Miracle-dz/UniFAR-FTUs huggingface dataset:
Six Sigma: a literature review

Purpose – The purpose of the work presented in this paper is to capture the current state of Six Sigma as well as to document the current practices of Six Sigma through a systematic literature review so as to extend and update the previous work of Brady and Allen.Design/methodology/approach – The approach to this paper is to answer the questions such as “what is Six Sigma? ”, “what are the applications of the Six Sigma? ”, “what are the main enablers and barriers to its application? ” and “what are the emerging trends? ” These questions are used to guide the search of papers from various publication databases even if it is expected that existing literature might not be sufficiently developed to translate each question directly into a finding. The literature is then analysed and the major emerging themes are presented.Findings – Seven key findings (topics on which the views of the authors converged) and two issues (topics on which authors had differing views) have been established. These include the interpreta.
Pediatric Acute Respiratory Distress Syndrome (PARDS) On Pediatric COVID-19 Patients

At the end of 2019, there was a pandemic happening in the world, called the novel Coronavirus disease-19 (COVID-19). Various spectrums of disease from COVID-19, one of which is ARDS. The incidence of COVID-19 in children is not as much as in adults. However, in children under one year of age it can get worse. The main characteristic of worsening infection is the occurrence of ARDS. Objective: To find out the best treatment for PARDS in COVID-19 patients. Method: The writing of this article uses various sources from scientific journals to government guidelines and related institutions. Search articles using the keywords “Acute Respiratory Distress Syndrome”, “ARDS”, “Pediatric Respiratory Distress Syndrome”, “PARDS”, and “PARDS on COVID-19” Result and Discussion: PARDS was defined based on PALICC in 2015. Pathophysiology of PARDS in COVID-19 patients is still unclear. However, there is a theory that explains the way SARS-Cov-2 enters cells, namely through membrane fusion, giving rise to ARDS. The difference in handling PARDS for COVID-19 patients is that the handling technique is more alert to the risk of aerosols. Conclusions: There are differences in the handling of PARDS for COVID-19 patients in the technique by reducing the risk of virus transmission by preventing leakage when using a ventilator and using a bacterial/virus filter, as well as rescuers and staff using complete PPE during the procedure.
Rare risk variants associate with epigenetic dysregulation in migraine

Migraine has a heritability of up to 65%. Genome-wide association studies (GWAS) on migraine have identified 123 risk loci, explaining only 10.6% of migraine heritability. Thus, there is a considerable genetic component not identified with GWAS. Further, the causality of the identified risk loci remains inconclusive. Rare variants contribute to the risk of migraine but GWAS are often underpowered to detect these. Whole genome sequencing is reliable for analyzing rare variants but is not frequently used in large-scale. We assessed if rare variants in the migraine risk loci associated with migraine. We used a large cohort of whole genome sequenced migraine patients (1,040 individuals from 155 families). The findings were replicated in an independent case-control cohort (2,027 migraine patients, 1,650 controls). We found rare variants (minor allele frequency<0.1%) associated with migraine in a Polycomb Response Element in the ASTN2 locus. The association was independent of the GWAS lead risk variant in the locus. The findings place rare variants as risk factors for migraine. We propose a biological mechanism by which epigenetic regulation by Polycomb Response Elements plays a crucial role in migraine etiology.
Cooperation among an anonymous group protected Bitcoin during failures of decentralization

Bitcoin is a digital currency designed to rely on a decentralized, trustless network of anonymous agents. Using a pseudonymous-address-linking procedure that achieves >99% sensitivity and >99% specificity, we reveal that between launch (1/3/2009), and when the price reached $1 (2/9/2011), most bitcoin was mined by only sixty-four agents. This was due to the rapid emergence of Pareto distributions in bitcoin income, producing such extensive resource centralization that almost all contemporary bitcoin addresses can be connected to these top agents by a chain of six transactions. Centralization created a social dilemma. Attackers could routinely exploit bitcoin via a “51% attack”, making it possible for them to repeatedly spend the same bitcoins. Yet doing so would harm the community. Strikingly, we find that potential attackers always chose to cooperate instead. We model this dilemma using an N-player Centipede game in which anonymous players can choose to exploit, and thereby undermine, an appreciating good. Combining theory and economic experiments, we show that, even when individual payoffs are unchanged, cooperation is more frequent when the game is played by an anonymous group. Although bitcoin was designed to rely on a decentralized, trustless network of anonymous agents, its early success rested instead on cooperation among a small group of altruistic founders. One Sentence Summary: Combining data leakage from the bitcoin blockchain with economic experiments, we study responses to a social dilemma in a group of anonymous individuals. Main Text: Cooperation, critical for most forms of social organization, entails individual sacrifice so that others can derive a benefit. Anonymity can interfere with the cooperative mechanisms of reciprocity, relatedness and reputation and is thus believed to reduce cooperation in general (1).
Do Coarse Mass Particles Increase Daily Mortality? New Findings from a Multi-Country, Multi-City Study

