technologies? What is the applicability of current safety standards within this new technological landscape? What are the key metrics to classify a system as safe? Currently, safety analysis for the railway reflects the failure modes of existing technology; in contrast, the primary concern of analysis of automation is typically average performance. Such purely statistical approaches to measuring ML performance are limited, as they may overlook classes of situations that may occur rarely but in which the function performs consistently poorly. To combat these difficulties we introduce SACRED, a safety methodology for producing an initial safety case and determining important safety metrics for autonomous systems. The development of SACRED is motivated by the proposed GoA-4 light-rail system in Berlin.
Adaptive Regulation Maintains Posttetanic Potentiation at Cerebellar Granule Cell Synapses in the Absence of Calcium-Dependent PKC

Posttetanic potentiation (PTP) is a transient, calcium-dependent increase in the efficacy of synaptic transmission following elevated presynaptic activity. The calcium-dependent protein kinase C (PKCCa) isoforms PKCα and PKCβ mediate PTP at the calyx of Held synapse, with PKCβ contributing significantly more than PKCα. It is not known whether PKCCa isoforms play a conserved role in PTP at other synapses. We examined this question at the parallel fiber → Purkinje cell (PF→PC) synapse, where PKC inhibitors suppress PTP. We found that PTP is preserved when single PKCCa isoforms are knocked out and in PKCα/β double knock-out (dko) mice, even though in the latter all PKCCa isoforms are eliminated from granule cells. However, in contrast to wild-type and single knock-out animals, PTP in PKCα/β dko animals is not suppressed by PKC inhibitors. These results indicate that PKCCa isoforms mediate PTP at the PF→PC synapse in wild-type and single knock-out animals. However, unlike the calyx of Held, at the PF→PC synapse either PKCα or PKCβ alone is sufficient to mediate PTP, and if both isoforms are eliminated a compensatory PKC-independent mechanism preserves the plasticity. These results suggest that a feedback mechanism allows granule cells to maintain the normal properties of short-term synaptic plasticity even when the mechanism that mediates PTP in wild-type mice is eliminated.
Genetic epidemiology of glioma

The present study performed a segregation analysis of a cohort of first-degree relatives (FDR) of glioma patients. The families with two or more gliomas were also expanded to determine if any more gliomas could be detected, and if any other types of cancers were associated. These glioma-prone families (n = 24/432) were extended to include first-, second- and third-degree relatives (n = 807) and a cohort was assembled, the standardized incidence risk for other types of cancer calculated and the pedigrees investigated for a possible mode of inheritance. A segregation analysis of the 2141 FDR in 297 families, performed using the Pointer software, did not clearly reject a multifactorial model χ2(3) = 6.13,P< 0.2. However, when letting all parameters be free, the recessive model provided the best fit. In the extended families, no increased risk of other types of cancer was found. This population-based study proposes that familial glioma occurs in about 5% of all glioma cases and that 1% have a possible autosomal dominant inheritance. This first segregation analysis performed in familial glioma must be cautiously interpreted, but an autosomal recessive gene provided the best fit, which could possibly explain 2% of all glioma cases. © 2001 Cancer Research Campaign http://www.bjcancer. com
Huntingtin is required for ER-to-Golgi transport and for secretory vesicle fusion at the plasma membrane

Huntingtin is a large membrane-associated scaffolding protein that associates with endocytic and exocytic vesicles and modulates their trafficking along cytoskeletal tracks. Although the progression of Huntington’s disease is linked to toxic accumulation of mutant huntingtin protein, loss of wild-type huntingtin function might also contribute to neuronal cell death, but its precise function is not well understood. Therefore, we investigated the molecular role of huntingtin in exocytosis and observed that huntingtin knockdown in HeLa cells causes a delay in endoplasmic reticulum (ER)-to-Golgi transport and a reduction in the number of cargo vesicles leaving the trans-Golgi network. In addition, we found that huntingtin is required for secretory vesicle fusion at the plasma membrane. Similar defects in the early exocytic pathway were observed in primary fibroblasts from homozygous Htt140Q/140Q knock-in mice, which have the expansion inserted into the mouse huntingtin gene so lack wild-type huntingtin expression. Interestingly, heterozygous fibroblasts from a Huntington’s disease patient with a 180Q expansion displayed no obvious defects in the early secretory pathway. Thus, our results highlight the requirement for wild-type huntingtin at distinct steps along the secretory pathway.
DISTINGUISHING PRIME NUMBERS FROM COMPOSITE NUMBERS

