Miracle-dz/UniFAR-FTUs huggingface dataset:
The Logics of Preference: A Study of Prohairetic Logics in Twentieth Century Philosophy

One The Objectivist Approach Toward the Formalization of Preferences. - 1. Prototheoretic Attempts Toward a Logic of Preference. - 2. Aristotelean Reflections in Richard M. Martin's Extensionalized Pragmatics of Preference. - 3. Rescher's Logic of Preference and Linguistic Analysis. - 4. Richard C. Jeffrey's Logic of First and Higher-Order Preferences. - Two The Subjectivist Approach Toward the Formalization of Preferences. - 5. Soren Hallden's "Puristic" Logic of the Better and Same. - 6. The Many Modal Interpretations of Prohairetic Logic: Aqvist, Chisholm, Sosa and Hansson. - 7. Von Wright's Logic of Propositions Expressing Preferences. - 8. Hochberg on the Logic of "Extrinsic Epistemic Preferability". - Postcript. - Selected Bibliography. - Name Index.
The Relationship Between Health Literacy and Outcomes Before and After Kidney Transplantation

Background. Limited health literacy (HL) is associated with decreased kidney function and death in patients with chronic kidney disease. Less is known about the impact of HL on kidney transplant (KT) outcomes. The aim of this study was to examine the relationship between HL and KT outcomes, including rates of waitlisting, healthcare utilization, acute rejection, renal allograft function, renal allograft failure, and death. Methods. We performed a retrospective review of HL data previously collected at our center. HL was assessed in a convenience sample of consecutive, English-speaking patients age ≥18 y who were evaluated for KT at Mayo Clinic in Minnesota between June 2015 and March 2017 as part of a practice improvement feasibility project (n = 690). HL was assessed using the 4-item Brief Health Literacy Screening Tool modified for the outpatient KT evaluation process. The 4 items assess confidence completing forms, reading comprehension, and oral literacy. Results. Overall, 30.4% of patients had limited or marginal HL. Patients with limited or marginal HL were less likely than those with adequate HL to be waitlisted for KT (hazard ratio = 0.62 and 0.69, respectively), even after adjusting for age, marital status, body mass index, Charlson comorbidity index, or dialysis dependency. Patient HL was not associated with post-KT healthcare utilization, acute rejection, or renal allograft function. Patients with limited or marginal HL appeared to experience a higher risk of renal allograft failure and post-KT death, but the number of events was small, and the relationship was statistically significant only for marginal HL. Conclusions. Inadequate HL is common in KT candidates and independently associated with decreased waitlisting for KT. We observed no statistically significant relationship between HL and posttransplant outcomes in our cohort. Further efforts to improve communication in patients with inadequate HL may improve access to KT.
Automated Decision Optimization with Reinforcement Learning

Sequential decision making under uncertainty has many practical real-world applications, ranging from supply-chain management to autonomous driving. Reinforcement learning has recently emerged as a promising technique for solving these kinds of problems. However, reinforcement learning algorithms are known to be highly sensitive to their internal hyperparameters which require significant expert manual effort for tuning their values. This in turn limits the widespread applicability of reinforcement learning based solutions in practice. In this paper, we introduce a new automated decision optimization system called AutoDO for end-to-end solving of sequential decision making problems. More specifically, the system not only automatically selects the best reinforcement learning algorithm but it also finds the best configuration of its hyperparameters using a search strategy based on limited discrepancy search coupled with Bayesian optimization. Furthermore, our system supports several different flavours of reinforcement learning including online and offline as well as model-free and model-based algorithms. We experiment with classical control benchmarks as well as a more realistic inventory management problem. Our results show that the proposed system is competitive and often outperforms existing state-of-the-art in terms of the quality of the solutions found.
05 02 03 6 v 1 3 F eb 2 00 5 Schrödinger representation of SU ( 2 )

