Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterising the Effect of Wnt/β-Catenin Signalling on Melanocyte Development and Patterning: Insights from Zebrafish (Danio rerio)

Zebrafish (Danio rerio) is a well-established model organism for studying melanocyte biology due to its remarkable similarity to humans. The Wnt signalling pathway is a conserved signal transduction pathway that plays a crucial role in embryonic development and regulates many aspects of the melanocyte lineage. Our study was designed to investigate the effect of Wnt signalling activity on zebrafish melanocyte development and patterning. Stereo-microscopic examinations were used to screen for changes in melanocyte count, specific phenotypic differences, and distribution in zebrafish, while microscopic software tools were used to analyse the differences in pigment dispersion of melanocytes exposed to LiCl (Wnt enhancer) and W-C59 (Wnt inhibitor). Samples exposed to W-C59 showed low melanocyte densities and defects in melanocyte phenotype and patterning, whereas LiCl exposure demonstrated a stimulatory effect on most aspects of melanocyte development. Our study demonstrates the crucial role of Wnt signalling in melanocyte lineage and emphasises the importance of a balanced Wnt signalling level for proper melanocyte development and patterning.
Not All Neighbors Matter: Point Distribution-Aware Pruning for 3D Point Cloud

Applying deep neural networks to 3D point cloud processing has demonstrated a rapid pace of advancement in those domains where 3D geometry information can greatly boost task performance, such as AR/VR, robotics, and autonomous driving. However, as the size of both the neural network model and 3D point cloud continues to scale, reducing the entailed computation and memory access overhead is a primary challenge to meet strict latency and energy constraints of practical applications. This paper proposes a new weight pruning technique for 3D point cloud based on spatial point distribution. We identify that particular groups of neighborhood voxels in 3D point cloud contribute more frequently to actual output features than others. Based on this observation, we propose to selectively prune less contributing groups of neighborhood voxels first to reduce the computation overhead while minimizing the impact on model accuracy. We apply our proposal to three representative sparse 3D convolution libraries. Our proposal reduces the inference latency by 1.60× on average and energy consumption by 1.74× on NVIDIA GV100 GPU with no loss in accuracy metric
Resistance to Chemotherapeutic 5-Fluorouracil Conferred by Modulation of Heterochromatic Integrity through Ino80 Function in Fission Yeast

5-Fluorouracil (5-FU) is a conventional chemotherapeutic drug widely used in clinics worldwide, but development of resistance that compromises responsiveness remains a major hurdle to its efficacy. The mechanism underlying 5-FU resistance is conventionally attributed to the disruption of nucleotide synthesis, even though research has implicated other pathways such as RNA processing and chromatin dysregulation. Aiming to clarify resistance mechanisms of 5-FU, we tested the response of a collection of fission yeast (Schizosaccharomyces pombe) null mutants, which confer multiple environmental factor responsiveness (MER). Our screen identified disruption of membrane transport, chromosome segregation and mitochondrial oxidative phosphorylation to increase cellular susceptibility towards 5-FU. Conversely, we revealed several null mutants of Ino80 complex factors exhibited resistance to 5-FU. Furthermore, attenuation of Ino80 function via deleting several subunit genes reversed loss of chromosome-segregation fidelity in 5-FU in the loss-of-function mutant of the Argonaute protein, which regulates RNA interference (RNAi)-dependent maintenance of pericentromeric heterochromatin. Our study thus uncovered a critical role played by chromatin remodeling Ino80 complex factors in 5-FU resistance, which may constitute a possible target to modulate in reversing 5-FU resistance.
The Effect of Sample Preparation Techniques on Lignin Fourier Transform Infrared Spectroscopy

The characterization and quantification of functional groups in technical lignins are among the chief obstacles of the utilization of this highly abundant biopolymer. Although several techniques were developed for this purpose, there is still a need for quick, cost-efficient, and reliable quantification methods for lignin. In this paper, three sampling techniques for fourier transform infrared (FTIR) spectroscopy were assessed both qualitatively and quantitatively, delineating how these affected the resultant spectra. The attenuated total reflectance (ATR) of neat powders and DMSO-d6 solutions, as well as transmission FTIR using the KBr pelleting method (0.5 wt%), were investigated and compared for eight lignin samples. The ATR of neat lignins provided a quick and easy method, but the signal-to-noise ratios in the afforded spectra were limited. The ATR of the DMSO-d6 solutions was highly concentration dependent, but at a 30 wt%, acceptable signal-to-noise ratios were obtained, allowing for the lignins to be studied in the dissolved state. The KBr pelleting method gave a significant improvement in the smoothness and resolution of the resultant spectra compared to the ATR techniques. Subsequently, the content of phenolic OH groups was calculated from each FTIR mode, and the best correlation was seen between the transmission mode using KBr pellets and the ATR of the neat samples (R2 = 0.9995). Using the titration measurements, the total OH and the phenolic OH group content of the lignin samples were determined as well. These results were then compared to the FTIR results, which revealed an under-estimation of the phenolic OH groups from the non-aqueous potentiometric titration, which was likely due to the differences in the pKa between the lignin and the calibration standard 4-hydroxybenzoic acid. Further, a clear correlation was found between the lower Mn and the increased phenolic OH group content via SEC analyses. The work outlined in this paper give complementary views on the characterization and quantification of technical lignin samples via FTIR.
Aspergillus niger Fermentation Broth Promotes Maize Germination and Alleviates Low Phosphorus Stress

