Miracle-dz/UniFAR-FTUs huggingface dataset:
Identiﬁability of Path-Speciﬁc Effects ∗

: Counterfactual quantities representing pathspecific effects arise in cases where we are interested in computing the effect of one variable on another only along certain causal paths in the graph (in other words by excluding a set of edges from consideration). A recent paper [Pearl, 2001] details a method by which such an exclusion can be specified formally by fixing the value of the parent node of each excluded edge. In this paper we derive simple, graphical conditions for experimental identifiability of path-specific effects, namely, conditions under which path-specific effects can be estimated consistently from data obtained from controlled experiments. Abstract Counterfactual quantities representing path-speciﬁc effects arise in cases where we are interested in computing the effect of one variable on another only along certain causal paths in the graph (in other words by excluding a set of edges from consideration). A recent paper [Pearl, 2001] details a method by which such an exclusion can be speciﬁed formally by ﬁxing the value of the parent node of each excluded edge. In this paper we derive simple, graphical conditions for experimental identiﬁability of path-speciﬁc effects, namely, conditions under which path-speciﬁc effects can be estimated consistently from data obtained from controlled experiments.
Merkel Cell Polyomavirus-Infected Merkel Cell Carcinoma Cells Require Expression of Viral T Antigens (cid:1)

Merkel cell carcinoma (MCC) is the most aggressive skin cancer. Recently, it was demonstrated that human Merkel cell polyomavirus (MCV) is clonally integrated in (cid:1) 80% of MCC tumors. However, direct evidence for whether oncogenic viral proteins are needed for the maintenance of MCC cells is still missing. To address this question, we knocked down MCV T-antigen (TA) expression in MCV-positive MCC cell lines using three different short hairpin RNA (shRNA)-expressing vectors targeting exon 1 of the TAs. The MCC cell lines used include three newly generated MCV-infected cell lines and one MCV-negative cell line from MCC tumors. Notably, all MCV-positive MCC cell lines underwent growth arrest and/or cell death upon TA knockdown, whereas the proliferation of MCV-negative cell lines remained unaffected. Despite an increase in the number of annexin V-positive, 7-amino-actinomycin D (7-AAD)-negative cells upon TA knockdown, activation of caspases or changes in the expression and phosphorylation of Bcl-2 family members were not consistently detected after TA suppression. Our study provides the ﬁrst direct experimental evidence that TA expression is necessary for the maintenance of MCV-positive MCC and that MCV is the infectious cause of MCV-positive MCC.
MASTER’S THESIS FEDERATED LEARNING FOR ENHANCED SENSOR RELIABILITY OF AUTOMATED WIRELESS NETWORKS

Autonomous mobile robots working in-proximity humans and objects is becoming frequent and thus, avoiding collisions becomes important to increase the safety of the working environment. This thesis develops a mechanism to improve the reliability of sensor measurements in a mobile robot network taking into the account of inter-robot communication and costs of faulty sensor replacements. In this view, ﬁrst, we develop a sensor fault prediction method utilizing sensor characteristics. Then, network-wide cost capturing sensor replacements and wireless communication is minimized subject to a sensor measurement reliability constraint. Tools from convex optimization are used to develop an algorithm that yields the optimal sensor selection and wireless information communication policy for aforementioned problem. Under the absence of prior knowledge on sensor characteristics, we utilize observations of sensor failures to estimate their characteristics in a distributed manner using federated learning . Finally, extensive simulations are carried out to highlight the performance of the proposed mechanism compared to several state-of-the-art methods.
Effect of CWND and RTO in the Performance of Wireless Networks

In this paper we describe a ns based simulation analysis of TCP performance over a hybrid network with first link as a wireless link. The latter choice is for understanding performance issues with better clarity. The effect of wireless errors on different TCP parameters resulted into end to end performance degradation of TCP is investigated. Based on the analysis of the basic MAC loss recovery mechanism, we are able to show impact of delay introduced by MAC loss recovery over the performance of TCP. With increased MAC loss recovery duration TCP is unable to conceive maximum of available bandwidth over a network. In addition, it also describe that adaption in CWND will improve the performance of wireless networks. All above simulation results clearly show a) scope for improving MAC loss recovery and b) requirement of tuning between TCP and MAC loss recovery, particularly for retransmission mechanism.
Solar sorption cooling for residential air-conditioning applications

