Miracle-dz/UniFAR-FTUs huggingface dataset:
Integrated Biomarker Responses of a Brackish Water Clam to Global Warming Conditions

To analyze physiological and biochemical marker responses of brackish water clam Corbicula japonica under global warming conditions, different water temperatures (20°C and 25°C), salinity (5 and 20 psu), and food availability (0.5 and 2.0 mg SS ind −1 d −1 ) levels were tested. Appropriate biomarkers were selected based on the sensitivity of biomarker responses, condition index (CI), energy reserves, superoxide dismutase (SOD), catalase, oxyradical-absorbance capacity, and lipid peroxidation (LPO) ( p < 0.05), and five methods of integrated biomarker response index (IBR) were calculated. CI, SOD, and LPO were employed for IBR I , although four biochemical biomarkers were generally employed for IBR. At high water temperature (HT), all biomarkers were deleteriously affected. HT significantly affected all the IBR methods ( p < 0.05), and the highest correlation was discovered in IBR I (r = 0.92, p < 0.01). The lowest and highest IBRs were observed at natural (control = 1.14) and global warming (HT = 2.43) conditions, respectively. The contribution of LPO scores was higher under HT, demon-strating poor organism health. Based on our estimates, three sensitive biomarkers could detect stress in C. japonica under global warming conditions. We conclude that the IBR method based on sensitive biomarkers should be used to quantify anthropogenic impacts on aquatic organisms, especially C. japonica .
Simulation Based Analysis of Hierarchical Timed Colored Petri Nets Model of the Restaurant Food Serving Process

The major goal of establishing a restaurant is improved earnings making which can be jeopardized by customers' withdrawals due to lengthy ready lines. The above scenario was studied in this paper using simulation-based analysis of a Hierarchical Timed Coloured Petri Nets (HTCPN) model, which abstracted the serving operation of a renowned restaurant in the Ibadan metropolis. The restaurant was characterized by two or more servers that serially served each Customer from the multiple available servers at the four serving points. One hundred simulation runs were carried out on the HTCPN model using CPN Tools to determine the four (4) parameters,Customers' Average Flow Time (CAFT),Customers' Average Waiting Time (CAWT),Servers' Average Utilization Rate (SAUR) andCustomers' Average Queue Length (CAQL) required in serving 567, 1100, 1103, 770 and 829 customers from Monday to Friday, respectively. The model was validated by carrying out a statistical analysis t-Test between the simulated and the actual customers' flow time andservers' utilization rate at a 5% significant level. The validation results showed no significant differences between the simulated and the actual customers' average flow time andservers' utilization rate at a 5% significance level. Hence, the model can represent the restaurant under consideration.
Statistical modeling by stochastic complexity

This thesis is a study of several statistical modeling problems by stochastic complexity. At first, an index of predictive power, using the concept of complexity or minimum description length, is proposed as a criterion to select the principal components of a random vector distributed in a parametric family. Then, we consider the problem of selecting a model with the best predictive ability in a class of generalized linear models. A predictive least quasi-deviance criterion is proposed to measure the predictive ability of a model. Some results concerning the consistency of this criterion are given. The method is also modified for finite sample applications. Thirdly a density estimation based complexity decision rule is proposed, which uses the quality of these estimators to estimate the corresponding unknown element of the true probability density. The resulting complexity density decision procedures shown to be admissible, to achieve the minimum expected risk, and to form a minimal complete class. Fourthly a generalized histogram density estimator with unequal-width subintervals is used to find both optimal and predictive optimal description of a sample. Both optimal descriptions are expressed in terms of the stochastic complexity. Uniform, almost sure asymptotic expressions for both descriptions are given. Finally, as an application of the stochastic complexity for optimal data description, a new test procedure for hypotheses of homogeneity is proposed. Some examples and simulation studies are further given to illustrate this test procedure.
Dendroclimatic analysis and cartographic modeling of the climatic response of Fagus sylvatica during growth in a sector of the central Cantabrian Mountains