Exploiting the SU(2) Skyrmion Lagrangian with second-class constraints associated with Lagrange multiplier and collective coordinates, we convert the second-class system into the first-class one in the Batalin-Fradkin-Tyutin embedding through introduction of the Stückelberg coordinates. In this extended phase space we construct the “canonical” quantum operator commutators of the collective coordinates and their conjugate momenta to describe the Schrödinger representation of the SU(2) Skyrmion, so that we can define isospin operators and their Casimir quantum operator and the corresponding eigenvalue equation possessing integer quantum numbers, and we can also assign via the homotopy class π4(SU(2)) = Z2 half integers to the isospin quantum number for the solitons in baryon phenomenology. Different from the semiclassical quantization previously performed, we exploit the “canonical” quantization scheme in the enlarged phase space by introducing the Stückelberg coordinates, to evaluate the baryon mass spectrum having global mass shift originated from geometrical corrections due to the S compact manifold involved in the topological Skyrmion. Including ghosts and anti-ghosts, we also construct Becci-Rouet-Stora-Tyutin invariant effective Lagrangian.
2 2 1 M ar 2 00 5 Helstrom Theorem by No-Signaling Condition

Quantum bits (qubits) are fundamentally different from classical bits in that unknown qubits cannot be copied with unit efficiency [1, 2, 3] (no-cloning theorem). Another related property of qubits is that nonorthogonal qubits cannot be distinguished with certainty [4]. Interestingly, however, it has been found that the nosignaling condition is entangled with other impossibility proofs [5, 6, 7, 8]. In particular, it has been shown that no-signaling condition gives the same tight bound on probability of conclusive measurement as obtained by quantum mechanical formula [7]. In this paper, we add one in the list of theorems that can be proven by the no-signaling condition. We prove a special case of Helstrom theorem [9]. Result in this paper is closely related to other’s works but different. In particular, our argument is quite similar to the one in Ref. [5]. Our contribution is an observation that violation of Helstrom theorem implies that two appropriately chosen (different) decompositions of the same density operator can be discriminated. This paper is organized as follows. We describe the proposition that we will prove. We prove it by no-signaling condition and then we conclude. Roughly speaking, Helstrom theorem means that the more non-orthogonal two qubits are, the more difficult it is to discriminate them by positive-operator-valuedmeasurement [4]. Let us consider a special case of Helstrom theorem. Proposition-1: Consider two non-orthogonal qubits, |α〉 and |β〉, whose overlap, |〈α|β〉|2, is between 0 and 1. We are given a qubit that is either |α〉 or |β〉 with equal a priori probability, 1/2. We want to identify the qubit quantum mechanically. Identifier of the qubit gives either an output, 0, or the other output, 1. PE is the probability of making error in the identification. Minimal value of PE is given by P m E = (1/2)[1− √
Exchange Bias Theory: a Review

Research on the exchange bias (EB) phenomenon has witnessed a flurry of activity during recent years, which stems from its use in magnetic sensors and as stabilizers in magnetic reading heads. EB was discovered in 1956 but it attracted only limited attention until these applications, closely related to giant magnetoresistance, were developed during the last decade. In this review I first give a short introduction, listing the most salient experimental results and what is required from an EB theory. Next, I indicate some of the obstacles in the road towards a satisfactory understanding of the phenomenon. The main body of the text reviews and critically discusses the activity that has flourished, mainly during the last five years, in the theoretical front. Finally, an evaluation of the progress made, and a critical assessment as to where we stand nowadays along the road to a satisfactory theory, is presented.
Multiple Hypothesis Correlation for Space Situational Awareness

Abstract : The primary objective of this program is to perform the necessary basic research to support the development of a statistical, multiple hypothesis tracker (MHT) for space surveillance. Such a MHT framework can serve as the next generation space surveillance system to maintain the space catalog, to identify uncorrelated tracks, and to support conjunction analysis and sensor resource management. Key components in such a system include a consistent characterization of uncertainty, physical modeling, multiple model filtering, and the association problem of determining which tracklets/measurements emanate from which object. To achieve a consistent characterization of uncertainty, Numerica has developed an adaptive Gaussian sum filter which correctly represents and propagates uncertainties and adaptively selects the correct the number of Gaussians in the mixture. Realtime online metrics support the coarsening and refining of the filter to maintain consistent uncertainty.
Chord2DS: An Extension to Chord Diagram to Show Data Elements from Two Heterogeneous Data Sources

