Miracle-dz/UniFAR-FTUs huggingface dataset:
Expression of Programmed Death Ligand 1 (PD-L1) in Breast Cancer patients in India and its Correlation with Prognostic Parameters

Background: The PD-1/PD-L1 pathway represents an adaptive immune resistance mechanism that is exerted by tumor cells. The study was conducted to evaluate the expression of PD-L1 in breast carcinoma in India and to find out its correlation with prognostic parameters. Despite numerous studies, there is a lack of literature for such studies in Indian patients. Moreover, the results obtained from these studies have not been uniform. Methods: A hospital-based cross-sectional study was conducted on 150 cases of breast carcinoma. The invasive cancer specimens were assessed for routine microscopy and classified into various histopathological subtypes. Bloom Richardson grading was done. Immunohistochemistry for surrogate molecular classification as well as PD-L1 was performed. PD-L1 expression was then compared with several prognostic parameters such as tumor subtype, tumor grade, surrogate molecular classification and pTNM stage. Data analysis was done using Statistical Package for Social Sciences (SPSS) version 21.0. A P value of <0.05 was considered statistically significant. Results: PD-L1 was positive in 14.67% of patients with score 1 in 6% and score 2 in 8.67% of patients. The PD-L1 expression showed a positive correlation with the tumor of higher grades (grade3). It was significantly higher among IBC with medullary features as compared to IBC-NST, IBC with papillary features and the Lobular type. PD-L1 showed a significant association with surrogate molecular classification as well. Its expression was found to be the highest in Triple negative breast cancer subtype as compared to tumors showing ER/PR positivity (p<0.05). However, there was no significant association between PD-L1 and TNM staging. Conclusion: This study revealed a significant association between PD-L1 several prognostic factors such as higher tumor grade (grade3), Triple Negative breast cancer, and IBC with the medullary pattern subtype. The association between PD-L1 and such prognostic parameters signifies its role in tumor mechanism and makes it a potential target for immunotherapy especially in Triple Negative breast cancer cases which lack specific targeted therapies. Moreover, paucity of literature on PD-L1 in breast cancer patients in India and the data showing conflicting results make this study valuable. Our study shall be helpful in further adding to the knowledge of PD-L1 expression in breast cancer especially in Indian women.
Geomagnetic conjugate observations of ionospheric disturbances in response to a North Korean underground nuclear explosion on 3 September 2017

Abstract. We report observations of ionospheric disturbances in response to a North Korean underground nuclear explosion (UNE) on 3 September 2017. By using data from IGS (International GNSS Service) stations and Swarm satellites, geomagnetic conjugate ionospheric disturbances were observed. The observational evidence showed that UNE-generated ionospheric disturbances propagated radially from the UNE epicenter with a velocity of ∼280 m s−1. We propose that the ionospheric disturbances are results of electrodynamic process caused by LAIC (lithosphere–atmosphere–ionosphere coupling) electric field penetration. The LAIC electric field can also be mapped to the conjugate hemispheres along the magnetic field line and consequently cause ionospheric disturbances in conjugate regions. The UNE-generated LAIC electric field penetration plays an important role in the ionospheric disturbances in the region of the nuclear test site nearby and the corresponding geomagnetic conjugate points.
Forest damage and forest supply chains: a literature review and reflections

ABSTRACT Timber supply is affected by natural disruptions such as storms, wildfires, and insect infestations, which modify timber properties and disturb the supply to forest industries. Climate change threatens to increase the prevalence of forest damage and supply chain disturbances. This review analyzed the research between 2000 and 2022 on the effects of forest damage on wood supply chains and management measures to handle such disruptions. The review identified 23 studies from North America, Europe, and Australia and analyzed them regarding damage type and impact, research approach, and key findings. The literature on the topic covers the leading causes of damage: fire, wind damage, and insect infestation. In some cases, climate change was identified as the underlying cause of the supply disruptions. Research approaches involved calculations of consequences, scenario modeling, optimizations, and qualitative studies. This review identifies the essential considerations for successfully handling supply chains after forest damage. Robust supply warrants a range of adaptations, including choices for forest establishment, forest management methods, and collaborative planning. In addition, future research themes based on findings in the retrieved papers are suggested.
A Comparison of Linear and Nonlinear Univariate Models for Forecasting Macroeconomic Time Series

A forecasting comparison is undertaken in which 49 univariate forecasting methods, plus various forecast pooling procedures, are used to forecast 215 U.S. monthly macroeconomic time series at three forecasting horizons over the period 1959 - 1996. All forecasts simulate real time implementation, that is, they are fully recursive. The forecasting methods are based on four classes of models: autoregressions (with and without unit root pretests), exponential smoothing, artificial neural networks, and smooth transition autoregressions. The best overall performance of a single method is achieved by autoregressions with unit root pretests, but this performance can be improved when it is combined with the forecasts from other methods.
Cross-Shareholdings Structural Characteristic and Evolution Analysis Based on Complex Network

