Search Results (194)

In high-stakes decision-making environments, predictive models must deliver not only high accuracy but also reliable uncertainty estimations and transparent explanations. This study explores the integration of probability calibration techniques with Conformal Prediction (CP) within a predictive process monitoring (PPM) framework tailored to healthcare analytics. CP is renowned for its distribution-free prediction regions and formal coverage guarantees under minimal assumptions; however, its practical utility critically depends on well-calibrated probability estimates. We compare a range of post-hoc calibration methods—including parametric approaches like Platt scaling and Beta calibration, as well as non-parametric techniques such as Isotonic Regression and Spline calibration—to assess their impact on aligning raw model outputs with observed outcomes. By incorporating these calibrated probabilities into the CP framework, our multilayer analysis evaluates improvements in prediction region validity, including tighter coverage gaps and reduced minority error contributions. Furthermore, we employ SHAP-based explainability to explain how calibration influences feature attribution for both high-confidence and ambiguous predictions. Experimental results on process-driven healthcare data indicate that the integration of calibration with CP not only enhances the statistical robustness of uncertainty estimates but also improves the interpretability of predictions, thereby supporting safer and robust clinical decision-making. Full article

The term ziran first appears in the Daodejing, yet its precise meaning and attribution remain ambiguous in this book, sparking ongoing scholarly debate. This paper argues that Laozi’s idea of ziran fundamentally pertains to all things and the common people, rather than the Dao or the ruler, and its realization depends on the noncoercive action (wuwei, 無為) of the Dao and the ruler. While ziran is commonly understood as “natural” or “free from external force”, Laozi reinterprets it beyond its literal meaning, integrating the notion of order through its relationship with wuwei and thus imbuing it with theoretical significance. In this framework, ziran encompasses orders of internal senses and orders of external activities inherent in all things while simultaneously excluding excessive and disorderly desires. It thereby serves as a criterion for assessing the orderliness of desires. Furthermore, by elucidating ziran as the continuous transformation of things, the standard to which the ideal ruler or the sage resorts to curb the disorderly desires of the common people is established. Full article

Patients with chronic kidney disease (CKD) face an increased risk of early vascular aging, progressive vascular calcification, and premature death. With increasing age, mitochondrial function and mitochondrial DNA copy number (mtDNA-cn) decline. This has been identified as an independent predictor of frailty and mortality in cardiovascular diseases (CVDs) and cancer. However, the relationship between mtDNA-cn and vascular calcification in the context of a uremic milieu remains ambiguous. We hypothesize that a lower mtDNA-cn is associated with medial calcification, as both are linked to impaired vascular health and accelerated aging. mtDNA-cn was analyzed in 211 CKD5 patients undergoing renal transplantation (RTx) and 196 healthy controls using quantitative PCR (qPCR) for three mtDNA genes (mtND1, mtND4, and mtCOX1) and single-locus nuclear gene hemoglobin beta (HbB). In 32 patients, mtDNA-cn was also quantified one year after RTx. The association between mtDNA-cn and vascular calcification scores, circulatory cell-free (ccf) mtDNA in plasma, and the surrogate marker of biological aging (skin autofluorescence) and CVD risk was assessed. mtDNA-cn was significantly lower in CKD5 patients than in controls and correlated with biological age, vascular calcification, and CVD risk. One year after RTx there was a significant recovery of mtDNA-cn in male patients compared to baseline levels. mtDNA-cn and ccf-mtDNA were inversely correlated. This prospective study provides novel insights into the link between low mtDNA-cn and vascular aging. It demonstrates that RTx restores mtDNA levels and may improve oxidative phosphorylation capacity in CKD. Further investigation is warranted to evaluate mtDNA as a biologically relevant biomarker and a potential therapeutic target for early vascular aging in the uremic environment. Full article