This paper presents the comparison of two sorption cooling systems for providing air conditioning in a residential building that can be driven by a flat plate solar collector. A thermodynamic model has been developed for each system to compare the energy balance in each component and the coefficient of performance (COP). Analyses have been performed for 10 kW water-ammonia absorption and activated carbon-ammonia adsorption chillers. For both systems, the first law efficiencies have been compared and the optimum efficiency has been investigated under different operating conditions. Analysis revealed that under any operating condition, the COP is always higher for the absorption chiller and its maximum value is 0.6, which is almost twice that of the adsorption chiller (COP = 0.35), for 10 kW systems operating at evaporator and condenser/absorber temperatures of 2°C and 30°C, respectively. The adsorption system requires a higher energy input to produce the same cooling effect as compared to the absorption system.
A novel length-based empirical estimation method of spawning potential ratio (SPR), and tests of its performance, for small-scale, data-poor ﬁsheries Journal of Marine Science

and J. A novel length-based empirical estimation method of spawning potential ratio (SPR), and tests of its performance, for small-scale, data-poor ﬁsheries. – ICES Journal of Marine Science, 72: 217–231. The spawning potential ratio (SPR) is a well-established biological reference point, and estimates of SPR could be used to inform management decisions for data-poor ﬁsheries. Simulations were used to investigate the utility of the length-based model (LB-SPR) developed in Hordyk et al. (2015). Some explorations of the life history ratios to describe length composition, spawning-per-recruit, and the spawning potential ratio. ICES Journal of Marine Science, 72: 204–216. ) to estimate the SPRof astockdirectly fromthe size composition of the catch. This was done by (i) testing some of the main assumptions of the LB-SPR model, including recruitment variability and dome-shaped selectivity, (ii) examining the sensitivityof the model to error in the input parameters, and (iii) completing an initial empirical test for the LB-SPR model by applying it to data from a well-studied species. The method uses maximum likelihood methods to ﬁnd the values of relative ﬁshing mortality ( F/M ) and selectivity-at-length that minimize the difference between the observed and the expected length composition ofthecatch,andcalculatestheresultingSPR.Whenparameterizedwiththecorrectinputparameters,theLB-SPRmodelreturnedaccurate estimatesof F/M andSPR.Withhighvariabilityinannualrecruitment,theestimatesofSPRbecameincreasinglyunreliable.Theusefulnessof the LB-SPR method was tested empirically by comparing the results predicted by the method with those for a well-described species with known length and age composition data. The results from this comparison suggest that the LB-SPR method has potential to provide atool forthecost-effectiveassessmentofdata-poorﬁsheries. However,themodelissensitivetonon-equilibriumdynamics,andrequiresaccurate estimates of the three parameters ( M/k , L 1 , and CV L 1 ). Care must be taken to evaluate the validity of the assumptions and the biological parameters when the model is applied to data-poor ﬁsheries.
Robust Diagnostics for the Logistic Regression Model

Current imputation methods, such as the EM types, are easily affected by outliers. They may either impute extra outliers if the existing outliers are ignored, or may move (potential) outliers to the center of the data when only part of them are observed. Atkinson and Cheng (2000) first employ the high breakdown estimator for the detection of outliers in the presence of missing values for the linear regression model. Recently, Atkinson and Riani (2001) adapt the forward search algorithm for the least median of squares (LMS) estimator to deal with outlier problem in the binary data. In this article, we extend their approach to identify multiple outliers for the logistic regression model when part of data are missing. The proposed forward algorithm starts with using the imputation method based on a small subset of the data to fill in those missing observations in the whole data set. Then the subset augments until all observations are included in the analysis. The algorithm monitors the statistics of interest during the progress of the forward search. The LMS criterion is used to judge the performance of each search. Real data are used to illustrate the resulting procedure.
Maximizing Fiber Utilization of Silage in Ruminants Maximizing Fiber Utilization of Silage in Ruminants

