Independent Properties Research Articles

SolarDesign: An online photovoltaic device simulation and design platform

Abstract SolarDesign (https://solardesign.cn/) is an online photovoltaic device simulation and design platform that provides engineering modeling analysis for crystalline silicon solar cells, as well as emerging high-efficiency solar cells such as organic, perovskite, and tandem cells. The platform offers user-updatable libraries of basic photovoltaic materials and devices, device-level multi-physics simulations involving optical-electrical-thermal interactions, and circuit-level compact model simulations based on detailed balance theory. Employing internationally advanced numerical methods, the platform accurately, rapidly, and efficiently solves optical absorption, electrical transport, and compact circuit models. It achieves multi-level photovoltaic simulation technology from “materials to devices to circuits” with fully independent intellectual property rights. Compared to commercial software, the platform achieves high accuracy and improves speed by more than an order of magnitude. Additionally, it can simulate unique electrical transport processes in emerging solar cells, such as quantum tunneling, exciton dissociation, and ion migration.

Enhancing preoperative diagnosis of pancreatic ductal adenocarcinoma and mass-forming chronic pancreatitis: a study on normalized conventional MR imaging parameters.

To assess the utility of signal intensity ratio (SIR) in distinguishing between mass-forming chronic pancreatitis (MFCP) and pancreatic ductal adenocarcinoma (PDAC), thereby reducing unnecessary pancreatectomies or delayed diagnosis brought by misdiagnosis. This retrospective study included 170 participants (34 with MFCP and 136 with PDAC) who underwent radical pancreatic surgery and were diagnosed via specimen pathology. The study group was carefully selected with a 1:4 ratio matching for sex, age, and operation time between two entities. T1 SIR, T2 SIR, arterial phase (AP) SIR, portal venous phase (VP) SIR, delay phase (DP) SIR, DWI0-50 SIR, and DWI500-1000 SIR, were calculated by dividing the signal intensity of lesions by that of the paraspinal muscle, serving as a reference organ. Intraclass Correlation Coefficient (ICC) was estimated to evaluate the intraobserver and interobserver reliability. Wilcoxon tests were employed for univariate analysis, and receiver operating characteristic (ROC) curves were generated to determine optimal cutoff points and AUC values for selected predictors. A tenfold cross-validation method was applied to validate the robustness of the results. The ICC demonstrated excellent correlation for both intraobserver and interobserver(ICCs > 0.8). T1 SIR, AP SIR, VP SIR, and DP SIR were significantly lower in the PDAC group compared to the MFCP group, and exhibited good independent predictive properties with the sensitivities of 61.8, 61.8, 70.6, and 73.5%, specificities of 66.2, 68.4, 59.6, and 55.9%, and AUCs of 0.620, 0.659, 0.670, and 0.668, respectively, hovering around 0.7. The tenfold cross-validation confirmed the reliability and robustness of our findings, with consistent AUC, sensitivity, specificity, and 95% confidence intervals over 1000 iterations. T1 SIR, AP SIR, VP SIR, and DP SIR show promise as potential imaging biomarkers for distinguishing between MFCP and PDAC.

Examining the local Universe isotropy with galaxy cluster velocity dispersion scaling relations

In standard cosmology, the Universe is assumed to be statistically homogeneous and isotropic. This assumption suggests that the expansion rate of the Universe, as measured by the Hubble parameter, should be the same in all directions. However, our recent study based on galaxy clusters finds an apparent angular variation of approximately $9<!PCT!>$ in the Hubble constant, $H_0$, across the sky. In the study, the authors utilised galaxy cluster scaling relations between various cosmology-dependent cluster properties and a cosmology-independent property, i.e. the temperature of the intracluster gas ($T$). A position-dependent systematic bias of $T$ measurements can, in principle, result in an overestimation of apparent $H_0$ variations. Therefore, it is crucial to confirm or exclude this possibility. In this work, we search for directional $T$ measurement biases by examining the relationship between the member galaxy velocity dispersion and gas temperature ($ v -T$) of galaxy clusters. Both measurements are independent of any cosmological assumptions and do not suffer from the same potential systematic biases. Additionally, we search for apparent $H_0$ angular variations independently of $T$ by analysing the relations between the X-ray luminosity and Sunyaev-Zeldovich signal with the velocity dispersion, $L_ X v $ and $Y_ SZ v To study the angular variation of scaling relation parameters, we determined the latter for different sky patches across the extra-galactic sky. We constrained the possible directional $T$ bias using the $ v -T$ relation, as well as the apparent $H_0$ variations using the $L_ X v $ and $Y_ SZ v $ relations. We utilised Monte Carlo simulations of isotropic cluster samples to quantify the statistical significance of any observed anisotropies. We calculated and rigorously took into account a correlation of $L_ X $ and $Y_ SZ $ residuals. No significant directional $T$ measurement biases are found from the $ v -T$ anisotropy study. The probability that the previously observed $H_0$ anisotropy is caused by a directional $T$ bias is only $0.002<!PCT!>$. On the other hand, from the joint analysis of the $L_ X v $ and $Y_ SZ v $ relations, the maximum variation of $H_0$ is found in the direction of $(295^ with a statistical significance of $3.64 fully consistent with our previous results. Our findings, based on the analysis of new scaling relations utilising a completely independent cluster property, $ v $, strongly corroborate the previously detected anisotropy of galaxy cluster scaling relations. The underlying cause, for example, $H_0$ angular variation or large-scale bulk flows of matter, remains to be identified.