The standard Chord diagram, a radial layout, shows data elements in a circular fashion from one data source. In this paper, we propose an extension to the standard Chord diagram to show data elements from two heterogeneous data sources into one single diagram. The main Chord diagram is used for showing data elements and the relations between them from one data source, while we use an outer layer to show data elements from the second data source. The relationships between data elements from both data sources are shown through visual cues. The proposed solution uses space efficiently compared to using multiple diagrams in the scenarios of two heterogeneous data sources
Extraction Optimization and Antibacterial Property of Total Flavonoids from Zizania Latifolia Bracts and the Effect on Chilled Pork Preservation

: Zizania latifolia is a widely distributed aquatic vegetable, and its bracts are an agricultural waste with a large proportion. In this study, Total Flavonoids of Z. latifolia Bracts (TFZB) were extracted with Ultrasound-Assisted Enzymatic Extraction (UAEE) for the first time, and the extraction process was optimized using Response Surface Method (RSM), and compared with other methods. Then, the antibacterial activity of TFZB extracted with optimized UAEE was assessed and the effects on chilled pork preservation were investigated. The optimal UAEE conditions for TFZB were: Cellulase dosage of 0.7%, enzymolysis time of 60 min, ultrasonic power of 704 W, and ultrasonic time of 47 min. Under these conditions, the TFZB extraction rate was up to 1.92%, which was significantly higher than those of other methods. The Scanning Electron Microscope (SEM) observation verified that the cytoskeletons of bracts had been severely damaged, resulting in a large release of TFZB. The infrared spectrum confirmed that TFZB has the typical characteristics that belong to natural flavonoids. Moreover, the TFZB extracted with optimized UAEE exerts significant antibacterial activities against Escherichia coli and Staphylococcus aureus with Minimal Inhibitory Concentrations (MIC) of 2.5 and 1.25 mg/mL, respectively. Finally, the TFZB solutions were sprayed onto the surface of fresh pork, and the indexes of the sensory score, pH, Total Volatile Basic Nitrogen (TVB-N), Metmyoglobin (MetMb)%, and total count of bacterial colonies during the storage period of chilled pork were measured. The results indicated that TFZB at 1.0 mg/mL can significantly improve the sensory quality of chilled pork via inhibiting microbes, and better preserve the freshness of pork when compared with sodium benzoate at 5.0 mg/mL. The present investigation implied that the TFZB extracted with optimized UAEE can be used as a natural flavonoid alternative resource to produce environmental disinfection products and novel preserving agents for chilled pork preservation.
A Cantilever-Based Piezoelectric MEMS for Arbitrary XY Path Generation

This work pertains to the design of a cantilever-based piezoelectric MEMS device that is capable of generating arbitrary paths of its tip. The conceived device consists of a pair of rigidly coupled piezoelectric bimorph cantilevers, and a theoretical model is developed for the analytical evaluation of the proper voltage distribution to be supplied to the inner and outer electrodes of each piezoelectric actuator, in order to drive the tip along any desired trajectory. Such a device could be appealing in some microsurgical operations, i.e., the unclogging of arteries, endoluminal treatment of obstructive lesions, but also as a 2D micropositioning stage, etc. Theoretical predictions of voltage versus time that allow several pathways such as circles, ellipses, spirals, etc., to be accomplished have been verified with multiphysics FEM simulations and the numerical outcomes seem to corroborate the proposed model.
IMPACT OF CLIMATE CHANGE ON OCCUPATIONAL HEALTH AND ITS POSSIBLE PREVENTIVE STRATEGIES (REVIEW ARTICLE)