This chapter highlights the importance of fiber digestibility and utilization in ruminants and to summarize the main factors that influence fiber digestibility in silages. Forage provides at least half of the diet of lactating cattle and greatly affects energy and carbohydrate intake. It is important to maximize the intake of digestible carbohydrate from forages, because energy requirements for maintenance and milk production often exceed the amount of energy high-producing cows can consume, particularly in early lactation. There are many approaches used for enhancing fiber utilization in silage and subsequent maximizing energy intake and productivity of dairy cattle. Out of these approaches are: selecting appropriate forages with high fiber digestibility, applying the appropriate agronomic practices such as harvesting at the proper stage of maturity, fertilization, and cutting height at harvest, along with using of esterase-producing inoculants or fibrolytic enzymes have been proposed as approaches to improving the productivity of dairy cattle. and an undegradable degradable be at a fractional (per a of harvest, cutting height, growing conditions, silage additives, and enzymes.
Transfer Learning Approach for Autonomous Agents in Collective Games

—The aim of this study is to present a new approach for Transfer Learning in collective games. This framework is a set of methods for transferring accumulated knowledge. In this way, autonomous agents share their knowledge in order to achieve better performance. The main hypothesis in the study is that the group of agents who exchange knowledge performs better than the same group without Transfer Knowledge, under the same conditions.
in the fibrinogen gamma gene the deep by reducing plasma fibrinogen

We investigated the association between haplotypes of fibrinogen alpha (FGA), beta (FGB) and gamma (FGG), total fibrinogen levels, fibrinogen γ ' ( γ A/ γ ' plus γ '/ γ ') levels, and risk of deep venous thrombosis. In a population-based case-control study, the Leiden Thrombophilia Study, we typed 15 haplotype-tagging (ht) SNPs in this gene-cluster. None of these haplotypes was associated with total fibrinogen levels. In each gene, one haplotype increased the thrombotic risk approximately 2-fold. After adjustment for linkage disequilibrium between the genes, only FGG-H2 homozygosity remained associated with risk (OR=2.4, 95%CI:1.5-3.9). FGG-H2 was also associated with reduced fibrinogen γ ' levels and reduced fibrinogen γ '/total fibrinogen ratios. Multivariate analysis showed that reduced fibrinogen γ ' levels and elevated total fibrinogen levels were both associated with an increased risk of thrombosis, even after adjustment for FGG-H2. A reduced fibrinogen γ '/total fibrinogen ratio (<0.69) also increased the risk (OR=2.4, 95%CI:1.7-3.5). We propose that FGG-H2 influences thrombosis risk via htSNP 10034C>T [rs2066865] by strengthening the consensus of a CstF site and thus favoring formation of γ A chain above that of γ ' chain. Fibrinogen γ ' contains a unique high-affinity non-substrate binding site for thrombin, which seems critical for the expression of the antithrombin activity which develops during fibrin formation (antithrombin I). γ ' levels γ 0.6-2.3). These results did not change after adjustment for age, sex, diabetes mellitus, BMI and high levels
Decision Forecast Modelling For Effective Execution Of Research Projects In R&D Labs Through Bi Models

— Research institutions adopting Enterprise Resource Planning packages for their day to day operations generate enormous data. Effective methodology for analysis these data will add value to the research and provide in the decision making process for the management using Business Intelligence (BI) models. For accomplishing this task, specific rules, techniques and algorithms needs to be developed in order to make the ERP system intelligent. These rules will bring out the hidden Business Intelligence in the ERP data and thereby will improve the outcome and deliverables of the project apart from providing support to the scientist. This forms a cyclic structure by again analyzing the outcome of the intelligence found, as this intelligence is incorporated with the ERP database itself. BI has been found used extensively in manufacturing sector and business houses and seldom used in R&D institutions and laboratories. This research work envisages to use BI model to improve the performance and provide support to large R&D labs like Council of Scientific and Industrial Research (CSIR).
Robust techniques for developing empirical models of fluidized bed combustors