Utidelone plus pembrolizumab as the fourth-line combination treatment in non-small cell lung cancer with EGFR mutation: a case report.

Utidelone is an ebomycin derivative chemotherapeutic drug, which can promote tubulin polymerization and stabilize microtubule structure, so as to induce apoptosis. The drug is an innovative drug independently developed by China with independent intellectual property rights. Phase II clinical trials for advanced breast cancer are being approved by National Medical Products Administration for the treatment of advanced breast cancer. However, there is no report on the application in non-small cell lung cancer (NSCLC) patients with the epidermal growth factor receptor (EGFR) mutation. This case is a patient with EGFR mutant stage IV NSCLC who has progressed after third-line targeted therapy. The fourth line was treated with utidelone combined with pabolizumab. The patient had progressed after targeted therapy with oxitinib, ametinib, and vometinib. Due to the patient's physical reasons, the traditional platinum drugs were not suitable, so the patient was treated with utidelone combined with pabolizumab. The curative effect was evaluated as SD after two cycles and progesterone receptor after four cycles. At present, it is still in the maintenance of reduction of utidelone combined with pabolizumab, and the tumor continues to shrink. Although peripheral neurotoxicity occurred during treatment, it improved after symptomatic treatment. The treatment of EGFR mutant stage IV NSCLC with utidelone combined with pabolizumab has good effect and mild adverse reactions.

Algorithms and data structures for Cs-smooth RMB-splines of degree 2s + 1

The simple mesh refinement algorithm of Groiss et al. (2023) generates T-meshes admitting Reachable Minimally supported (RM) B-splines that possess the property of local linear independence and form a non-negative partition of unity. The construction was first presented for the bilinear case and has later been extended to Cs-smooth splines of degree p=2s+1. The present paper is devoted to algorithms and data structures for RMB-splines. We prove that the memory consumption of the data structures for representing a T-mesh and the associated RMB-splines is linear with respect to the mesh size, and we describe the details of the underlying refinement algorithm. Moreover, we introduce a novel evaluation algorithm for RMB-spline surfaces, which is based solely on repeated convex combinations of the control points, thereby generalizing de Boor's algorithm for tensor-product splines. Numerical experiments are included to demonstrate the advantageous behavior of the proposed data structures and algorithms with respect to their efficiency. We observe that the total computational time (which includes also error estimation and spline coefficient computation) scales roughly linearly with the number of degrees of freedom for the meshes considered.

Nonlinear Reduced Order Modeling of Heated Structures with Temperature-Dependent Properties

This paper focuses on extending coupled structural–thermal reduced order modeling approaches for the prediction of the nonlinear geometric response of heated structures to efficiently account for temperature-dependent structural and thermal properties. Structurally, a linear dependence of the elasticity tensor and thermal expansion coefficient is assumed consistently with typical material behavior. The resulting structural reduced order model (ROM) equations exhibit polynomials of the temperature generalized coordinates, the coefficients of which are readily identified. A different strategy is proposed for conductance and capacitance properties which typically depend nonlinearly on temperature. It relies on splitting the temperature generalized coordinates into a small set of dominant ones having a nonlinear effect on the ROM conductances and capacitances and a much larger set affecting them linearly. The inclusion of uncertainty in the structural ROM is also addressed extending earlier work limited to temperature independent properties. These strategies are exemplified on a representative hypersonic vehicle panel undergoing a full mission profile and with aero-thermal–structural coupling. The ROM predictions are observed to be very close to the full finite element ones for the mean model. Moreover, an uncertainty analysis demonstrates the strong sensitivity of the response to the structural model in the strongly nonlinear regions of the trajectory.

