Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient Algorithms for Fixed-Rate

In quantisation of any source with a nonuniform probability density function, the entropy coding of the quantizer output can result in a substantial decrease in bit rate. A straight-forward entropy coding scheme presents us with the problem of the variable data rate. A solution in a space of dimensionality N is to select a subset of elements in the N-fold cartesian product of a scalar quantiaer and represent them with codcworda of the same length. A reasonable rule is to select the N-fold symbols of the highest For a memoryless source, this is equivalent to selecting the N-fold symbols with the lowest additiveself-information. The search/addressingof this scheme can no longer be achieved independently along the oncdimensional subspaces. In the case of a memoryless source, the selected subset has a high degree of structure which can be used to substantially decrease the complexity. In this work, a dynamic prog&nmbq approach is used to exploit this structure. We build our recursive structure required for the dynamic programming in a hierarchy of stages. This results in several benefits over the conventional trellis-based approaches. Using this structure, we develop efficient rules (based on aggregating the states) to substantially reduce the search/addredsing complexities while keeping the degradation negligible.
Objective weight computation based on personal preference for multi- objective optimization problem

For the problem that how to compute the objective weight based on personal preference during multi-objective optimization process, a method which decides the objective weights by solving a constrained optimization problem is proposed. Firstly, by using this method, the objective weight computation problem is transformed into a synthetical fitness optimization problem according to the statistics theory. Then the personal preference is transformed into the constrain condition of the synthetical fitness optimization problem. Finally, the gradient projection method is used to solve the constrained synthetical fitness optimization problem to get optimum objective weights. The proposed method is used to compute the objective weight of economical efficiency and safety during the electric locomotive repair strategy decision process, and the test result shows that the proposed method can get the optimum objective weight under the constraint of personal preference.
Impact of Technological Innovation Capabilities on the Market Value of Firms

In the era of globalisation and with the advent of knowledge economies, organisational innovation has assumed a critical role in enhancing economic performance of ¯rms. Proponents of the Resource Based View of the ¯rm and its more recent extensions such as the Knowledge Based View and Dynamic Capabilities Theory have suggested that generation, di®usion and application of organisational knowledge could be the source of sustained competitive advantage and superior performance of ¯rms. While there is near unanimity in accepting the vital role of innovation in a ¯rm's performance, consensus on what constitutes organisational innovation and how to measure it has proven to be elusive so far. Most previous research in this area has conceptualised innovation through one or more dimensions of a ¯rm's innovative capability using R&D of a ¯rm only. The measurement of the construct has thus re°ected this narrow conceptualisation with a single measure of R&D expenditure being the most often used proxy. This study utilises a broader de¯nition of organisational innovation capabilities that includes the generation, dissemination and strength of innovative activity in a ¯rm. The unique features of this study is that it uses multiple indicators of a ¯rm's innovation pro¯le along with lagged measures of market value using ¯xed e®ects panel data analysis.
Holothurin A Inhibits RUNX1-Enhanced EMT in Metastasis Prostate Cancer via the Akt/JNK and P38 MAPK Signaling Pathway

Due to the challenge of prostate cancer (PCa) management, there has been a surge in efforts to identify more safe and effective compounds that can modulate the epithelial–mesenchymal transition (EMT) for driving metastasis. Holothurin A (HA), a triterpenoid saponin isolated from Holothuria scabra, has now been characterized for its diverse biological activities. However, the mechanisms of HA in EMT-driven metastasis of human PCa cell lines has not yet been investigated. Moreover, runt-related transcription factor 1 (RUNX1) acts as an oncogene in prostate cancer, but little is known about its role in the EMT. Thus, the purpose of this study was to determine how RUNX1 influences EMT-mediated metastasis, as well as the potential effect of HA on EMT-mediated metastasis in endogenous and exogenous RUNX1 expressions of PCa cell lines. The results demonstrated that RUNX1 overexpression could promote the EMT phenotype with increased EMT markers, consequently driving metastatic migration and invasion in PC3 cell line through the activation of Akt/MAPK signaling pathways. Intriguingly, HA treatment could antagonize the EMT program in endogenous and exogenous RUNX1-expressing PCa cell lines. A decreasing metastasis of both HA-treated cell lines was evidenced through a downregulation of MMP2 and MMP9 via the Akt/P38/JNK-MAPK signaling pathway. Overall, our approach first demonstrated that RUNX1 enhanced EMT-driven prostate cancer metastasis and that HA was capable of inhibiting the EMT and metastatic processes and should probably be considered as a candidate for metastasis PCa treatment.
Evaluation of dynamic tumour tracking radiotherapy with real-time monitoring for lung tumours using a gimbal mounted linac.