Aspergillus niger is a type of soil fungus with the ability to dissolve insoluble phosphate and secrete organic metabolites such as citric acid. However, whether cell-free Aspergillus niger fermentation broth (AFB) promotes maize growth and alleviates low-phosphorus stress has not been reported. In this study, we explored their relationship through a hydroponics system. The results indicated that either too low or too high concentrations of AFB may inhibit seed germination potential and germination rate. Under low phosphorus conditions, all physiological indexes (biomass, soluble sugar content, root length, etc.) increased after AFB was applied. A qRT-PCR analysis revealed that the expression of the EXPB4 and KRP1 genes, which are involved in root development, was upregulated, while the expression of the CAT2 and SOD9 genes, which are keys to the synthesis of antioxidant enzymes, was downregulated. The expression of LOX3, a key gene in lipid peroxidation, was down-regulated, consistent with changes in the corresponding enzyme activity. These results indicate that the application of AFB may alleviate the oxidative stress in maize seedlings, reduce the oxidative damage caused by low P stress, and enhance the resistance to low P stress in maize seedlings. In addition, it reveals the potential of A. niger to promote growth and provides new avenues for research on beneficial plant-fungal interactions.
Effect of the Supplementation of Endogenous Probiotics in Feed on Growth Performance, Digestive Enzyme Activity, and Non-Specific Immunity Gene Expression of Sandfish, Holothuria scabra Juveniles

The present study aimed to evaluate the effects of endogenous compared to commercial probiotics on the growth, digestive enzyme activity, and non-specific immunity of sandfish juveniles. Treatments were: A. diet without probiotic; B. diet supplemented with endogenous probiotics Gamma proteobacterium strain M-4, Bacillus subtilis strain Q-1, Bacillus sp. strain E-2; C. diet supplemented with a commercial probiotic containing B. subtilis, B. licheniformis, and B. pumilus. The research was conducted for 4 months using 12 plastic containers, 30 juveniles each (initial weight of 2.72±0.37 g, mean ± standard deviation). From each container, ten samples were taken randomly every 14 days and weighed and three intestine samples at initial and every following month to analysis enzyme activities. At the end the study, all juveniles were counted and weighed individually, and performed a challenge test by injected a 106 CFU ml-1 Vibrio azureus strain 4C-1 at 0.1 ml/ind. Immune response observed were: total coelomate and gene expression (SOD, CAT, LZM) by Quantitative real-time PCR. The specific growth rate of juveniles fed by diet B was significantly different from treatment A (P<0.05), its final weight was higher compared to diets A and C (P<0.05). Protease, lipase, and amylase activity in treatment B was higher compared to C and A (P<0.05). The survival rate, total coelomocyte count, gene expression after being challenged were higher in treatment B compared to C and A (P<0.05). The present study showed endogenous probiotics promote growth, improve digestion enzyme activity, and stimulate non-specific immune responses.
Content Analysis of Class X High School Physics Learning Video by Koh Ben on the Big Course YouTube Channel

This paper reports research that aims to determine the feasibility of a learning video made by Koh Ben on the 'BIG Course' YouTube channel. Video learning is one of the most frequently used learning media and only videos that are appropriate can provide maximum benefits in learning physics. This study used a content analysis design with 4 analyzes carried out, namely content analysis, presentation analysis, graphic analysis, and language analysis. The learning videos analyzed were taken directly from the YouTube channel totaling 20 videos containing material for class X physics in the 2013 curriculum. From the results and discussion, it was concluded that the 20 videos for teaching physics for class X were very feasible with a percentage of 89.25% on the content aspect, 86% on the aspect delivery, 91.5% in the graphic aspect, and 99.75% in the language aspect
A Binary Block Code Generated by JU-Algebras