The Impact of Innovative Activities in the Innovative Pharmaceutical Industry on Corporate Market Value

Innovative drugs refer to drugs with independent intellectual property patents. With the gradual improvement of China's intellectual property status, research on innovative drugs will bring high profits to enterprises. The innovative drug industry has always been in the eyes of investors in today's social conditions. At the same time, as an emerging investment option, what indicators will affect the changes in the market value of innovative drug companies is available for everyone to discuss. In this article, through the collection of Chinese innovation Companies in the pharmaceutical industry conducted linear regression analysis and found that the impact of corporate market value is closely related to innovation activities. At the same time, it was found that patent activities related to innovation activities will have a marginal effect and have a certain negative correlation. This article aims to help companies in the innovative drug industry find ways to increase their market value and help investors see the good news brought about by innovative activities in the stock market.

A novel constraint-based structure learning algorithm using marginal causal prior knowledge

Causal discovery with prior knowledge is important for improving performance. We consider the incorporation of marginal causal relations, which correspond to the presence or absence of directed paths in a causal model. We propose the Marginal Prior Causal Knowledge PC (MPPC) algorithm to incorporate marginal causal relations into a constraint-based structure learning algorithm. We provide the theorems of conditional independence properties by combining observational data and marginal causal relations. We compare the MPPC algorithm with other structure learning methods in both simulation studies and real-world networks. The results indicate that, compare with other constraint-based structure learning methods, MPPC algorithm can incorporate marginal causal relations and is more effective and more efficient.

Topological Crystals: Independence of Spectral Properties with Respect to Reference Systems

Topological Crystals: Independence of Spectral Properties with Respect to Reference Systems

Localization in quantum field theory

We review the issue of localization in quantum field theory and detail the nonrelativistic limit. Three distinct localization schemes are examined: the Newton–Wigner, the algebraic quantum field theory, and the modal scheme. Among these, the algebraic quantum field theory provides a fundamental concept of localization, rooted in its axiomatic formulation. In contrast, the Newton–Wigner scheme draws inspiration from the Born interpretation, applying mainly to the nonrelativistic regime. The modal scheme, relying on the representation of single particles as positive frequency modes of the Klein–Gordon equation, is found to be incompatible with the algebraic quantum field theory localization.This review delves into the distinctive features of each scheme, offering a comparative analysis. A specific focus is placed on the property of independence between state preparations and observable measurements in spacelike separated regions. Notably, the notion of localization in algebraic quantum field theory violates this independence due to the Reeh–Schlieder theorem. Drawing parallels with the quantum teleportation protocol, it is argued that causality remains unviolated. Additionally, we consider the nonrelativistic limit of quantum field theory, revealing the emergence of the Born scheme as the fundamental concept of localization. Consequently, the nonlocality associated with the Reeh–Schlieder theorem is shown to be suppressed under nonrelativistic conditions.

Ethical Dilemmas and Copyright Challenges among Independent Artists in Kenya's Music Industry

This qualitative phenomenological research aims to find out the ethical dilemmas around revenue generation and copyright practices among independent artists in Kenya. The study delves into various aspects, including collective management organisations (CMOs), copyright laws, governmental policies, exploitative practices, and regulatory frameworks, through an extensive analysis of existing literature and qualitative data. It reveals that while Kenya's music industry has experienced substantial growth with the introduction of new music genres and disruptive innovations, it still struggles with systemic barriers that limit the welfare and success of independent artists. Governmental policies and copyright laws revealed gaps in protecting independent artists' intellectual property rights. The study shed light on issues such as corruption, mismanagement, and failure to distribute royalties to artists fairly, with a close examination of CMOs, thus calling for the need for increased transparency and accountability. These issues are linked to numerous challenges, including inadequate industry support, limited access to resources, and unfair compensation. Exploitative practices conducted by industry participants and intermediaries are subjecting independent artists to illegitimate contractual agreements, delayed royalties, and predatory behaviours from industry participants. The presence of weak regulations magnifies these concerns, resulting in the degradation of artists' rights and limited recourse in cases of copyright infringements or contractual disputes. This research, therefore, calls for regulatory reforms and industry-wide interventions to address these structural barriers and to give light on how to promote a more sustainable and equitable music ecosystem in Kenya. The study recommends the strengthening of copyright enforcement mechanisms, improving transparency and accountability within CMOs, and establishing tailored support systems for independent artists.