The wide distribution of the common beech (Fagus sylvatica) in Europe reveals its great adaptation to diverse conditions of temperature and humidity. This interesting aspect explains the context of the main objective of this work: to carry out a dendroclimatic analysis of the species Fagus sylvatica in the Polaciones valley (Cantabria), an area of transition with environmental conditions from a characteristic Atlantic type to more Mediterranean, at the southern limit of its growth. The methodology developed is based on the analysis of 25 local chronologies of growth rings sampled at different altitudes along the valley, generating a reference chronology for the study area. Subsequently, the patterns of growth and response to climatic variations are estimated through the response and correlation function, and the most significant monthly variables in the annual growth of the species are obtained. Finally, these are introduced into a Geographic Information System (GIS) where they are cartographically modeled in the altitudinal gradient through multivariate analysis, taking into account the different geographic and topographic variables that influence the zonal variability of the species response. The results of the analyses and cartographic models show which variables are most determinant in the annual growth of the species and the distribution of its climatic response according to the variables considered.
Secrecy Rate Maximization for Multicarrier-Based Cognitive Radio Networks With an Energy Harvesting Jammer

Cognitive radio (CR) is becoming an increasingly significant component of Internet-of-Things technologies because it overcomes the challenge of spectrum resource scarcity for wireless communications. For the cooperative CR network (CRN) based on the multicarrier system, this article investigates the physical layer security (PLS) to guarantee information privacy for the secondary network while guaranteeing the quality of service (QoS) of the primary network. First, we propose one communication scheme for this type of CRN. The secondary transmitter (ST) and secondary jammer (SJ) first harvest RF energy from the primary signal transmitted by the primary transmitter (PT). Then, ST transmits confidential information with the spectrum vacated by the primary network to the secondary receiver (SR), and SJ simultaneously generates the jamming signal to interfere with the eavesdropper (ED). Second, for the scenarios with the instantaneous channel state information (CSI) and the statistical CSI of the ED, respectively, we aim to maximize the secrecy rate of the secondary network while guaranteeing the QoS requirement of the primary network by jointly optimizing the time allocation between the two phases and the transmit power allocation for ST and SJ over subcarriers. For each scenario, the secrecy rate maximization is formulated as the nonconvex optimization problem. Finally, we design efficient algorithms for both two nonconvex problems. The optimal time allocation is obtained by the 1-D search method at the outer layer, and the optimal transmit power allocation is obtained by the difference of concave (DC) programming at the inner layer, where the Lagrange duality method is used to solve the convex approximation problem. Simulation results verify that the proposed scheme essentially improves the secrecy rate of the secondary network compared to benchmark schemes.
Sinusoidal liquid crystal display grating in the Ronchi test

The Ronchi test with a LCD amplitude sinusoidal grating is used for testing convergent optical systems. The rulings are computer- generated and displayed on the LCD. By displaying various phase- shifted rulings and capturing the corresponding images, the phase is obtained with the conventional phase-shifting algorithms. For reference, experimental results are compared with those on a commercial Fizeau interferometer. © 2003 Society of Photo-Optical Instrumentation Engineers.
Genetic Predisposition of TNF-α (-308), TGF-β-1 
(-508) and IL-35(EBI3) Gene Polymorphisms towards Rheumatic Heart Disease in the Population of Telangana from South India

Background: Rheumatic Heart Disease (RHD) is a complex disease, subject to genetic and environmental factors. Cytokines play an important role in development and pathogenesis of the rheumatic heart disease. TNF-α, TGF-β and IL-35 gene polymorphisms may affect the expression levels of cytokines which may lead to damage to the heart valves. Objective: This study was intended to explore the association of TNF-α, TGF-β and IL-35 gene polymorphisms with RHD. Materials and Methods: The present case control study consisted of 145 patients with rheumatic heart disease and 217 control subjects in the same age group. Genotyping was done for the TNF-α (-308), TGF-β-1 (-508) and IL-35(EBI3) gene polymorphisms in both case and control groups. Results: The results showed Bone differences in the distribution of genotypes in TNF-α, TGF-β and IL-35 genes RHD cases and control groups. However, the statistical analysis of the data showed the differences in the genotypes between TNF alpha (-308 G>A), TGF-β-1 (C-508T) and IL-35 EBI3G/C genes RHD case and control subjects were not found to be statistically significant. Conclusion: In conclusion our study could not find any significant association between TNF-α (-308), TGF-β-1 (-508) and IL-35(EBI3) gene polymorphisms and RHD. Key words: Rheumatic Heart Disease, Cytokines, Tumour Necrosis Factor alpha, Transforming growth factor beta 1, Interleukin, Single Nucleotide Polymorphism.
Involutory automorphisms of groups of odd order