Introduction: Climate change and other types of environmental alteration are of our generation’s most pressing issues. Due to its geographical location and reliance on climate-sensitive economic sectors, Egypt is particularly vulnerable to climate change. Occupational exposure as a result of rising temperatures and climate change has become a threat to the health and safety, productivity, and social well-being of the world’s diverse workforce. Both outdoor and indoor employees are expected to be affected by climate change. Heatstroke, headache, exhaustion, insomnia, heart, kidney, respiratory, and skin disorders, immunological dysfunction, infections, injuries, cancer, and (in severe situations) mortality are among the most common occupational health concerns. High temperature, ozone, polycyclic aromatic hydrocarbons, and other chemicals are among the occupational exposures that are predicted to rise due to climate change. Climate change has also been linked to an increase in the spread of pathogenic microbes, vector-borne infectious agents, and wildfires, as well as increased workplace violence. Aim of Work: To discuss the different types of occupational exposure that are anticipated to cause climate change, to highlight the regions that would be the most vulnerable to their consequences, and to draw attention to the different preventive measures which are needed to safeguard employees from the health risks of climate change. Conclusion: Climate change could raise the risk of work-related diseases and injuries, necessitating steps to enhance the detection and prevention of its impact on occupational health. Employers, governments, and politicians must implement a variety of methods to safeguard employees against the long-term health effects of climate change. Workers should also be informed of any actions that may be taken to mitigate the health effects of climate change.
Fractal methods in image analysis and coding

In this thesis we present an overview of image processing techniques which use fractal methods in some way. We show how these fields relate to each other, and examine various aspects of fractal methods in each area. The three principal fields of image processing and analysis th a t we examine are texture classification, image segmentation and image coding. In the area of texture classification, we examine fractal dimension estimators, comparing these methods to other methods in use, and to each other. We attempt to explain why differences arise between various estimators of the same quantity. We also examine texture generation methods which use fractal dimension to generate textures of varying complexity. We examine how fractal dimension can contribute to image segmentation methods. We also present an in-depth analysis of a novel segmentation scheme based on fractal coding. Finally, we present an overview of fractal and wavelet image coding, and the links between the two. We examine a possible scheme involving both fractal and wavelet methods.
OsABT Is Involved in Abscisic Acid Signaling Pathway and Salt Tolerance of Roots at the Rice Seedling Stage

Rice is a staple cereal crop worldwide, and increasing its yields is vital to ensuring global food security. Salinity is a major factor that affects rice yield. Therefore, it is necessary to investigate salt tolerance mechanisms in rice. Proteins containing WD40 repeats play important roles in eukaryotic development and environmental adaptation. Here, we showed that overexpression of OsABT, a gene encoding a WD40-repeat protein, enhanced salt tolerance in rice seedlings by regulating root activity, relative conductivity, malondialdehyde and H2O2 content, and O2•− production rate. Root ion concentrations indicated that OsABT overexpression lines could maintain lower Na+ and higher K+/Na+ ratios and upregulated expression of salt-related genes OsSOS1 and OsHAK5 compared with the wild-type (WT) Nipponbare plants. Furthermore, Overexpression of OsABT decreased the abscisic acid (ABA) content, while downregulating the ABA synthesis genes OsNCED3 and OsNCED4 and upregulating the ABA catabolic gene OsABA8ox2. The yeast two-hybrid and bimolecular fluorescence complementation analyses showed that OsABT interacted with the ABA receptor proteins OsPYL4, OsPYL10, and PP2C phosphatase OsABIL2. A transcriptome analysis revealed that the differentially expressed genes between OsABT overexpression lines and WT plants were enriched in plant hormone signal transduction, including ABA signaling pathway under salt stress. Thus, OsABT can improve the salt tolerance in rice seedling roots by inhibiting reactive oxygen species accumulation, thereby regulating the intracellular Na+/K+ balance, ABA content, and ABA signaling pathway.
AANet: an attention-based alignment semantic segmentation network for high spatial resolution remote sensing images

ABSTRACT In this paper, we present an efficient network to tackle three critical problems in high spatial resolution (HSR) remote sensing image segmentation: feature misalignment, insufficient contextual information extraction and various class imbalance issues. In detail, we propose a novel Feature Alignment Block (FAB) to suppress misalignment issues with the guide of an anchor map. Further, to extract sufficient information, we design a Contextual Augmentation Block (CAB) to augment features of different semantic levels. Finally, we present an Annealing Online Hard Example Mining (AOHEM) strategy to handle the various class imbalance issues with a view to dynamically adjust the focus of the network. We apply the above proposed designs to FPN to form our Attention-based Alignment Network (AANet). Experimental results demonstrate that the proposed method achieves promising results on the challenging iSAID and Vaihingen datasets with a better trade-off between accuracy and complexity.
Overview of Patients with Metastatic Brain Tumors from Breast Cancer at H. Adam Malik Hospital, Medan in 2017-2021