the INCREASE trial. Am J Respir Crit Care Med 2022;205:198–207. 7. Jandl K, Marsh LM, Mutgan AC, Crnkovic S, Valzano F, Zabini D, et al. Impairment of the NKT–STAT1–CXCL9 axis contributes to vessel fibrosis in pulmonary hypertension caused by lung fibrosis. Am J Respir Crit Care Med 2022;206:981–998. 8. Kim JH, Kim HY, Kim S, Chung JH, Park WS, Chung DH. Natural killer T (NKT) cells attenuate bleomycin-induced pulmonary fibrosis by producing interferon-g. Am J Pathol 2005;167:1231–1241. 9. Kimura T, Ishii Y, Morishima Y, Shibuya A, Shibuya K, Taniguchi M, et al. Treatment with a-galactosylceramide attenuates the development of bleomycin-induced pulmonary fibrosis. J Immunol 2004;172:5782–5789. 10. Gairhe S, Awad KS, Dougherty EJ, Ferreyra GA, Wang S, Yu ZX, et al. Type I interferon activation and endothelial dysfunction in caveolin-1 insufficiency-associated pulmonary arterial hypertension. Proc Natl Acad Sci USA 2021;118:e2010206118. 11. Savale L, Sattler C, G€ unther S, Montani D, Chaumais MC, Perrin S, et al. Pulmonary arterial hypertension in patients treated with interferon. Eur Respir J 2014;44:1627–1634. 12. Ormiston ML, Chang C, Long LL, Soon E, Jones D, Machado R, et al. Impaired natural killer cell phenotype and function in idiopathic and heritable pulmonary arterial hypertension. Circulation 2012;126: 1099–1109. 13. R€ atsep MT, Moore SD, Jafri S, Mitchell M, Brady HJM, Mandelboim O, et al. Spontaneous pulmonary hypertension in genetic mouse models of natural killer cell deficiency. Am J Physiol Lung Cell Mol Physiol 2018;315:L977–L990. 14. Christmann RB, Sampaio-Barros P, Stifano G, Borges CL, de Carvalho CR, Kairalla R, et al. Association of interferonand transforming growth factor b-regulated genes and macrophage activation with systemic sclerosis-related progressive lung fibrosis. Arthritis Rheumatol 2014;66: 714–725. 15. Elinoff JM, Agarwal R, Barnett CF, Benza RL, Cuttica MJ, Gharib AM, et al. Challenges in pulmonary hypertension: controversies in treating the tip of the iceberg. A joint National Institutes of Health Clinical Center and Pulmonary Hypertension Association symposium report. Am J Respir Crit Care Med 2018;198:166–174.
The development of nasal turbinal morphology of moles and shrews