Let G be a finite group of odd order with an automorphism ω of order 2. The Feit-Thompson theorem implies that G is soluble and this is assumed throughout the paper. Let Gω denote the subgroup of G consisting of those elements fixed by ω. If F(G) denotes the Fitting subgroup of G then the upper Fitting series of G is defined by F1(G) = F(G) and Fr+1(G) = the inverse image in G of F(G/Fr(G)). G(r) denotes the rth derived group of G. The principal result of this paper may now be stated as follows: THEOREM 1. Let G be a group of odd order with an automorphism ω of order 2. Suppose that Gω is nilpotent, and that G(r)ω = 1. Then G(r) is nilpotent and G = F3(G).
EVD Dualdating Based Online Subspace Learning

Conventional incremental PCA methods usually only discuss the situation of adding samples. In this paper, we consider two different cases: deleting samples and simultaneously adding and deleting samples. To avoid the NP-hard problem of downdating SVD without right singular vectors and specific position information, we choose to use EVD instead of SVD, which is used by most IPCA methods. First, we propose an EVD updating and downdating algorithm, called EVD dualdating, which permits simultaneous arbitrary adding and deleting operation, via transforming the EVD of the covariance matrix into a SVD updating problem plus an EVD of a small autocorrelation matrix. A comprehensive analysis is delivered to express the essence, expansibility, and computation complexity of EVD dualdating. A mathematical theorem proves that if the whole data matrix satisfies the low-rank-plus-shift structure, EVD dualdating is an optimal rank-k estimator under the sequential environment. A selection method based on eigenvalues is presented to determine the optimal rank k of the subspace. Then, we propose three incremental/decremental PCA methods: EVDD-IPCA, EVDD-DPCA, and EVDD-IDPCA, which are adaptive to the varying mean. Finally, plenty of comparative experiments demonstrate that EVDD-based methods outperform conventional incremental/decremental PCA methods in both efficiency and accuracy.
Efficacy and safety of Gushen Antai Pills combined with dydrogesterone in the treatment of threatened miscarriage: a systematic review and meta-analysis

Background: Despite some progress has been made in the pathogenesis and treatment of threatened miscarriage (TM), conventional treatment remains suboptimal. Thus, complementary medicine gradually become a new treatment option for treating threatened miscarriage. Gushen Antai Pills (GAP), a classic prescription of Traditional Chinese medicine (TCM), has became a popular complementary therapy to conventional western medicine (dydrogesterone) in treating threatened miscarriage in recent years. However, a systematic summary and analysis for its therapeutic effects is lacking. This meta-analysis aimed to systematically evaluate the effectiveness and safety of Gushen Antai Pills combined with dydrogesterone in the treatment of threatened miscarriage. Methods: A systematic search across seven electronic databases was conducted from inception to 17 September 2022. Studies were included if they were randomized controlled trials (RCTs) evaluating the effect of integrating Gushen Antai Pills and dydrogesterone in patients with threatened miscarriage, and reported the outcomes of interest. All statistical analyses were conducted using the Revman5.3 and Stata 13 software. The GRADE system was used to evaluate the quality of evidence. Results: Ten eligible randomized controlled trials involving 950 participants were contained in this meta-analysis. The pooled analysis showed that Gushen Antai Pills combined with dydrogesterone can significantly reduce the incidence of early pregnancy loss (RR: 0.29; 95% CI: 0.19–0.42; p < 0.00001) and alleviate clinical symptoms (RR: 1.39; 95% CI: 1.22–1.59; p < 0.00001), compared with treatment of dydrogesterone alone. Also, meta-analysis indicated that integrating Gushen Antai Pills and dydrogesterone is more effective than using dydrogesterone alone in improving hormone levels (serum levels of progesterone, β-HCG and estradiol) for women with threatened miscarriage (all p < 0.00001). Meanwhile, the combined effects with significant heterogeneity also showed favorable consistency in the sensitivity analyses, indicating a good stability of present results. Moreover, no significant differences between Gushen Antai Pills combined with dydrogesterone and control group on adverse events was identified. The overall GRADE qualities were low to moderate. Conclusion: The overall available evidence suggested that Gushen Antai Pills combined with dydrogesterone had significant effects in improving pregnancy success rate, clinical symptoms and hormone levels for women with threatened miscarriage, with considerable safety and reliability. However, due to the partial heterogeneity, suboptimal quality and high risk of bias of some included studies, further rigorously designed randomized controlled trials are required. Systematic Review Registration: identifier https://INPLASY2022120035, https://inplasy.com/inplasy-2022-12-0035/.
Utilizing Non-Orthogonal Polarization With Polarization Reuse Technique for 4 × 4 MIMO Capacity Enhancement