Facial semantic segmentation, as a critical technology in high-level visual understanding, plays an important role in applications such as facial editing, augmented reality, and identity recognition. However, due to the complexity of facial structures, ambiguous boundaries, and inconsistent scales of facial components, traditional methods still suffer from significant limitations in detail preservation and contextual modeling. To address these challenges, this paper proposes a facial parsing network based on the Deeplabv3+ framework, named FP-Deeplab, which aims to improve segmentation performance and generalization capability through structurally enhanced modules. Specifically, two key modules are designed: (1) the Context-Channel Refine Feature Enhancement (CCR-FE) module, which integrates multi-scale contextual strip convolutions and Cross-Axis Attention and introduces a channel attention mechanism to strengthen the modeling of long-range spatial dependencies and enhances the perception and representation of boundary regions; (2) the Self-Modulation Attention Feature Integration with Regularization (SimFA) module, which combines local detail modeling and a parameter-free channel attention modulation mechanism to achieve fine-grained reconstruction and enhancement of semantic features, effectively mitigating boundary blur and information loss during the upsampling stage. The experimental results on two public facial segmentation datasets, CelebAMask-HQ and HELEN, demonstrate that FP-Deeplab improves the baseline model by 3.8% in Mean IoU and 2.3% in the overall F1-score on the HELEN dataset, and it achieves a Mean F1-score of 84.8% on the CelebAMask-HQ dataset. Furthermore, the proposed method shows superior accuracy and robustness in multiple key component categories, especially in long-tailed regions, validating its effectiveness. Full article

The rail transit switch machine ensures the safe turning and operation of trains on the track by switching switch positions, locking switch rails, and reflecting switch status in real time. However, in the detection of complex rail transit switch machine parts such as augmented reality and automatic inspection, existing algorithms have problems such as insufficient feature extraction, large computational complexity, and high demand for hardware resources. This article proposes a complex scene rail transit switch machine parts detection network YOLO-SMPDNet (YOLO-based Switch Machine Parts Detecting Network). The YOLOv8s backbone network is improved, and the number of network parameters are reduced by introducing MobileNetV3. Then a parameter-free attention-enhanced ResAM module is designed, which forms a lightweight detection network with the improved network, improving detection efficiency. Finally, Focal IoU Loss is introduced to more accurately define the scale information of the prediction box, alleviate the problem of imbalanced positive and negative samples, and improve the relative ambiguity of CIoU Loss in YOLOv8s on the definition of aspect ratio. By validating the performance of YOLO-SMPDNet on a self-made dataset of rail transit switch machines, the results show that YOLO-SMPDNet can significantly improve detection accuracy and real-time performance and has robust comprehensive detection capabilities for rail transit switch machine parts and good practical application performance. Full article

The construction industry faces persistent challenges from disputes and claims, leading to delays, cost overruns, and strained stakeholder relationships. This study proposes a strategic framework that integrates building information modeling (BIM) as a proactive tool for dispute avoidance. Using a causal loop diagram (CLD), the research maps the relationships among systemic factors contributing to disputes, such as poor communication, ambiguous specifications, and ineffective stakeholder engagement. The study highlights BIM’s transformative potential in enhancing visualization, improving collaboration, and fostering proactive conflict resolution. Validated through expert insights, the framework provides actionable recommendations for integrating BIM (with ISO19650 specs) into construction workflows, addressing the root causes of disputes, and driving project efficiency. This research contributes a structured roadmap for advancing construction management practices, emphasizing early BIM adoption considered with ISO19650, stakeholder alignment, and balancing systemic dynamics. The findings underscore BIM’s pivotal role in reshaping conflict prevention strategies, paving the way for sustainable and dispute-free project delivery. Full article

Despite the widespread adoption of indoor positioning technology, the existing solutions still face significant challenges. On one hand, Wi-Fi-based positioning struggles to balance accuracy and efficiency in complex indoor environments and architectural layouts formed by pre-existing access points (APs). On the other hand, vision-based methods, while offering high-precision potential, are hindered by prohibitive costs associated with binocular camera systems required for depth image acquisition, limiting their large-scale deployment. Additionally, channel state information (CSI), containing multi-subcarrier data, maintains amplitude symmetry in ideal free-space conditions but becomes susceptible to periodic positioning errors in real environments due to multipath interference. Meanwhile, image-based positioning often suffers from spatial ambiguity in texture-repeated areas. To address these challenges, we propose a novel hybrid indoor positioning method that integrates multi-granularity and multi-modal features. By fusing CSI data with visual information, the system leverages spatial consistency constraints from images to mitigate CSI error fluctuations while utilizing CSI’s global stability to correct local ambiguities in image-based positioning. In the initial coarse-grained positioning phase, a neural network model is trained using image data to roughly localize indoor scenes. This model adeptly captures the geometric relationships within images, providing a foundation for more precise localization in subsequent stages. In the fine-grained positioning stage, CSI features from Wi-Fi signals and Scale-Invariant Feature Transform (SIFT) features from image data are fused, creating a rich feature fusion fingerprint library that enables high-precision positioning. The experimental results show that our proposed method synergistically combines the strengths of Wi-Fi fingerprints and visual positioning, resulting in a substantial enhancement in positioning accuracy. Specifically, our approach achieves an accuracy of 0.4 m for 45% of positioning points and 0.8 m for 67% of points. Overall, this approach charts a promising path forward for advancing indoor positioning technology. Full article