This study depicts the network morphology of firms which establish ties through cross-shareholdings by the theory of complex network analysis method. It calculates some complex network properties of the cross-shareholdings network and analyzes the evolution law of network structure in nearly 7 years. The network clearly displays small world properties and scale-free properties. The cross-shareholdings network average path length and clustering coefficient is with a small amplitude fluctuation; the network structure is relatively stable. Such a study is of practical importance and could provide opportunities for policy makers to improve the performance of the cross-shareholdings network.
Detector‐based approach for
 H
 filtering of Markov jump linear systems with partial mode information

The goal of this study is to present new results for H ∞ filtering for continuous-time Markov jump linear systems with partial information on the jumping parameter. The central hypothesis considered here is the existence of a suitable detector, which provides measurements of the Markov chain. Besides the interest in its own right, this detector-based approach allows us to treat, in a unified manner, the cases with complete observations, no information and cluster observations of the jumping process as particular scenarios. The main result comprises a method for designing a mean square stable linear H ∞ filter by using the information given by the detector, in the limit case where the sensors respond at much faster rates than the system dynamics. The proposed filter design is given in terms of parameterised linear matrix inequalities (LMIs), which are tackled through an iterative LMI-based algorithm. Furthermore, the result is applied to the state estimation of an unmanned aerial vehicle model.
Little‐v0 Agreement and Templatic Morphology in Ch'ol

This paper addresses typological differences in subject–verb agreement and provides evidence that transitive subject agreement need not always involve a high functional head, namely T0, but may instead be the result of a local relation between the subject and a low functional head, v0. In Mayan languages, grammatical relations are head-marked on the predicate through two series of morphemes, known as “Set A” (ergative/possessive) and “Set B” (absolutive). I argue that Set A morphemes reflect a local relationship of agreement between v0 and the transitive subject in its low base position and, in an analogous structural configuration in the nominal domain, between a possessive n0 head and the possessor. Crucially, I show that no higher functional projection is involved. This is important in light of proposals that ergative agreement systems are epiphenomenal, resulting from standard nominative agreement from T0 which is blocked from agreeing with morphologically case-marked ergative subjects (Woolford 2010). In this paper, I examine the morphologically ergative Mayan language Ch'ol to show that true ergative agreement is possible even in the absence of morphological case. This paper has implications for the typology of ergative case and agreement systems and contributes to our understanding of the nature of agreement and clitic doubling.
Robust H? Control for Sampled-data Dynamic Positioning Ships

This study is concerned with the robust H ? sampled-data control problem for dynamic positioning (DP) ships. Using the input delay approach, the ship dynamic positioning (DP) system is converted to a time-varying delay system. Sufficient conditions were then established to make the system exponentially stable with prescribed H ? performance using Lyapunov stability theorems. Then, the H ? sampled-data controller is obtained by means of linear matrix inequalities to guarantee that the DP ships can maintain the desired position, heading and velocities. Simulation result is shown that the proposed method and the designed controller for DP ships are effective in the existence of varying environment disturbance.
A validated shape optimization approach for maximizing the convective heat transfer from generic heat sink geometries

Improving the effectiveness of heat transfer devices is one of the most challenging and determinant processes for industrial situations involving energy transformation. Thermal simulations can enable engineers to try and assess different approaches to deal with a heat transfer situation, at a very early stage in the design process of a device. The enhancement of the heat transfer potential of a device, based on the optimization of its shape, has been reported by many authors. This thesis presents the development of a shape optimization procedure for maximizing the heat transfer from complex geometries by (i) establishing and validating a robust and low-cost computational fluid dynamics (CFD) method to predict the fluid flow and heat transfer of steady and unsteady convective heat transfer phenomena, and by (ii) incorporating the CFD model in an optimization loop which aims at searching for the optimal design that maximizes the heat transfer, using a genetic algorithm. In parallel, this study could enable the improvement of our understanding of coral growth as these living organisms rely on mass transfer processes to develop. In order to achieve the development of a shape optimization procedure that can be applied to complex geometries, and additionally, that can provide results comparable to situations specific to the living environment of corals, the investigation was done progressively. The idea is to study flow and heat transfer configurations around geometries of increasing complexity resulting in a shape optimization methodology applicable to a wide range of shape complexities. A genetic algorithm is used to search for optimal solutions over a high-dimension search-space that represents all the possible designs of a complex geometry. The study of how genetic algorithms operate in combination with CFD simulations is conducted in order to assess the shape optimization methodology.
A Microphysics Guide to Cirrus Clouds