5G communication promises fast and large data stream which requires higher capacity of a cellular wireless network. A higher capacity could be achieved with wider bandwidth and network densification, but they are expensive approaches. Instead, upgrading the wireless network with higher-order Multiple Input Multiple Output (MIMO) antenna system with polarization diversity can inexpensively escalate the peak data rate for higher capacity. We present a <inline-formula> <tex-math notation="LaTeX">$4\times 4$ </tex-math></inline-formula> MIMO cellular network scheme utilizing polarization reuse and using 4 polarization to reform the cellular network from current state of the art of dual polarization <inline-formula> <tex-math notation="LaTeX">$4\times 4$ </tex-math></inline-formula> MIMO scheme. 4 Polarization (vertical, Horizontal, ±45° slant) is used in 2 orthogonal polarization pair form, with a beam-separation among pair, to intensify polarization diversity and maximize the MIMO network channel capacity. This beam-separated polarization reuse technique minimizes the channel correlation which maximizes the probability of four independent data streams (rank 4). The simulated result of the channel capacity with the proposed scheme achieves a 30% higher capacity compared to the baseline configuration of 3-sector <inline-formula> <tex-math notation="LaTeX">$4\times 4$ </tex-math></inline-formula> MIMO. The field trial of the presented network indicates a higher portion of rank 4, supporting four independent data streams in the rich scattering environment of a cellular network.
The smallest late Miocene phocine from the Southern Caucasus and the Eastern Paratethys seal community crisis

ABSTRACT The Caucasus is one of the most important areas for the study of Paratethyan Neogene phocids, with a number of ‘paleorookery’ sites that are still poorly studied. In this study, the remains of a fossil phocine from the Late Miocene locality of Eldari I (late Vallesian/late Sarmatian s.l.) in the Southern Caucasus are described and compared with other Paratethyan phocines. The new materials obtained from the site consists of the right complete forelimb bones along with the carpal and metacarpal bones in natural anatomical articulation and a right innominate bone fragment. Additionally, published remains of ‘Phoca’ procaspica from Eldari I are analysed. Based on morphological and morphometric studies, the Eldari I phocine is assigned to the genus Praepusa. The skeletal material demonstrates a distinct combination of diagnostic traits that can be attributed to the smallest representative of the subfamily, Praepusa procaspica. During the early Late Miocene (10 Ma.), major palaeoecological and palaeogeographic changes took place in the Eastern Paratethyan basin, which significantly decreased the diversity of phocids and had a negative impact on the remnant taxa; this was expressed in the Eldari I and Küçükçekmece seals by the decrease in body size and a change in the feeding apparatus. urn:lsid:zoobank.org:pub:497DEEE9-8557-4136-8AD7-B8749A0285A2
MFAC parameter optimization based on improved sparrow search algorithm