This report is designed to provide a review of those data analysis techniques that are most useful for fitting m-dimensional empirical surfaces to very large sets of data. One issue explored is the improvement of data (1) using estimates of the relative size of measurement errors and (2) using known or assumed theoretical relationships. An apparently new concept is developed, named robust weighting, which facilitates the incorporation of a priori knowledge, based upon the values of input and response variables, about the relative quality of different experiments. This is a particularly useful technique for obtaining statistical inferences from the most relevant portions of the data base, such as concentrating on important ranges of variables or extrapolating off the leading edge of the frontier of knowledge for an emerging technology. The robust weightings are also useful for forcing a riori known asymptotic behaviors, as well as for fighting biases due to shear size of conflicting data clustersand for formulating separate models for conflicting clusters. Another new development has evolved from the two very different objectives of the empirical modeling in this project. The first objective is the usual requirement for the best possible predictive mechanism, and standard techniques are useful with their emphasis on model building, specifically the successive separation of trend techniques. In addition, a second objective involves the pursuit of high-dimensional, yet simple, models that could provide insight into analytic gaps and scientific theories that might govern the situation. For this second objective a new stepwise process was developed for rapidly sweeping the data base and producing crude quantitative measures of the next (or the first) most important m-tuple relationship to incorporate into the empirical model. These quantitative
Ecological divergence of a novel group of Chloroflexus along a geothermal gradient

Environmental gradients are expected to promote the diversification and co-existence of 26 ecological specialists adapted to local conditions. Consistent with this view, genera of 27 phototrophic microorganisms in alkaline geothermal systems generally appear to consist 28 of anciently divergent populations which have specialized on different temperature 29 habitats. At White Creek (Lower Geyser Basin, Yellowstone NP), however, a novel, 16S 30 rRNA-defined lineage of the filamentous anoxygenic phototroph Chloroflexus (OTU 10, 31 phylum Chloroflexi ) occupies a much wider thermal niche than other 16S rRNA-defined 32 groups of phototrophic bacteria. This suggests that Chloroflexus OTU 10 is either an 33 ecological generalist or, alternatively, a group of cryptic thermal specialists which have 34 recently diverged. To distinguish between these alternatives, we first isolated laboratory 35 strains of Chloroflexus OTU 10 from along the White Creek temperature gradient. These 36 strains are identical for partial gene sequences encoding the 16S rRNA and malonyl Co- 37 A reductase, respectively. However, strains isolated from upstream and downstream 38 samples could be distinguished based on sequence variation at pcs , which encodes 39 propionyl-CoA synthase of the 3-hydroxypropionate pathway of carbon fixation used by 40 the genus Chloroflexus . We next demonstrated that strains have diverged in temperature 41 range for growth. Specifically, we obtained evidence for a positive correlation between 42 thermal niche breadth and temperature optimum, with strains isolated from lower 43 temperatures exhibiting greater thermal specialization than the most thermotolerant 44 strain. The study has implications for our understanding of both the process of niche 45 diversification of microorganisms and how diversity is organized in these hot spring 46 communities.
Time-of-day inﬂuences on respiratory sequelae following maximal electroshock-induced seizures in mice