In this paper, we clarify a serious misinterpretation and consequent misuse of the Principle of Maximum Conformality (PMC), which also can serve as a mini-review of PMC. In a recently published article, P. M. Stevenson has claimed that “the PMC is ineffective and does nothing to resolve the renormalization-scheme-dependence problem”, concluding incorrectly that the success of PMC predictions is due to the PMC being a “laborious, ad hoc, and back-door” version of the Principle of Minimal Sensitivity (PMS). We show that such conclusions are incorrect, deriving from a misinterpretation of the PMC and an overestimation of the applicability of the PMS. The purpose of the PMC is to achieve precise fixed-order pQCD predictions, free from conventional renormalization schemes and scale ambiguities. We demonstrate that the PMC predictions satisfy all the self-consistency conditions of the renormalization group and standard renormalization-group invariance; the PMC predictions are thus independent of any initial choice of renormalization scheme and scale. The scheme independence of the PMC is also ensured by commensurate scale relations, which relate different observables to each other. Moreover, in the Abelian limit, the PMC dovetails into the well-known Gell-Mann–Low framework, a method universally revered for its precision in QED calculations. Due to the elimination of factorially divergent renormalon terms, the PMC series not only attains a convergence behavior far superior to that of its conventional counterparts but also deftly curtails any residual scale dependence caused by the unknown higher-order terms. This refined convergence, coupled with its robust suppression of residual uncertainties, furnishes a sound and reliable foundation for estimating the contributions from unknown higher-order terms. Anchored in the bedrock of standard renormalization-group invariance, the PMC simultaneously eradicates the factorial divergences and eliminates superfluous systematic errors, which inversely provides a good foundation for achieving high-precision pQCD predictions. Consequently, owing to its rigorous theoretical underpinnings, the PMC is eminently applicable to virtually all high-energy hadronic processes. Full article

Background/Objectives: Congenital adrenal hyperplasia (CAH) is an autosomal recessive disorder caused by mutations in the CYP21A2 gene associated with 21-hydroxylase deficiency and increased levels of adrenal androgens. Affected females are at risk of ambiguous genitalia, while affected males show sexual precocity. Here, we present a case of a newborn female patient, characterized by ambiguous genitalia and previously identified as low risk for common aneuploidies by non-invasive prenatal testing (NIPT). Methods: We performed a NIPT, which showed a 46, XX genotype, confirmed by karyotype on the newborn’s DNA extracted lymphocytes. For clinical suspicion of CAH, we performed reverse dot blot and Multiple Ligation-dependent Probe Amplification (MLPA) of the CYP21A2 gene on the patients and her parents’ DNA. Then, we performed on mother’s plasma NGS analysis with an in-house developed panel of genes for monogenic diseases, including the CYP21A2 gene. Results: Reverse dot blot and MLPA detected the presence of the c.290-13A/C>G (I2 splice) mutation in heterozygosity in the parents and in homozygosity in the child, respectively. NGS detected the c.290-13A/C>G (I2splice) mutation in cell-free fetal DNA (cfDNA) in mother’s plasma with a variant allele frequency (VAF) of 67% with a fetal fraction (FF) of 5%. This latter suggests the presence of the variant both in the mother and in newborn cfDNA. Conclusions: The study reinforces the hypothesis that cfDNA can be used to identify point mutations, small insertions and/or deletions for the diagnosis of monogenic diseases, reducing the number of invasive tests and the risk of early miscarriages. Early detection of mutations in genes causing sexual development disorders could make it possible to start therapy in the womb. Full article