Model-free adaptive control (MFAC) is based on data and does not depend on the mathematical model of the controlled object. It is simple in structure and easy to implement. At present, there are few methods to determine the parameters of MFAC controller, which brings considerable inconvenience to the research and application. Therefore, an improved sparrow search algorithm (ISSA) is proposed to optimize the parameters of MFAC. The ISSA improves its performance by introducing the piecewise chaotic map operator, and finally realizes the automatic optimization of MFAC. The results show that the ISSA has better searching speed and precision. After using optimized parameters for control, the overshoot is greatly reduced, and the oscillation phenomenon when the desired output changes or the external disturbance occurs is effectively overcome, which makes the system more robust.
Unlanded Class: Albania's Gender Gaps in Land Ownership and Inheritance

This study investigates gender gaps in access to land ownership and land inheritance in Albanian rural areas by combining a large-scale survey and five in-depth focus groups discussions. The article considers three sets of variables: place-based characteristics; family characteristics; and individual characteristics. Results find that rural societies lack awareness around legal property rights, undermine the confidence of women in myriad ways, and continue to rely on customary laws. Current inequalities are placed in the context of Albania's entrenched patriarchal system. Culture and tradition are as important as, if not more important than, legal frameworks surrounding land ownership and inheritance. The findings bring intersectionality issues into high relief: where patriarchy is combined with poverty, gender inequality is exacerbated. Findings call for a more holistic approach that combines efforts to improve legal literacy, raise awareness among all genders, and alleviate poverty for boosting women's inclusion in the economy. HIGHLIGHTS In Albania, patriarchal customary laws disfavor women when it comes to property ownership, inheritance, and decision making. Women in rural societies, in particular, rely on custom and have low awareness of their legal property rights. Women who are more informed about formal laws view themselves as more equal to men. Where patriarchy is combined with poverty, gender inequality is exacerbated. Education and legal literacy are key to overcoming entrenched patriarchy and fostering women’s empowerment.
Creators Matter. Perception and Pricing of Art Made by Human, Cyborgs and Humanoid Robots

Not only does the art market include human and nonhuman creators, it also incorporates technologically augmented artists, called cyborgs. They use wearables, sensors, chips, and even new organs to process various stimuli, such as electromagnetic radiation, atmospheric pressure, or ultraviolet rays, to produce artworks. Little is known however, how the objects produced by them are perceived by the art recipients. This paper applies an experimental study with 373 non-experts in the field of art. The results show that the perceived value of the painting depends on the type of agent and on the context of the evaluation. The price of objects created by a human artist is significantly higher if the context cue is the price of the canvas made by humanoid robot than another human. People value cyborg's artwork similarly to human-generated artwork when contextual cue is human, and similarly to robot-generated artwork when contextual cue is humanoid robot.
OSTTD: Offloading of Splittable Tasks With Topological Dependence in Multi-Tier Computing Networks

With the arrival of the Internet of Things (IoT) era, multi-tier computing has attracted significant attention. The multi-tier computing can organize many computing devices and provide sufficient computing resources to support various IoT applications. However, due to the complex architecture and the dynamic system status of the multi-tier computing network, task offloading for multi-tier computing is still challenging. This paper proposes a novel task offloading method named OSTTD, to deal with the Offloading of Splittable Tasks with Topological Dependence in multi-tier computing networks. OSTTD formulates the task offloading as a sequential decision-making problem and learns the task offloading policy by Deep Reinforcement Learning (DRL). Compared with existing task offloading approaches, OSTTD is the first method in which the topological dependence among sub-tasks of the splittable task is fully considered. OSTTD makes offloading decisions intelligently based on the dynamic system status and can be applied to various multi-tier network topology structures. To verify the effectiveness of OSTTD, we extend and build a latency-aware multi-tier computing simulation platform. Extensive simulations show that OSTTD can significantly reduce the task processing time, thus, improving the overall task processing efficiency in multi-tier computing networks.
Dopant diffusion in silicon: A consistent view involving nonequilibrium defects

A numerical solution of the problem of diffusion via a dual mechanism is obtained for P, As, and B diffusion in Si by solving the full system of impurity, vacancy, and self‐interstitial continuity equations. The suitable constants are derived by fitting on experimental results for diffusions in both inert and oxidizing ambients, and lead to interesting information on silicon point defects at high temperature. In particular, it is found that dopant diffusion is essentially vacancy assisted, whereas self‐diffusion proceeds primarily via self‐interstitials.