Time-of-day inﬂuences on respiratory sequelae following maximal electroshock-induced sei- zures in mice. J Neurophysiol 2017. unexpected death in epilepsy (SUDEP) is the leading cause of death in refractory epilepsy patients. Although speciﬁc mechanisms underlying SUDEP are not well understood, evidence suggests most SUDEP occurs due to seizure-induced respiratory arrest. SUDEP also tends to happen at night. Although this may be due to circumstances in which humans ﬁnd themselves at night, such as being alone without supervision or sleeping prone, or to independent inﬂuences of sleep state, there are a number of reasons why the night (i.e., circadian inﬂuences) could be an independent risk factor for SUDEP. We explored this possibility. Adult male WT mice were instrumented for EEG, EMG, and EKG recording and subjected to maximal electroshock (MES) seizures during wakefulness, non-rapid eye movement (NREM) sleep, and rapid eye movement (REM) sleep during the nighttime/dark phase. These data were compared with data collected following seizures induced during the daytime/light phase. Seizures induced during the nighttime were similar in severity and duration to those induced during the daytime; however, seizures induced during the nighttime were associated with a lesser degree of respiratory dysregulation and postictal EEG suppression. Seizures induced during REM sleep during the nighttime were universally fatal, as is seen when seizures are induced during REM during the daytime. Taken together, these data implicate a role for time of day in inﬂuencing the physiological consequences of seizures that may contribute to seizure-induced death. NEW & NOTEWORTHY Sudden unexpected death in epilepsy (SUDEP) is the leading cause of death in patients with refractory epilepsy. SUDEP frequently occurs during the night, which has been attributed to an effect of sleep. We have shown that sleep state does indeed inﬂuence survival following a seizure. That SUDEP occurs during the night could also implicate a circadian inﬂuence. In this study we found that time of day independently affects the physiological consequences of seizures.
Edinburgh Research Explorer Hetero-trans--glucanase, an enzyme unique to Equisetum plants, functionalises cellulose

Known transglycanase several however, no transglycanases were known to act on cellulose, the principal polysaccharide of We now report the discovery and characterization of hetero-trans- b - glucanase (HTG), a transglycanase that targets cellulose, in horsetails ( Equisetum spp., an early-diverging genus of monilophytes). HTG is also remarkable in predominantly catalysing hetero-transglycosylation: its preferred donor substrates (cel-lulose or mixed-linkage b - glucan) differ qualitatively from its acceptor substrate (xyloglucan). HTG thus gen-erates stable cellulose–xyloglucan and mixed-linkage b - glucan–xyloglucan covalent bonds, and may therefore strengthen ageing Equisetum tissues by inter-linking different structural polysaccharides of the cell wall. 3D modelling suggests that only three key amino acid substitutions (Trp ? Pro, Gly ? Ser and Arg ? Leu) are responsible for the evolution of HTG’s unique speciﬁcity from the better-known xyloglucan-act-ing homo-transglycanases (xyloglucan endotransglucosylase/hydrolases; XTH). Among land plants, HTG appears to be conﬁned to Equisetum , but its target polysaccharides are widespread, potentially offering opportunities for enhancing crop mechanical properties, such as wind resistance. In addition, by linking cellulose to xyloglucan fragments previously tagged with compounds such as dyes or indicators, HTG may be useful biotechnologically for manufacturing stably functionalized celluloses, thereby potentially offering a commercially valuable ‘green’ technology for industrially manipulating biomass.
Total Hip Replacement in Developmental Dysplasia Total Hip Replacement in Developmental Dysplasia

Total hip arthroplasty (THA) for osteoarthritis secondary to development dysplasia of the hip (DDH) is facing increasing levels of complexity with increasing grade of deformity. The dysplastic acetabulum is characterized by diminished bone stock with decreased lateral coverage. Therefore, it is challenging to restore the anatomic center of rotation and ensure adequate acetabular component fixation. Surgical strategies include a medializa - tion of the acetabular component, a higher hip center, lateral structural bone grafting and the selection of smaller component sizes to improve native bone coverage. Excessive femoral anteversion is commonly encountered in patients with developmental dysplasia. Moreover, the intramedullary canal is narrow and the neck often aligned in valgus. Modular implants are helpful to address the altered femoral anatomy and also facilitate femoral shortening osteotomies in patients with high hip dislocation. Although clinical results are comparable to primary total hip replacement in primary osteoarthritis, the risk for revision surgery due to dislocation and loosening is increased. The current chapter reviews classification, preoperative planning, and surgical strategies for patients under going THA for osteoarthritis secondary to developmental dysplasia.