The phylogenetic relationships of major groups within the Order Eulipotyphla was once highly disputed, but the advent of molecular studies has greatly improved our understanding about the diversification history of talpids, soricids, erinaceids, and solenodontids. Their resolved phylogenetic relationships now allow us to revisit the turbinal and lamina evolution of this group. The inner structure of the nasal cavity of mammals is highly complicated and the homologies of the turbinals among mammalian species are still largely unsettled. In this regard, investigation on fetal anatomy and ontogenetic changes of the nasal capsule allows us to evaluate the homologies of the turbinals and laminae. We observed various fetuses and adults of talpids and soricids using high-resolution diffusible iodine-based contrast-enhanced computed tomography (diceCT) and reviewed previous reports on erinaceids, solenodontids, and other laurasiatherians. Although the turbinal and lamina morphology was previsouly considered to be similar among eulipotyphlans, we found phylogenetic patterns for talpids and soricids. The nasoturbinal of the common ancestor of talpids and soricids was most likely rostrocaudally elongated. The epiturbinal at the ethmoturbinal II disappeared in soricids independently. Finally, we propose two possible scenarios for the maxilloturbinal development: 1) the maxilloturbinal of talpids and soricids became small independently with a limited number of lamellae as a result of convergent evolution, or 2) the common ancestor of talpids and soricids already had a small and simple maxilloturbinal.
Inelastic scattering approach to the theory of a tunnel magnetic transistor source

The high efficiency of a tunnel magnetic transistor as a source of spin-polarized electrons has been proven recently [X. Jiang {\it et al.}, Phys. Rev. Lett. {\bf 90}, 256603 (2003)]. A concept of this device based on an active group of hot electrons controlling the collector current and experiencing predominantly inelastic scattering in the base is developed. It takes into account the interconnection between the injection and filtering of spin-polarized electrons in different elements of the device. Explicit expressions for the parameters of the device in terms of the basic parameters of the system are presented.
Virtual neighborhood technique for pseudo-holomorphic spheres

This is the first part of a trilogy where we apply the theory of virtual manifold/orbifolds developed by the first named author and Tian to study the Gromov-Witten moduli spaces. In this paper, we resolve the main analytic issue arising from the lack of differentiability of $PSL(2, \C)$-action on spaces of $W^{1, p}$-maps from the Riemann sphere to a symplectic manifold $(X, \omega, J)$ with a non-zero homology class $A$. In particular, we establish the slice and tubular neighbourhood theorems for $PSL(2, \C)$-action along smooth maps, and construct a $PSL(2, \C)$-obstruction bundle along $PSL(2, \C)$-orbit of a pseudo-holomorphic map representing a point in the moduli space $\cM_{0, 0}(X, A)$. In Sections 2 and 3 of this paper, we explain an integration theory on virtual orbifolds using proper \'etale groupoids and establish the virtual neighborhood technique for a general orbifold Fredholm system. When the moduli space $\cM_{0, 0}(X, A)$ of pseudo-holomorphic spheres in $(X, \omega, J)$ is compact, applying the virtual neighborhood technique developed in Section 3, we obtain a virtual system for the moduli space $\cM_{0, 0}(X, A)$ of pseudo-holomorphic spheres in $(X, \omega, J)$ and show that the genus zero Gromov-Witten invariant is well-defined.
A Numerical Model of the Flow and Heat Transfer in a Rotating Disk Chemical Vapor Deposition Reactor

Steady, laminar, axisymmetric and circumferentially uniform flow and heat transfer, including the effects of variable properties and buoyancy, have been modeled within a rotating disk chemical vapor deposition (CVD) reactor. The reactor is oriented vertically, with the hot, isothermal, spinning disk facing upward. The Navier-Stokes and energy equations have been solved for the carrier gas helium, at atmospheric pressure. The solutions have been obtained over a range of parameters which is of importance in CVD applications. The primary parameters are the ratio of the disk temperature to the free stream temperature T/sub . omega. //T/sub infinity/, the disk Reynolds number Re = r/sub d//sup 2/. omega. /. nu. /sub infinity/, a mixed convection parameter Gr/Re/sup 3/2/ = g(1 - rho/sub .omega.//rho/sub infinity/)/(.omega sqrt omega nu./sub infinity/), the dimensionless inlet velocity u/sub infinity//. sqrt omega nu. /sub infinity/, and two geometric parameters r/sub 0//r/sub d/ and L/r/sub d/. Results are obtained for the velocity and the temperature fields and for the heat flux at the surface of the rotating disk. Comparisons are made with the one-dimensional, variable properties (excluding buoyant effects), infinite rotating disk solutions of Pollard and Newman. Results are presented in terms of a local Nusselt number. The potential uniformity of CVD in this geometry can bemore » inferred from the variation of the Nusselt number over the surface of the rotating disk. The effects of buoyancy and the finite size of the rotating disk within the cylindrical reactor evident. « less
Towards Automation in IVF: Pre-Clinical Validation of a Deep Learning-Based Embryo Grading System during PGT-A Cycles