Cirrus clouds still represent one of the largest uncertainties in the prediction of the Earth’s climate (IPCC, 2013) since their microphysical and radiative properties remain poorly or only partially characterized. One major reason is that it is difficult to measure these properties on fast-flying, high altitude aircraft. Another problem is that aircraft measurements cannot capture the evolution of the cirrus clouds properties with time. The most common parameters that are measured in cirrus clouds -besides the meteorological variablesare ice water content (IWC), number of ice crystals (Nice) and relative humidity (with respect to ice, RHice), and sometimes vertical velocity. However, it is difficult to deduce on the history of ice nucleation and development of microphysical properties from these observations.
Implementation of mutual information and bayes theorem for classification microarray data

Microarray Technology is one of technology which able to read the structure of gen. The analysis is important for this technology. It is for deciding which attribute is more important than the others. Microarray technology is able to get cancer information to diagnose a person’s gen. Preparation of microarray data is a huge problem and takes a long time. That is because microarray data contains high number of insignificant and irrelevant attributes. So, it needs a method to reduce the dimension of microarray data without eliminating important information in every attribute. This research uses Mutual Information to reduce dimension. System is built with Machine Learning approach specifically Bayes Theorem. This theorem uses a statistical and probability approach. By combining both methods, it will be powerful for Microarray Data Classification. The experiment results show that system is good to classify Microarray data with highest F1-score using Bayesian Network by 91.06%, and Naïve Bayes by 88.85%.
Decentralized intelligent tracking control for uncertain high‐order stochastic nonlinear strong interconnected systems in drift and diffusion terms

This paper focuses mainly on decentralized intelligent tracking control for a class of high‐order stochastic nonlinear systems with unknown strong interconnected nonlinearity in the drift and diffusion terms. For the control of uncertain high‐order nonlinear systems, the approximation capability of RBF neural networks is utilized to deal with the difficulties caused by completely unknown system dynamics and stochastic disturbances, and only one adaptive parameter is constructed to overcome the overparameterization problem. Then, to address the problem from high‐order strong interconnected nonlinearities in the drift and diffusion terms with full states of the overall system, by using the monotonically increasing property of the bounding functions, the variable separation technique is achieved. Lastly, based on the Lyapunov stability theory, a decentralized adaptive neural control method is proposed to reduce the number of online adaptive learning parameters. It is shown that, for bounded initial conditions, the designed controller can ensure the semiglobally uniformly ultimate boundedness of the solution of the closed‐loop system and make the tracking errors eventually converge to a small neighborhood around the origin. Two simulation examples including a practical example are used to further illustrate the effectiveness of the design method.
Dynamical ages of the young local associations with Gaia

Context. The young local associations (YLAs) constitute an excellent sample for the study of a variety of astrophysical topics, especially the star formation process in low-density environments. Data from the Gaia mission allows us to undertake studies of the YLAs with unprecedented accuracy. Aims. We determine the dynamical age and place of birth of a set of associations in a uniform and dynamically consistent manner. There are nine YLAs in our sample ϵ Chamaeleontis, TW Hydrae, β Pictoris, Octans, Tucana-Horologium, Columba, Carina, Argus, and AB Doradus. Methods. We designed a method for deriving the dynamical age of the YLAs based on the orbital integration. The method involves a strategy to account for the effect of observational errors. We tested the method using mock YLAs. Finally, we applied it to our set of nine YLAs with astrometry from the first Gaia data release and complementary on-ground radial velocities from the literature. Results. Our orbital analysis yields a first estimate of the dynamical age of 33−0+9 Myr, 1313−0+7 Myr, and 55−0+23 Myr for ϵ Chamaeleontis, β Pictoris, and Tucana-Horologium, respectively. For four other associations (Octans, Columba, Carina, and Argus), we provide a lower limit for the dynamical age. Our rigorous error treatment indicates that TW Hydrae and AB Doradus deserve further study. Conclusions. The dynamical ages that we obtain are compatible spectroscopic and isochrone fitting ages obtained elsewhere. From the orbital analysis, we suggest a scenario for these YLAs where there were two episodes of star formation: one ~40 Myr ago in the first quadrant that gave birth to ϵ Chamaeleontis, TW Hydrae, and β Pictoris, and another 5−15 Myr ago close to the Sun that formed Tucana-Horologium, Columba, and Carina. Future Gaia data will provide the necessary accuracy to improve the present results, especially for the controversial age determinations, and additional evidence for the proposed scenario once a complete census of YLAs and better membership can be obtained.
Factors Affecting Quality of Accounting Information and its impact on local government fixed assets management's effectiveness: A study on Local Government of Indonesia