This paper compares 21 methods to distinguish prime numbers from composite numbers. It answers the following questions for each method: Does the method certify primality? Conjecturally certify primality? Certify compositeness? Are certificates conjectured to exist for all inputs? Proven to exist for all inputs? Found deterministically for all inputs? Is a certificate verified in essentially linear time? Essentially quadratic time? Et cetera. Is a certificate found immediately? In essentially linear time? Essentially quadratic time? Et cetera. In brief, how does the method work? When and where was the method published?
Embarrassingly Simple Scribble Supervision for 3D Medical Segmentation

Traditionally, segmentation algorithms require dense annotations for training, demanding significant annotation efforts, particularly within the 3D medical imaging field. Scribble-supervised learning emerges as a possible solution to this challenge, promising a reduction in annotation efforts when creating large-scale datasets. Recently, a plethora of methods for optimized learning from scribbles have been proposed, but have so far failed to position scribble annotation as a beneficial alternative. We relate this shortcoming to two major issues: 1) the complex nature of many methods which deeply ties them to the underlying segmentation model, thus preventing a migration to more powerful state-of-the-art models as the field progresses and 2) the lack of a systematic evaluation to validate consistent performance across the broader medical domain, resulting in a lack of trust when applying these methods to new segmentation problems. To address these issues, we propose a comprehensive scribble supervision benchmark consisting of seven datasets covering a diverse set of anatomies and pathologies imaged with varying modalities. We furthermore propose the systematic use of partial losses, i.e. losses that are only computed on annotated voxels. Contrary to most existing methods, these losses can be seamlessly integrated into state-of-the-art segmentation methods, enabling them to learn from scribble annotations while preserving their original loss formulations. Our evaluation using nnU-Net reveals that while most existing methods suffer from a lack of generalization, the proposed approach consistently delivers state-of-the-art performance. Thanks to its simplicity, our approach presents an embarrassingly simple yet effective solution to the challenges of scribble supervision. Source code as well as our extensive scribble benchmarking suite will be made publicly available upon publication.
A grid model based on tree-shaped resource fusion

How can make use of the existing substantial grid resources in network environments and quickly develop new grid applications adapting to the variable requirements of users, that is a big challenge for current grid research. In order to solve the problems, a tree-shaped resource fusion based grid model is proposed. The basic idea of the model is that new resources are created by the fusion of resources in the form of tree from bottom to top. It supports the self-similar constructing model for grid application by the tree-shaped fusion, which can regenerate new resources and develop grid applications effectively. After proposing the grid resource abstraction, the grid resource classification and the unified interfaces for access to resources, the model for tree-shaped fusion of resources is present and the theoretical results for the model are obtained. Finally, a grid prototype system FuseGrid based on resource fusion is designed.
Status of Glucocorticoid Alterations in Post‐traumatic Stress Disorder

The current status of glucocorticoid alterations in post‐traumatic stress disorder (PTSD) will be described in this chapter. Emphasis will be placed on data that suggest that at least some glucocorticoid‐related observations in PTSD reflect pretraumatic glucocorticoid status. Recent observations have provided some evidence that pretraumatic glucocorticoid alterations may arise from genetic, epigenetic, and possibly other environmental influences that serve to increase the likelihood of developing PTSD following trauma exposure, as well as modulate attendant biological alterations associated with its pathophysiology. Current studies in the field of PTSD employ glucocorticoid challenge strategies to delineate effects of exogenously administered glucocorticoids on neuroendocrine, cognitive, and brain function. Results of these studies have provided an important rationale for using glucocorticoid strategies in the treatment of PTSD.
Aracna: An Open-Source Quadruped Platform for Evolutionary Robotics