Background/Objectives: The archaeobotanical taxon “Triticum parvicoccum” was first described in 1980 as a small-grained, naked, free-threshing, and dense ear tetraploid wheat species (2n = 4x = 28) identified from archaeological remains. This primitive tetraploid, cultivated in the Levant approximately 9000 years ago and subsequently dispersed throughout the Fertile Crescent, represents a potential contributor of the BBAA genomes to T. aestivum. This study aims to resolve the complex nomenclatural status of this taxon, which has remained ambiguous due to competing interpretations under fossil and non-fossil taxonomic regulations. Methods: We conducted a comprehensive nomenclatural review to evaluate the taxonomic validity of T. parvicoccum, analyzing previous research on the classification of archaeobotanical materials in relation to fossil status. Results: Our analysis demonstrated that archaeobotanical materials do not qualify as fossils and led to the validation of the taxon at a subspecific rank as a non-fossil entity: T. turgidum subsp. parvicoccum Kislev. subsp. nov. The holotype was established using a charred rachis fragment from Timnah (Tel Batash), an archaeological site on the inner Coastal Plain (Shfela) adjacent to the western piedmont of the Judean Mountains, Israel. Conclusions: This study resolves the longstanding nomenclatural uncertainty surrounding this archaeologically significant wheat taxon, providing a valid taxonomic designation that reflects its biological and historical importance while adhering to current botanical nomenclature standards. Full article

Internet of Things (IoT) technology has continuously advanced over the past decade. As a result, device-free indoor localization functions have become a crucial part of application areas such as healthcare, safety, and energy management. Passive infrared (PIR) sensors detecting changes in temperature in an environment are one of the suitable options for human localization due to their lower cost, low energy consumption, electromagnetic tolerance, and enhanced private awareness. Although existing localization methods, including machine/deep learning, have been proposed to detect multiple persons based on signal phase and amplitude, they still face challenges regarding signal quality, ambiguity, and interference caused by the complex, interleaving movements of multiple persons. This paper proposes a novel deep learning method for multi-person localization using channel separation and template-matching techniques. The approach is based on a deep CNN-LSTM architecture with ensemble models using a mean bagging technique for achieving higher localization accuracy. Our results show that the proposed method can estimate the locations of two participants simultaneously with a mean distance error of 0.55 m, and 80% of the distance errors are within 0.8 m. Full article

Application of rare earths (RE) as grain refiners is well-known in the technology of aluminum alloys for the automotive industry. In the current study, Al-2.4%Cu-0.4%Mg alloy (coded 220) and Al-7.5%Si-0.35%Mg alloy (coded 356.1), were prepared by melting each alloy in a resistance furnace. Strontium (Sr) was used as a modifier, while titanium boride (TiB₂) was added as a grain refiner. Measured amounts of Ce and La were added to both alloys (max. 1 wt.%). The alloy melts were poured in a preheated metallic mold. The main part of the study was conducted on tensile testing at room temperature. The results show that although RE would cause grain refining to be about 30–40% through the constitutional undercooling mechanism, grain refining with TiB₂ would lead to approximately 90% refining (heterogenous nucleation mechanism). The addition of high purity Ce or La (99.9% purity) has no modification effect regardless of the alloy composition or the concentration of RE. Depending on the alloy ductility, the addition of 0.2 wt.%RE has a hardening effect that causes precipitation of RE in the form of dispersoids (300–700 nm). However, this increase vanishes with the decrease in alloy ductility, i.e., with T6 treatment, due to intensive precipitation of ultra-fine coherent Mg₂Si-phase particles. There is no definite distinction in the behavior of Ce or La in terms of their high affinity to interact with other transition elements in the matrix, particularly Ti, Fe, Cu, and Sr. When the melt was properly degassed using high-purity argon and filtered using a 20 ppi ceramic foam filter, prior to pouring the liquid metal into the mold sprue, no measurable number of RE oxides was observed. In conclusion, the application of RE to aluminum castings would only lead to formation of a significant volume fraction of brittle intermetallics. In Ti-free alloys, identification of Ce- or La-intermetallics is doubtful due to the fairly thin thickness of the precipitated platelets (about 1 µm) and the possibility that most of the reported Al, Si, and other elements make the reported values for RE rather ambiguous. Full article