Studies on the binary block codes generated by some ordered algebraic structures have been the interest of many researchers. In this paper, we study the binary block code generated by an arbitrary JU-algebra and investigate some of its properties. For this intent, we introduce the notion of a JU function \(\phi\) on a nonempty set P into a JU-algebra X, and by using that concept, j-functions and j-subsets of P for an arbitrary element j on a JU-algebra X are investigated. Furthermore, we define a new order on the generated code C based on the JU-algebra X, and show that every finite JU-algebra with its order and the corresponding generated code C with the defined order have the same structures. Finally, we generate a JU-algebra from a particular set of binary block code.
Polynomial structures and generic Torelli for projective hypersurfaces

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Study on the Synergistic Evolutionary Effects of China’s Digital Economy Core Industry and Energy Industry Based on DEA Malmquist Synergistic Development Model and Grey Correlation Analysis

The burgeoning digital economy has facilitated a transformation and upgraded within the energy industry, which, in return, continually guarantees robust energy security for the expansion of the digital economy. China’s digital economy and energy sector have increasingly merged and innovated in the domains of technology, market, and operations in recent years. Consequently, an accurate assessment of the interplay between these two sectors and their evolving patterns is vital for policy formulation and execution concerning their joint development. Drawing on 14,520 authoritative departmental statistics from 30 Chinese provinces spanning 2011 to 2021, this study applies techniques such as Data Envelopment Analysis (DEA)-Malmquist, grey correlation, and objective empowerment to develop a quantitative evaluation model for the reciprocal evolution of these industries finding that the own synergistic evolutionary effect of these two industries experienced fluctuations, declining from 0.8512 and 0.7535 in 2012 to 0.4590 and 0.4378 in 2021, respectively. Conversely, the comprehensive synergistic evolutionary effect between industries increased from 0.5879 in 2012 to 0.6841 in 2021. Building upon these findings, a series of development proposals are put forth to provide valuable insights and recommendations for advancing the high-level coordinated development of China’s digital economy and energy industry.
LOW-COST STRATA MAINTENANCE ISSUES AND COST IMPACT

The economic and social developments in Malaysia have encouraged internal migration of locals from rural to urban areas, in response to this migration, the government initiates high-rise developments for housing to fulfil these movements. Maintenance work practices aims to benefit the building’s operational age. Maintenance includes all building elements including the façade, flooring, plumbing, electrical and structural maintenance. The aim of this study is to identify the most common maintenance issue that occurred and reported within selected strata schemes. The objective is to identify maintenance issues as reported and observed by strata management bodies and which have the highest cost impact according to the management bodies. A survey involving 50 strata management bodies within the Klang Valley amongst low and medium low-cost strata schemes were conducted and analysed. The result shows that the top three most common maintenance issues are clogged plumbing roofing structure, leakage, and sewer pipe maintenance whilst maintenance with highest cost impacts are relating to general repair, maintenance works and general electrical supply maintenance. Other problems include small but repetitive repairs such as corridor lightings, drainage clogging, leakages and other works that generally affect the residents’ use and enjoyment of the common properties.
Fintech Risks and Continuance to use on Generation Z

Purpose: Most fintech users will be the generation Z; thus, understanding the generation Z is essential. This study is aimed to explore the relationship between financial risk, legal risk, security risk, and operational risk with risk in using fintech. This study also examines fintech risk influence on generation Z’s intention to continuance to use fintech. Theoretical framework: Previous studies (Darmiasih & Setiawan, 2020; Leon & Diana, 2020; Putritama, 2019; Ryu, 2018) analyzed the relationship between risk and fintech use continuance by excluding the generation Z perspective from the study. This study fills the research gap by focusing on Generation Z. Design/methodology/approach: This study adopts a quantitative approach. This study distributes online questionnaires to Generation Z in Indonesia. This study utilized the Partial Least Square approach to answer the research question using 199 responses earned from the country survey. The analysis is assisted by SmartPLS 3.2. 8 software. Findings: The analysis result showed a positive relationship between financial risk, legal risk, security risk, and operational risk with risk in using fintech. This study also found a negative relationship between fintech risk and Generation Z’s intention to continuance to use fintech among Generation Z Research, Practical & Social implications: This study gives a new insight into the fintech industry in anticipating future failure in the business. Originality/value: This study finding provides a new perspective (Generation Z) on fintech use and risk investigation, which was rarely conducted in the previous studies most publications.
Beamforming for NOMA Under Similar Channel Conditions Including Near-Field Formulation