DSDRec: Next POI recommendation using deep semantic extraction and diffusion model

Semantics play a crucial role in many AI tasks, yet the lack of high-quality textual data in LBSNs hampers deep semantic feature learning. Sparse user check-in records, characterized by significant spatial or temporal intervals (cut points), create challenges in understanding users' real mobile preferences. However, prior studies often rely on shallow semantic signals from independent textual properties and overlook these cut points when modeling spatio-temporal context. This work proposes a recommender model named DSDRec for the next POI recommendation. To alleviate the shortage of high-quality textual data in LBSNs, we take prompt engineering to freely obtain rich semantic texts (a.k.a., prompt sentences) from the discrete trajectory sequences and then use a pre-trained language model to acquire high-quality deep semantic features based on the functional prompt sentences. To mitigate the risk caused by the cut points, we propose an effective method, Spatio-Temporal Area Encoding, to depict the global spatial and temporal relationship of check-ins in trajectory. Besides, to study the potential of diffusion models in the next POI recommendation, we stacked an improved diffusion model to assist the recommender in learning more abstract interaction information. Comprehensive experiments conducted on two real-world datasets validate the competitive performance of DSDRec over previous SOTA approaches.

The syntax of Greek split reciprocals

AbstractWe provide the first detailed description and analysis of the syntax of the understudied Greek split reciprocal reconstruction. As in other languages, the reciprocal appears to be bipartite consisting of a quantificational distributor (‘the one’) and a reciprocator (‘the other’). We show that, in Greek, this bipartiteness runs deep: the two parts are syntactically independent, with the reciprocator having the syntax of a Condition A anaphor, and the distributor behaving as a floating quantifier. Once we turn to how these elements establish relations between themselves and their antecedent, we find that Greek reciprocals resist a movement‐ or Agree‐based analysis, since both elements can occur in positions inaccessible to movement/Agree. Given that the reciprocator can occur in embedded subject position, the Greek data also argue against recent attempts to reduce the binding domain to phases, instead supporting a more traditional definition of the binding domain in terms of the smallest XP containing the anaphor and a subject. Finally, we show that the morphosyntactic properties of the bipartite construction can be connected to independent properties of its two component parts and that these can, in turn, be related to interpretive aspects of reciprocity.

Conditional plausibility entropy of belief functions based on Dempster conditioning

Uncertainty quantification of belief functions is an unsolved issue in belief function theory that is used widely to tackle epistemic uncertainty. This study provides a new definition of conditional entropy of belief functions, called conditional plausibility entropy, in terms of Dempster conditioning and plausibility entropy of mass functions. The proposed conditional plausibility entropy mainly meets two aspects of good properties, one is the semantics of independence property, the other is the compatibility with Shannon's conditional entropy for probability distributions, which are not simultaneously satisfied by existing definitions of conditional entropy of belief functions. The effectiveness of conditional plausibility entropy is validated further through comparison and analysis on the basis of different conditioning methods.

Whole-genome sequencing reveals genomic diversity and selection signatures in Xia’nan cattle

BackgroundThe crossbreeding of specialized beef cattle breeds with Chinese indigenous cattle is a common method of genetic improvement. Xia’nan cattle, a crossbreed of Charolais and Nanyang cattle, is China’s first specialized beef cattle breed with independent intellectual property rights. After more than two decades of selective breeding, Xia’nan cattle exhibit a robust physique, good environmental adaptability, good tolerance to coarse feed, and high meat production rates. This study analyzed the population genetic structure, genetic diversity, and genomic variations of Xia’nan cattle using whole-genome sequencing data from 30 Xia’nan cattle and 178 published cattle genomic data.ResultThe ancestry estimating composition analysis showed that the ancestry proportions for Xia’nan cattle were mainly Charolais with a small amount of Nanyang cattle. Through the genetic diversity studies (nucleotide diversity and linkage disequilibrium decay), we found that the genomic diversity of Xia’nan cattle is higher than that of specialized beef cattle breeds in Europe but lower than that of Chinese native cattle. Then, we used four methods to detect genome candidate regions influencing the excellent traits of Xia’nan cattle. Among the detected results, 42 genes (θπ and CLR) and 131 genes (FST and XP-EHH) were detected by two different detection strategies. In addition, we found a region in BTA8 with strong selection signals. Finally, we conducted functional annotation on the detected genes and found that these genes may influence body development (NR6A1), meat quality traits (MCCC1), growth traits (WSCD1, TMEM68, MFN1, NCKAP5), and immunity (IL11RA, CNTFR, CCL27, SLAMF1, SLAMF7, NAA35, and GOLM1).ConclusionWe elucidated the genomic features and population structure of Xia’nan cattle and detected some selection signals in genomic regions potentially associated with crucial economic traits in Xia’nan cattle. This research provided a basis for further breeding improvements in Xia’nan cattle and served as a reference for genetic enhancements in other crossbreed cattle.