We describe a new, quadruped robot platform, Aracna, which requires non-intuitive motor commands in order to locomote and thus provides an interesting challenge for gait learning algorithms, such as those frequently developed in the Evolutionary Computation and Artificial Life communities. Aracna is an open-source hardware project composed of off-the-shelf and 3D-printed parts, enabling other research teams to modify its design according to their scientific needs. Aracna was designed to overcome the shortcomings of a previous quadruped robot platform, whose legs were so heavy that the motors could not reliably execute the commands sent to them. We avoid this problem by locating all motors in the body core instead of on the legs and through a design which enables the servos to have a greater mechanical advantage. Specifically, each of the four legs has two joints controlled by separate four-bar linkage mechanisms that drive the pitch of the hip joint and knee joint. This novel design causes unconventional kinematics, creating an opportunity for gaitlearning algorithms, which excel in counter-intuitive design spaces where human engineers tend to underperform. Because it is low-cost, flexible, kinematically interesting, and and improvement over a previous design, Aracna provides a useful new hardware platform for testing algorithms that automatically generate robotic behaviors.
Energy smart routing protocol (ESRP)

Sensor nodes in Wireless sensor networks (WSN's) have limited energy, range, memory and computational power, therefore, approaches have been proposed over the years to reduce energy consumption and to prolong network lifetimes. In this paper, we propose an energy smart routing protocol (ESRP) for WSNs with mobile sinks. The first sink proactively constructs a grid structure. A path along grid points is paved from a sink to the source for forwarding queries and disseminating data. For choosing each grid sensor node, a cost function is applied to serve each respective crossing point and to handle grid node failure. Based upon this grid, we develop novel methods for handling multiplicity and movements of sinks by creating an expected mobility zone in sensor field so as to ensure continuous data delivery from source nodes to sink or sinks.
NIRMAL: Automatic identification of software relevant tweets leveraging language model

Twitter is one of the most widely used social media platforms today. It enables users to share and view short 140-character messages called “tweets”. About 284 million active users generate close to 500 million tweets per day. Such rapid generation of user generated content in large magnitudes results in the problem of information overload. Users who are interested in information related to a particular domain have limited means to filter out irrelevant tweets and tend to get lost in the huge amount of data they encounter. A recent study by Singer et al. found that software developers use Twitter to stay aware of industry trends, to learn from others, and to network with other developers. However, Singer et al. also reported that developers often find Twitter streams to contain too much noise which is a barrier to the adoption of Twitter. In this paper, to help developers cope with noise, we propose a novel approach named NIRMAL, which automatically identifies software relevant tweets from a collection or stream of tweets. Our approach is based on language modeling which learns a statistical model based on a training corpus (i.e., set of documents). We make use of a subset of posts from StackOverflow, a programming question and answer site, as a training corpus to learn a language model. A corpus of tweets was then used to test the effectiveness of the trained language model. The tweets were sorted based on the rank the model assigned to each of the individual tweets. The top 200 tweets were then manually analyzed to verify whether they are software related or not, and then an accuracy score was calculated. The results show that decent accuracy scores can be achieved by various variants of NIRMAL, which indicates that NIRMAL can effectively identify software related tweets from a huge corpus of tweets.
Ethics in the Family Firm: Cohesion through Reciprocity and Exchange

ABSTRACT: The ubiquity of family dominated firms in economies worldwide suggests that inquiry into the nature of the ethical frames of these types of firms is increasingly important. In the context of a social exchange approach and the norm of reciprocity, this manuscript addresses social cohesion in a dominant family firm coalition. It is argued that the factors underlying this cohesion, direct versus indirect reciprocity, shape unique attributes of family firms such as intentions for transgenerational sustainability, the pursuit of non-economic goals, and strong interpersonal ties. Exchange structures, represented by direct and indirect reciprocity, lead family and non-family firms toward development of distinctive ethical frames of reference.
Validation of the 12-gene colon cancer recurrence score in NSABP C-07 as a predictor of recurrence in patients with stage II and III colon cancer treated with fluorouracil and leucovorin (FU/LV) and FU/LV plus oxaliplatin.