: Inseparable from managing regional fixed assets is the quality of information or data utilized by each unit. The quality of accounting information in government is heavily dependent on the leadership's commitment, the effectiveness of internal control, and the execution of good governance, according to various published works; nevertheless, this must be demonstrated further. Consequently, this study aims to investigate the link and size of the influence of these three elements on the quality of accounting information and their impact on the efficacy of local government fixed asset management. In Indonesia, 34 provincial governments, 416 district governments, and 98 city governments were surveyed for this quantitative research. This study included 529 participants. The research data was gathered using a questionnaire instrument that included in-person interviews—data analysis using the Structural Equation Modeling (SEM) method with Lisrel 8.8 statistical software. The explanation of research findings is both descriptive and causally explanatory. In general, local governments in Indonesia have excellent accounting data and management of fixed assets. In carrying out local government tasks, the local government has also built an effective internal control system and excellent governance. The study's findings demonstrate that the effectiveness of internal control and the function of good governance substantially impact the quality of accounting data. Similarly, leadership commitment, the importance of good governance, and the accuracy of accounting information substantially impact the success of fixed asset management. However, internal control efficacy does not significantly impact managing local governments' fixed assets.
First a tragedy, then farce

It is impossible to think about the problems in the UK over the last 10 months arising from the £80m shortfall in the budget of the Science and Technology Facilities Council (STFC) without recalling Marx's famous aphorism: "History repeats itself, first as tragedy, then as farce. " Certainly the repetition of a funding crisis in UK particle physics and astronomy is hardly unexpected; they seem to occur every decade or so with unwelcome regularity. The consequent loss of morale, jobs and opportunities in the UK for the brightest young people to pursue their dreams in what is widely acknowledged to be world-class science is a tragedy. What perhaps marks the uniqueness of the funding crisis this time round is the level of farce. The sums that did not add up; the consultations without interlocutors; and the truculent and damaging statements about withdrawal from the Gemini telescopes based in Hawaii and Chile, and the International Linear Collider (ILC) – the next big particle-physics project after the Large Hadron Collider (LHC) at CERN.
THE DEVELOPMENT OF A VALIDATED MODEL OF ORTHODONTIC MOVEMENT OF THE MAXILLARY CENTRAL INCISOR IN THE HUMAN SUBJECT

A progressive approach to the modeling of orthodontic tooth movement is described. A novel method of experimental validation of a three dimensional model of a human maxillary central incisor is presented. By this approach an appropriate figure for the Elastic Modulus and Poisson's Ratio for the periodontal ligament (PDL) were determined to be 1.0 N/mm 2 and 0.45 respectively.
Biochemical and electrolytes analysis of colic in indigenous breeds of horses

Colic is most important clinical problem in horses. Role of biochemical and electrolyte analysis in the diagnosis and prognosis clinical problems is very important. Present study was carried out to see the biochemical and electrolyte changes with different types of colic in indigenous horses belonging to Marwari, Zanskari and Manipuri breed of horses kept at an organised farm at Bikaner. Data of clinical cases were recorded for 8 months. Serum biochemical analyses were carried out using commercially available kits. On biochemical and electrolyte analysis no significant change was observed except few parameters. All the cases of spasmodic cases responded well to the primary treatment for colic.
Cellular response of pulp fibroblast to single or multiple photobiomodulation applications

This study aimed to evaluate in vitro the effects of single or multiple photobiomodulation (PBM) applications on the viability and proliferation of pulp fibroblasts. Pulp fibroblasts from human deciduous teeth were obtained from a biorepository, plated into 96-well plates, and irradiated according to the experimental groups. At 24 h, 48 h, and 72 h after irradiation, cell viability and proliferation were assessed through MTT and Crystal Violet assays, respectively. The intragroup comparison revealed statistically significant differences for 2.5 J cm−2 (3×) with increasing viability at 72 h over 48 h (p = 0.027). The intergroup analysis showed a greater viability of the multiple PBM applications 2.5 J cm−2 (3×) over the single application 7.5 J cm−2 (1×) at 72 h. The application of 5 J cm−2 (1×) exhibited greater proliferation than the application of 7.5 J cm−2 (1×), 2.5 J cm−2 (2×) and 2.5 J cm−2 (3×). Single or multiple PBM applications demonstration different stimulatory effects on pulp fibroblast. The results show that the group submitted to multiple irradiation presented significantly higher cell viability than the groups with single irradiation at 72 h. However, the photobiomodulation therapy with single irradiations was more effective on cell proliferation at 24 h.