Preimplantation genetic testing for aneuploidies (PGT-A) is arguably the most effective embryo selection strategy. Nevertheless, it requires greater workload, costs, and expertise. Therefore, a quest towards user-friendly, non-invasive strategies is ongoing. Although insufficient to replace PGT-A, embryo morphological evaluation is significantly associated with embryonic competence, but scarcely reproducible. Recently, artificial intelligence-powered analyses have been proposed to objectify and automate image evaluations. iDAScore v1.0 is a deep-learning model based on a 3D convolutional neural network trained on time-lapse videos from implanted and non-implanted blastocysts. It is a decision support system for ranking blastocysts without manual input. This retrospective, pre-clinical, external validation included 3604 blastocysts and 808 euploid transfers from 1232 cycles. All blastocysts were retrospectively assessed through the iDAScore v1.0; therefore, it did not influence embryologists’ decision-making process. iDAScore v1.0 was significantly associated with embryo morphology and competence, although AUCs for euploidy and live-birth prediction were 0.60 and 0.66, respectively, which is rather comparable to embryologists’ performance. Nevertheless, iDAScore v1.0 is objective and reproducible, while embryologists’ evaluations are not. In a retrospective simulation, iDAScore v1.0 would have ranked euploid blastocysts as top quality in 63% of cases with one or more euploid and aneuploid blastocysts, and it would have questioned embryologists’ ranking in 48% of cases with two or more euploid blastocysts and one or more live birth. Therefore, iDAScore v1.0 may objectify embryologists’ evaluations, but randomized controlled trials are required to assess its clinical value.
Research Progress on Cannabinoids in Cannabis (Cannabis sativa L.) in China

Cannabis (Cannabis sativa L.) is an ancient cultivated plant that contains less than 0.3% tetrahydrocannabinol (THC). It is widely utilized at home and abroad and is an economic crop with great development and utilization value. There are 31 countries legalizing industrial cannabis cultivation. Cannabis fiber has been used for textile production in China for 6000 years. China is the largest producer and exporter of cannabis. China may still play a leading role in the production of cannabis fiber. China has a long history of cannabis cultivation and rich germplasm resources. Yunnan, Heilongjiang, and Jilin are three Chinese provinces where industrial cannabis can be grown legally. Cannabinoids are terpenoid phenolic compounds produced during the growth, and which development of cannabis and are found in the glandular hairs of female flowers at anthesis. They are the active chemical components in the cannabis plant and the main components of cannabis that exert pharmacological activity. At the same time, research in China on the use of cannabis in the food industry has shown that industrial cannabis oil contains 13–20% oleic acid, 40–60% omega-6 linoleic acid, and 15–30% omega-3 α-linolenic acid. At present, more than 100 cannabinoids have been identified and analyzed in China, among which phenolic compounds are the main research objects. For instance, phenolic substances represented by cannabidiol (CBD) have rich pharmacological effects. There are still relatively little research on cannabinoids, and a comprehensive introduction to research progress in this area is needed. This paper reviews domestic and foreign research progress on cannabinoids in cannabis sativa, which is expected to support cannabis-related research and development.
University of Birmingham Multi-stream online transfer learning for software effort estimation

Software Effort Estimation (SEE) may suffer from changes in the relationship between features describing software projects and their required effort over time, hindering predictive performance of machine learning models. To cope with that, most machine learning-based SEE approaches rely on receiving a large number of Within-Company (WC) projects for training over time, being prohibitively expensive. The approach Dycom reduces the number of required WC training projects by transferring knowledge from Cross-Company (CC) projects. However, it assumes that CC projects have no chronology and are entirely available before WC projects start being estimated. Given the importance of taking chronology into account to cope with changes, it may be beneficial to also take the chronology of CC projects into account. This paper thus investigates whether and under what circumstances treating CC projects as multiple data streams to be learned over time may be useful for improving SEE. For that, an extension of Dycom called OATES is proposed to enable multi-stream online learning, so that both incoming WC and CC data streams can be learnt over time. OATES is then compared against Dycom and five other approaches on a case study using four different scenarios derived from the ISBSG Repository. The results show that OATES improved predictive performance over the state-of-the-art when the number of CC projects available beforehand was small. Learning CC projects over time as multiple data streams is thus recommended for improving SEE in such scenario. When the number of CC projects available before-hand was large, OATES obtained similar predictive performance to the state-of-the-art. Therefore, CC data streams are unnecessary in this scenario, but are not detrimental either.
The Need for a Fresh Approach to Climate Change Economics