Non-Orthogonal Multiple Access (NOMA) has emerged as a promising strategy for increasing spectral efficiency in wireless multiuser communications. The performance of NOMA highly depends on the users’ channel conditions, being enhanced when these are significantly different, i.e., one strong user and one weak user. On the contrary, rate fairness is compromised when users present similar channel conditions since the maximization of the sum capacity may result in the allocation of most resources to one user. In general, this problem can be avoided with correct user grouping. However, there are scenarios, e.g., picocells or femtocells, where finding users with distinctive channel conditions is not always possible. In this paper, we study the application of beamforming in a two-user Multiple-Input-Single-Output (MISO) downlink NOMA system to achieve rate fairness through channel shaping even when the conditions of both users are similar. The proposed formulation includes the effect of Near-Field (NF) radiation, which yields an accurate modeling of the problem at hand in a small-cell scenario. We use an optimization algorithm to jointly calculate both the power allocation and the complex weights to be applied to the elements of a given array. Numerical simulations across scenarios with distinctive or similar channel conditions show that the proposed approach outperforms alternative NOMA methods in ensuring rate fairness. Additionally, it yields improved overall rates compared to Far-Field (FF) formulation-based modelling and beamforming Time Division Multiple Access (TDMA) solutions.
The enhancement of viscous fingering with bidisperse particle suspension

Viscous fingering is observed experimentally when a bidisperse suspension displaces air inside a Hele-Shaw cell, despite the stabilising viscosity ratio between the invading (suspension) and defending (air) phases. Careful experiments are carried out to characterise this instability by either systematically varying the large-particle concentrations $\unicode[STIX]{x1D719}_{l0}$ at constant total concentrations $\unicode[STIX]{x1D719}_{0}$ , or changing $\unicode[STIX]{x1D719}_{0}$ with fixed $\unicode[STIX]{x1D719}_{l0}$ . Leading to the instability, we observe that larger particles consistently enrich the fluid–fluid interface at a faster rate than small particles. This size-dependent enrichment of the interface leads to an earlier onset of the fingering instability for bidisperse suspensions, compared to their monodisperse counterpart of all small particles. In particular, even the small presence of large particles is shown to effectively lower the total particle concentration needed for fingering, compared to the all-small-particle case. We hypothesise that the key mechanism behind this enhanced viscous fingering is the size-dependent nature of shear-induced migration of particles far upstream from the interface. A reduced equilibrium model is derived based on the modified suspension balance model to verify this hypothesis, in reasonable agreement with experiments.
Derivation of Coupled PCA and SVD Learning Rules from a Newton Zero-Finding Framework

In coupled learning rules for PCA (principal component analysis) and SVD (singular value decomposition), the update of the estimates of eigenvectors or singular vectors is influenced by the estimates of eigenvalues or singular values, respectively. This coupled update mitigates the speed-stability problem since the update equations converge from all directions with approximately the same speed. A method to derive coupled learning rules from information criteria by Newton optimization is known. However, these information criteria have to be designed, offer no explanatory value, and can only impose Euclidean constraints on the vector estimates. Here we describe an alternative approach where coupled PCA and SVD learning rules can systematically be derived from a Newton zero-finding framework. The derivation starts from an objective function, combines the equations for its extrema with arbitrary constraints on the vector estimates, and solves the resulting vector zero-point equation using Newton's zero-finding method. To demonstrate the framework, we derive PCA and SVD learning rules with constant Euclidean length or constant sum of the vector estimates.
Verifiable Privacy-Preserving Heart Rate Estimation Based on LSTM

Remote heart rate (HR) estimation via facial videos has emerged as an attractive application for healthcare monitoring. Long short-term memory (LSTM) is a kind of deep recurrent neural network architecture used for modeling sequential information, which can be utilized for remote HR estimation. Outsourcing computation is an emerging paradigm for enterprises or individuals with a huge volume of private data but limited computing power for data modeling and analysis, but the risks of privacy leakage cannot be ignored. Prior privacy-preserving LSTM-based protocols only protect sensitive data or model parameters, or approximate nonlinear functions with somewhat utility degradation. To mitigate the aforementioned issues, we propose a verifiable outsourcing protocol of LSTM training for HR estimation (VOLHR) based on batch homomorphic encryption, which not only ensures the confidentiality of the local data and model parameters but also guarantees the verifiability of the model predictions to resist the deceptive attacks. Theoretical analysis proves that VOLHR provides a higher level of privacy protection than the prior works. Computational cost analysis demonstrates that VOLHR can reduce the computational overhead greatly compared with the original LSTM models with different structures. To exhibit the practical utility, we implement VOLHR on two real-world data sets for HR estimation. Extensive evaluations demonstrate that VOLHR achieves almost the same performance as the original LSTM model and outperforms prior related protocols.