PURPOSE Accurate assessments of recurrence risk and absolute treatment benefit are needed to inform colon cancer adjuvant therapy. The 12-gene Recurrence Score assay has been validated in patients with stage II colon cancer from the Cancer and Leukemia Group B 9581 and Quick and Simple and Reliable (QUASAR) trials. We conducted an independent, prospectively designed clinical validation study of Recurrence Score, with prespecified end points and analysis plan, in archival specimens from patients with stage II and III colon cancer randomly assigned to fluorouracil (FU) or FU plus oxaliplatin in National Surgical Adjuvant Breast and Bowel Project C-07. METHODS Recurrence Score was assessed in 892 fixed, paraffin-embedded tumor specimens (randomly selected 50% of patients with tissue). Data were analyzed by Cox regression adjusting for stage and treatment. RESULTS Continuous Recurrence Score predicted recurrence (hazard ratio for a 25-unit increase in score, 1.96; 95% CI, 1.50 to 2.55; P < .001), as well as disease-free and overall survival (both P < .001). Recurrence Score predicted recurrence risk (P = .001) after adjustment for stage, mismatch repair, nodes examined, grade, and treatment. Recurrence Score did not have significant interaction with stage (P = .90) or age (P = .76). Relative benefit of oxaliplatin was similar across the range of Recurrence Score (interaction P = .48); accordingly, absolute benefit of oxaliplatin increased with higher scores, most notably in patients with stage II and IIIA/B disease. CONCLUSION The 12-gene Recurrence Score predicts recurrence risk in stage II and stage III colon cancer and provides additional information beyond conventional clinical and pathologic factors. Incorporating Recurrence Score into the clinical context may better inform adjuvant therapy decisions in stage III as well as stage II colon cancer.
Debating the role of drugs in sport: a reader

The development of the agenda to guide social science research into drugs in sport was driven by two workshops. The first workshop examined basic drugs in sport issues, and attempted to put a common lexicon or discourse to frame and explore different ways of thinking about the issues. Development of this framework saw a first principles approach built from the purpose of social science towards the questions that proved starting points to understanding the issues at hand. The second workshop challenged the academic approach to drugs in sport with a hypothetical scenario discussed by people involved in the sports industry, including athletes, policy makers and parents of athletes. The results of these workshops form an insight into one attempt of a multi-disciplinary group to come to grips with how social science can contribute to relevant social issues such as understanding the role of drugs in sport.
Bayesian Multi-Document Summarization at MSE

We describe our entry into the Multilingual Summarization Evaluation (MSE) competition for evaluating generic multidocument summarization systems, where documents are drawn both from English data and English translations of Arabic data. Our system is based on a Bayesian Query-Focused Summarization model, adapted to the generic, multidocument setting and tuned against the ROUGE evaluation metric. In the human pyramid-based evaluation, our system scored an average of 0.530, approximately 8% better than the next best system, which scored 0.489. In the automatic evaluation, our system scored 0.157 (behind four other sites) with the skip-bigram evaluation, and 0.131 (behind two other sites) with the standard bigram evaluation.
Metrics to monitor performance of patients with mild cognitive impairment using computer based games

Mild Cognitive Impairment (MCI) results in a noticeable decrease in cognitive abilities but does not interfere with regular daily functions. Some patients with MCI may be able to return to age-appropriate cognitive abilities, but some will progress to dementia. Clinical interviews, tests and measurements are used to identify and monitor cognitive decline. Timely detection of cognitive decline provides an opportunity for early intervention and can improve care and quality of life. Periodic monitoring of the cognitive status of MCI patients in their own environment is a significant and cost effective aid in patient care. This paper presents a methodology and performance metrics for remote monitoring of cognitive ability using computer based Sudoku and word search games. We collected game data for 2 MCI patients from the Bruyére Memory Program over a period of weeks. Their game performance was then compared to results from cognitive testing using the Montreal Cognitive Assessment (MoCA) and the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). The patient who performed better on the games also had higher scores on the cognitive testing.
A Fuzzy Interactive Approach for Solving Bilevel Programming 1

In this paper, we focus bilevel programming problem with common decision variable in the upper level and lower level programming. After introducing fuzzy goals for objective functions, consulting the ratios of satisfaction between the leader at the upper level and the follower at the lower level, interactive fuzzy decision making method to derive a satisfactory solution for decision makers is presented. A numerical example illustrates the proposed method.