The complete workshop proceedings, including video of 17 expert presentations, this summary report, and individual off­prints of expert papers are available free of charge from the Pew Center on Global Climate Change at Abstract The integrated assessment models (IAMs) that economists use to analyze the expected costs and benefits of climate policies frequently suggest that the " optimal " policy is to do relatively little in the near term to reduce greenhouse gas emissions. This conclusion seemingly conflicts with the emerging scientific consensus about the irreversibility of climate change and the risks of catastrophic impacts. We trace this disconnect to contestable assumptions and limitations of IAMs when applied to climate change. For example, they typically discount future impacts from climate change at relatively high rates that are empirically and philosophically controversial when applied to intergenerational environmental issues. IAMs also monetize the benefits of climate mitigation on the basis of incomplete and sometimes speculative information about the worth of human lives and ecosystems and fail to account for the full range of scientific uncertainty about the extent of expected damages. IAMs may also exaggerate mitigation costs by inadequately capturing the socially determined, path‐dependent nature of technological change and ignoring the potential savings from reduced energy utilization and other opportunities for innovation. A better approach to climate policy, drawing on recent research on the economics of uncertainty, would avoid the limitations of the narrow cost‐benefit comparisons of IAMs and reframe the cost of mitigation as buying insurance against irreversible and catastrophic events, the avoidance of which would yield large but unquantifiable benefits. Policy decisions should be based on a judgment concerning the maximum tolerable increase in temperature and/or atmospheric carbon dioxide concentrations given the state of scientific understanding. In this framework, the appropriate role for economists would be to determine the least‐cost strategy to achieve that target. 1 A more technical version of this paper titled " Limitations of Integrated Assessment Models of Climate Change " is forthcoming in Climatic Change. 2 The listing of authors is alphabetical and does not imply precedence.
RE-SORT: Removing Spurious Correlation in Multilevel Interaction for CTR Prediction

Click-through rate (CTR) prediction is a critical task in recommendation systems, serving as the ultimate filtering step to sort items for a user. Most recent cutting-edge methods primarily focus on investigating complex implicit and explicit feature interactions; however, these methods neglect the spurious correlation issue caused by confounding factors, thereby diminishing the model's generalization ability. We propose a CTR prediction framework that REmoves Spurious cORrelations in mulTilevel feature interactions, termed RE-SORT, which has two key components. I. A multilevel stacked recurrent (MSR) structure enables the model to efficiently capture diverse nonlinear interactions from feature spaces at different levels. II. A spurious correlation elimination (SCE) module further leverages Laplacian kernel mapping and sample reweighting methods to eliminate the spurious correlations concealed within the multilevel features, allowing the model to focus on the true causal features. Extensive experiments conducted on four challenging CTR datasets, our production dataset, and an online A/B test demonstrate that the proposed method achieves state-of-the-art performance in both accuracy and speed. The utilized codes, models and dataset will be released at https://github.com/RE-SORT.
Heterogeneity and soil element testing

Studies of strains within granular assemblies using digital image correlation have shown that as the resolution of observation becomes finer so the detail of the local variations of strains becomes more complex. The scale of this observed complexity is typically of the order of a few (5–10? ) particles. The notion of a localised shear band of uniform shear or volumetric strain is not easily supported. In addition, studies reveal somewhat regular patterns of heterogeneity within samples which have been subjected to uniform external boundary deformations. A heterogeneous state is the natural state for granular materials. These observations have implications for the scales that should be adopted for testing of granular materials either in single-element or in physical model tests. Testing of a single element of a size that just accommodates a single region of ‘localisation’ will inevitably impose constraints on the particles in this region. On the other hand, one can envisage a representative element that is .