Statistical investigation of interdependence of trabecular microarchitectural parameters from micro-computed tomography

Standard microarchitectural analysis of bone using micro-computed tomography produces a large number of parameters that quantify the structure of the trabecular network. Analyses that perform statistical tests on many parameters are at elevated risk of making Type I errors. However, when multiple testing correction procedures are applied, the risk of Type II errors is elevated if the parameters being tested are strongly correlated. In this article, we argue that four commonly used trabecular microarchitectural parameters (thickness, separation, number, and bone volume fraction) are interdependent and describe only two independent properties of the trabecular network. We first derive theoretical relationships between the parameters based on their geometric definitions. Then, we analyze these relationships with an aggregated in vivo dataset with 2987 images from 1434 participants and a synthetically generated dataset with 144 images using principal component analysis (PCA) and linear regression analysis. With PCA, when trabecular thickness, separation, number, and bone volume fraction are combined, we find that 92 % to 97 % of the total variance in the data is explained by the first two principal components. With linear regressions, we find high coefficients of determination (0.827–0.994) and fitted coefficients within expected ranges. These findings suggest that to maximize statistical power in future studies, only two of trabecular thickness, separation, number and bone volume fraction should be used for statistical testing.

On the state principle of classical thermodynamics

We discuss the state principle of classical thermodynamics, namely that the thermodynamic state of a simple compressible system can be uniquely determined by specifying two independent properties. We show that for certain combinations of properties, one is not guaranteed to arrive at a unique state. This caveat to the state principle is illustrated with three examples, two involving liquid water and a third using real gases. Finally, we show that to guarantee a unique state for a simple compressible system, the required two independent properties must be chosen from the trio consisting of a thermodynamic potential and its two natural variables.

Perspectives on the Intersection of Gender, Customary Laws and Land Rights in India

Abstract For centuries, tribal communities in India have maintained distinct social and cultural identities, often with communal land ownership practices that were inclusive of women. The struggle of tribal women in India for land rights is a poignant manifestation of their fight against intersecting forms of oppression rooted in patriarchy, traditional power structures, and historical marginalisation. Given the existing background, this article discusses the intersection of property rights and gender relations in India, making a case for independent property rights for tribal women. It analyses the role of customary laws of inheritance in a legal pluralistic India and its conflict with positive law. The article also focuses on the role of the Indian judiciary in remedying the systemic discrimination against tribal women in India. It analyses the approach of the Indian courts in maintaining a balance between the autonomy granted to the tribes by the Indian Constitution and ensuring justice to women who are victims of such self-governance.

ON CIVIL LAW ASPECTS OF RECOVERY OF LOSSES FOR NON-PAYMENT OF TAXES BY AN ORGANIZATION FROM ITS CONTROLLING PERSON

The purpose of the study is to the identification the essence of the "civilistic" approach to the compensation of pecuniary damage for non-payment of taxes through the fault of persons controlling the organization, as well as related legal consequences of the latter. Based on the analysis of legal doctrine, law enforcement practice on this issue, as well as the positions of the Constitutional Court of Russia, the conclusion is made about the subsidiary nature of the state's claims to the persons controlling the organization, through whose fault the budget was deprived of tax revenues. As a result of the research the substantive legal features of their consideration are determined. The aforementioned features includes: the possibility of compensation for damage at the expense of the controlling entity only if it has an independent property mass in relation to the main debtor; inadmissibility of deprivation of the subsidiary debtor of the right of recourse against the main debtor; the need for an economic link between the offence committed by the subsidiary debtor and the non-performance of the debtor's tax obligations; the need for the existence of an economic link between the offence committed by the subsidiary debtor and the non-performance of the debtor's tax obligations.

Weak interlayer interactions and nearly temperature independent electrical transport in p-type 1T′-MoTe2/Sb2Te3 superlattice-like films

Thermoelectric superlattices (SLs) are one of the important focuses in the thermoelectric field due to their ordered stacking structure and the potential to obtain extremely high thermoelectric performance. To understand the critical effects of interlayer interactions, this work fabricates p-type (1T′-MoTe2)x(Sb2Te3)y SLs and investigates their electrical properties as functions of SL period and temperature. The results discovered that the weak interlayer interactions could be driven by both the small work function difference and temperature. This brings forth hole donation and energy filtering and leads to increased hole density and the carrier effective mass of (1T′-MoTe2)x(Sb2Te3)y SLs. Strikingly, the SL structure is beneficial for achieving temperature independent electrical properties, owing to the temperature driven interlayer interaction. Several SLs acquire the largest average power factor among all SLs, which is about 1.10 mWm−1K−2 within 300∼473 K, favorable for thermoelectric applications near room temperature. This work points out the beneficial effect of the SL structure on obtaining high thermoelectric properties in a wide temperature range.