Quantum mechanics (QM) has long challenged our understanding of time, space, and reality, with phenomena such as superposition, wave–particle duality, and quantum entanglement defying classical notions of causality and locality. Despite the predictive success of QM, its interpretations—such as the Copenhagen and many-worlds interpretations—remain contentious and incomplete. This paper introduces Strip Theory, a novel framework that reconceptualises time as a two-dimensional manifold comprising foretime, the sequential dimension, and sidetime, an orthogonal possibility dimension representing parallel quantum outcomes. By incorporating sidetime, the theory provides a unified explanation for quantum superposition, coherence, and interference, resolving ambiguities associated with wavefunction collapse. The methods involve extending the mathematical formalism of QM into a five-dimensional framework, where sidetime is explicitly encoded alongside spatial and sequential temporal dimensions. The principal findings demonstrate that this model reproduces all measurable results of QM while addressing foundational issues, offering a clearer and more deterministic interpretation of quantum phenomena. Furthermore, the framework provides insights into quantum coherence, wave–particle duality, and the philosophical implications of free will. These results suggest that Strip Theory can serve as a bridge between interpretations and provide a deeper understanding of time and reality, advancing both theoretical and conceptual horizons. Full article

Origen’s theology is fundamentally rooted in the question of whether he upheld the pre-existence of the soul or focused more on the soul’s superiority over the body and its perfection. While inheriting many ideas from Plato, Origen adapted them in accordance with Christian doctrine. Both Origen and Plato emphasized that the soul governs the body and is superior to it in both status and importance. The image of God resides in human soul, not the body, guiding individuals toward the perfection of the soul and the attainment of the whole virtues. Origen’s tripartite distinction of spirit, soul, and body is intrinsically connected to Plato’s tripartite theory of the soul, with the intermediary of the incarnate soul corresponding to the ambiguous role of thumos (spiritedness) in Plato’s dialogue. This suggests that humans are capable of both good and evil, a potential grounded in free will rather than the sin of the body. Nevertheless, Origen assigned the body a more important role, asserting that the Incarnation not only depended on the body but also facilitated the practice of virtue, positioning the body as central to his theory of resurrection. Origen also adopted Plato’s epistemology, teleology of knowledge, and theory of participation. He emphasized that the perfection of the soul requires liberation from the dominance of the senses, using Plato’s dialectical method and drawing inspiration from the Holy Spirit to achieve comprehensive knowledge and spiritual maturity. Origen should not be viewed as merely a Platonist or an anti-Platonist. Both he and Plato shared concerns about the correct way of life and perfect knowledge, and both sought to bridge the gap between the majority and the minority, avoiding both elitism and populism. Full article

With the advancement of multi-frequency and multi-constellation GNSS signals and the introduction of observable-specific bias (OSB) products, the uncombined precise point positioning (PPP) model has grown more prevalent. However, this model faces challenges due to the large number of estimated parameters, resulting in strong correlations between state parameters, such as clock errors, ionospheric delays, and hardware biases. This can slow down the convergence time and impede ambiguity resolution. We propose two methods to improve the triple-frequency uncombined PPP-AR model by integrating ambiguity constraints. The first approach makes use of the resolved ambiguities from dual-frequency ionosphere-free combined PPP-AR processing and incorporates them as constraints into triple-frequency uncombined PPP-AR processing. While this approach requires the implementation of two filters, increasing computational demands and thereby limiting its feasibility for real-time applications, it effectively reduces parameter correlations and facilitates ambiguity resolution in post-processing. The second approach incorporates fixed extra-wide-lane (EWL) and wide-lane (WL) ambiguities directly, allowing for rapid convergence, and is well suited for real-time processing. Results show that, compared to the uncombined PPP-AR model, integrating N1 and N2 constraints reduces averaged convergence time from 8.2 to 6.4 min horizontally and 13.9 to 10.7 min vertically in the float solution. On the other hand, integrating EWL and WL ambiguity constraints reduces the horizontal convergence to 5.9 min in the float solution and to 4.6 min for horizontal and 9.7 min for vertical convergence in the fixed solution. Both methods significantly enhance the ambiguity resolution in the uncombined triple-frequency PPP model, increasing the validated fixing rate from approximately 80% to 89%. Full article