Abstract Introduction: The incidence of breast cancer based on Globocan in 2018, reached 2,088,849 cases (11.6%), with a mortality rate of 626,679 cases (6.6%). Breast cancer is one of the most common causes of a metastatic brain tumor. Approximately 10%-16% of patients with breast cancer develop brain metastases during the course of their disease. Current case management guidelines for patients with metastatic brain tumors from breast cancer are radiotherapy to the entire brain, with or without surgical resection, or stereotactic radiosurgery. Hormone receptor ([HR]; estrogen receptor [ER], progesterone receptor [PR]) and HER2 expression serve as predictors of response to hormone-targeted therapy and HER2, respectively. Method: The study was a descriptive study with a retrospective cohort design in which the researchers identified 78 patients with breast cancer brain metastases (either for diagnostic purposes or for therapeutic purposes at RSUP HAM Medan between 2017 and 2021. Data were collected from SIRS RSUP HAM Medan. Data related to clinicopathology were collected from medical records, including demographic characteristics, tumor characteristics, biomarker status, recurrence of metastatic brain tumors based on Magnetic Resonance Imaging (MRI) examination, and data on therapeutic regimens in cases of brain metastases of breast cancer. ER and PR status were determined by immunohistochemical examination. the intensity of the HER2 3+ immunohistochemical staining was considered positive Result: The mean age at breast cancer diagnosis was 46 years (range: 24-73 years). Most patients had invasive ductal histology (n=73, 94%). In addition, 56% of patients had T3 (n=34) T4 disease in 56% of patients (n=44) and 68% of patients (n=53) had positive axillary lymph nodes. Among patients with known HR and HER2 status, a total of 56% of tumors were ER negative (ER-; n=44), 62% were PR negative (n=48), and 44% were HER2-positive (HER2+; n= 34). With regard to the four subtypes formed by the combined values of HR and HER2 status, 21% (n=16) of tumors were HR+HER2+, 27% (n=21) were HR+HER2-, 23% (n=18) were HR+/ HER2-, and 28% (n=23) were triple negative (TN). Discussion: In the current study, investigators found that apart from patient age and number of brain metastases, HER2 status was a strong predictor of survival outcome after brain metastases. Patients with HER2-positive characteristics had a longer life expectancy than patients with HER2-negative disease. Considering the intracranial antitumor effect of anti-HER2 therapy, it is important to establish HER2 status not only in primary tumors but also in brain metastases to aid in consideration of the choice of therapeutic modality Conclusion: This study showed that younger age, brain metastases from solitary breast cancer, and HER2 positive from breast tumors were independent predictors of better survival in patients with breast cancer brain metastases
Stable Isotopes and Bayesian Tracer Mixing Model Reveal Chemical Weathering and CO2 Release in the Jiulongjiang River Basin, Southeast China

Links between erosion, chemical weathering, and atmospheric CO2 can modulate the global climate over geologic times, but the role of chemical weathering on Earth's long‐term carbon cycle is still unclear. Although silicate weathering by carbonic acid could sequester CO2, the pyrite oxidation coupled to carbonate dissolution could provide a transient source of CO2 at the same time. Landscapes with low physical erosion rate cover the majority of exposed land area, however, the concomitant weathering of silicate, carbonate, and sulfide occurring in the low erosion rate terrains is not well understood. Here, we investigate these questions by examining the river water chemistry from a catchment characterized by complex lithology and low erosion rate. Using a Bayesian tracer mixing model, elemental and isotopic ratios, we quantitatively identify the proportion of cations from silicate and carbonate weathering as well as the acid sources during weathering. We propose that the sulfuric acid from pyrite oxidation boosts both silicate and carbonate weathering, and the coupling between pyrite oxidation and silicate weathering is more pronounced as the pyrite oxidation rates increases. In doing so we determine the effect of weathering on the CO2 balance in our study area, and find that the CO2 release from pyrite oxidation coupled to carbonate dissolution overwhelms the CO2 drawdown from silicate weathering on the time scale between marine carbonate precipitation and sulfate reduction (approximately 106–107 years). Our analysis indicates that the lithology and distribution of minerals play an important role on the chemical weathering in low erosion rate terrains.