: 35 Purpose: To evaluate feasibility and acute toxicities after dynamic tumour tracking (DTT) irradiation 36 with real-time monitoring for lung tumours using a gimbal mounted linac. 37 Materials and Methods: Spherical gold markers were placed around the tumour using a bronchoscope 38 prior to treatment planning. Prescription dose at the isocentre was 56 Gy in 4 fractions for T2a lung 39 cancer and metastatic tumour, and 48 Gy in 4 fractions for the others. Dose-volume metrics were 40 compared between DTT and conventional static irradiation using in-house developed software. 41 Results: Of twenty patients enrolled, DTT radiotherapy was successfully performed for 16 patients, 42 except 4 patients who coughed out the gold markers, one who showed spontaneous tumour regression, 43 and one where the abdominal wall motion did not correlate with the tumour motion. Dose 44 covering 95% volume of GTV was not different between the two techniques, while normal lung volume 45 receiving 20 Gy or more was reduced by 20%. A mean treatment time per fraction was 36 minutes using 46 DTT. With a median follow-up period of 13.2 months, no severe toxicity grade 3 or worse was observed. 47 Conclusions: DTT radiotherapy using a gimbal mounted linac was clinically feasible for lung treatment 48 without any severe acute toxicity.
KIER DISCUSSION PAPER SERIES KYOTO INSTITUTE OF ECONOMIC RESEARCH

In this study, we analyze how economic shocks affect six ASEAN Member States—Indonesia, Malaysia, Philippines, Singapore, Thailand, and Vietnam—in three dimensions: global, domestic, and uncertainty shocks. We collect macroeconomic indicators for 1990−2021 and calculate macroeconomic shocks based on the prediction errors of real GDP growth rates. First, we demonstrate that countries were significantly subjected to unforeseen negative economic shocks on average. Second, we show high synchronization of economic fluctuations and shocks within these countries and with the world. Third, by conducting regression analyses separately, we derive the following: (i) positive association between variations of the global real GDP growth rates and countries’ economic shocks; (ii) different quantitative significance of previous estimates among countries; (iii) country-specific domestic shocks; and (iv) correlation of global-and country-level uncertainty indices with negative economic shocks in some AMS. Our results highlight the relative importance of global, domestic, and uncertainty shocks in the AMS as 56.3%, 39.6%, and 2.8%, respectively. Finally, based on this dataset and conducted analysis, we also review the effect of the COVID-19 pandemic on these countries. JEL Classification : E32; F44; N15
An Improved User Requirements Notation (URN) Models' Construction Approach

Semi-formal software techniques have been very successful in industry, government institutions and other areas such as academia. Arguably, they owe a large part of their success to their graphical notation, which is more human-oriented than their counterpart text-based and formal notation techniques. However, ensuring the consistency between two or more models is one of the known challenges of these techniques. This work looks closely at the specific case of the User Requirements Notation (URN) technique. Although the abstract model of URN provides for link elements to ensure the consistency between its two main components, namely, Goal-Oriented Requirement Language (GRL) and Use Case Maps (UCM), the effective implementation of such links is yet to be fully addressed. This paper performs a detailed analysis of the existing URN models construction process and proposes an improved process with some guidelines to ensure, by construction, the correctness and consistency of the GRL and UCM models. A case study is used throughout the paper to illustrate the suggested solution.
Scanning Strategies in Laser Surface Texturing: A Review

Laser surface texturing (LST) is one of the most promising technologies for controllable surface structuring and the acquisition of specific physical surface properties needed in functional surfaces. The quality and processing rate of the laser surface texturing strongly depend on the correct choice of a scanning strategy. In this paper, a comparative review of the classical and recently developed scanning strategies of laser surface texturing is presented. The main attention is paid to maximal processing rate, precision and existing physical limitations. Possible ways of further development of the laser scanning strategies are proposed.
TITLE: Association of ITPA polymorphisms rs6051702/rs1127354 instead of rs7270101/rs1127354 as predictor of ribavirin-associated anemia in chronic hepatitis C treated patients. Authors:

Functional variants rs7270101 and rs1127354 of inosine triphosphatase (ITPA) were recently found to protect against ribavirin (RBV)-induced hemolytic anemia. However, no definitive data are yet available on the role of no functional rs6051702 polymorphism. Since a simultaneous evaluation of the three ITPA SNPs for hemolytic anemia has not yet been investigated, we aimed to understand the contribution of each SNPs and its potential clinical use to predict anemia in HCV treated patients. A retrospective analysis included 379 HCV treated patients. The ITPA variants rs6051702, rs7270101 and rs1127354 were genotyped and tested for association with achieving anemia at week 4. We also investigated, using multivariate logistic regression, the impact of each single and paired associated polymorphisms on anemia onset. All SNPs were associated with Hb decrease. The carrier of at least one variant allele in the functional ITPA SNPs was associated with a lower decrement of Hb, as compared to patients without a variant allele. In multivariate logistic regression analyses the carrier of a variant allele in the rs6051702/rs1127354 association (OR=0.11, p=1.75x10 -5 ) and Hb at baseline (OR=1.51, p=1.21x10 -4 ) were independently associated with protection against clinically significant anemia at week 4. All ITPA polymorphisms considered were shown to be significantly associated with anemia onset. A multivariate regression model based on ITPA genetic polymorphisms was developed for predicting the risk of anemia. Considering the characterization of pre-therapy anemia predictors, rs6051702 SNP in association to rs1127354 is more informative in order to avoid this relevant adverse event.
Household PV Power Scheduling Based on an Improved Sparrow Search Algorithm

With renewable energy development, wind and photovoltaic power generation will gradually penetrate the traditional distribution network and occupy a more important part of the distribution network. To make up for the shortage of solar power generation, an important measure is to install a household photovoltaic power generation system at the user end, which is an essential part of the future distribution network structure. Users who install PV in their homes will not only be self-sufficient in electricity but will also be able to sell excess power back to the grid. This kind of distributed power directly integrated into the grid without dispatch can cause severe instability to the grid. Based on this, we propose a power dispatching model in this paper, which takes renewable energy and household photovoltaic power generation as the primary power sources of the grid. Household photovoltaic users can sell excess power to the grid while ensuring power consumption. In scheduling, we use an improved sparrow search algorithm to publish scheduling tasks based on real-time power balance so that each generator can provide the most appropriate power. By comparing the running results of the algorithm with different scheduling times and the number of prosumers, we found that when the scheduling time is different, the total cost does not change. When the number of prosumers increases, the total cost will decrease, and the efficiency of the improved algorithm remains stable.
Platformed listening in podcasting: An approach from material and scales potentials

This article proposes to investigate delineations of the audience in podcasting in streaming media ecology. To meet this objective, we highlight the scales between contents, circulation, and consumption of podcasts in platformization contexts. We observe these relationships from an intersectional approach that involves spaces between codes, contents and software to understand the dynamics of interrelationships between contents and its flows which are associated with the emergence of varied audiences, derived from listening practices, characterized by binge listening; fidelity strategies; hybrid recommendation practices, playlists and cross-device consumption in multiplatform architecture.
Toward effective utilization of similarity based residual life prediction methods: Weight allocation, prediction robustness, and prediction uncertainty

Similarity based residual life prediction method is an emerging method for component residual life prediction. Studies on (a) the effect of weight function on prediction accuracy; (b) prediction robustness; and (c) prediction uncertainty of such method are rare. However, the abovementioned factors are essential concerns for wide application of a similarity based residual life prediction method. In this article, the essential elements of a similarity based residual life prediction method is outlined first with an extended weight function introduced. Afterward, an evaluation framework for investigating the prediction robustness of a similarity based residual life prediction method is established. In addition, a prediction uncertainty estimation method is proposed based on historical samples, inspired by cross-validation technique. In an extensive numerical investigation, a comparative study on the effect of weight function on prediction accuracy is conducted by tuning the parameters in the weight function. The prediction robustness of the similarity based residual life prediction method is evaluated in comparison with a time-series forecasting based residual life prediction method. Finally, the proposed prediction uncertainty estimation method is illustrated, which may facilitate further application of the similarity based residual life prediction method.
PARTICLE SWARM OPTIMIZATION BASED ON TENT MAP AND LOGISTIC MAP

Particle swarm optimization (PSO) is a population-based stochastic optimization originating from artificial life and evolutionary computation. PSO, however, has a feature of un-stability during its running, and like other evolutionary algorithms, has a tendency to get stuck in local optimal solutions during the search process. So, two improved particle swarm optimization are proposed in this paper, which are PSO with an initial population of tent map solutions and Gaussian mutation based on maximal focus distance (Tent-PSO) and PSO with an initial population of logistic map solutions and Gaussian mutation based on maximal focus distance (Logistic-PSO), respectively. Simulation results on two benchmark functions illustrate that the PSO proposed in this paper is feasible and efficient.
On the (Im)possibility of Distributed Samplers: Lower Bounds and Party-Dynamic Constructions

Distributed samplers, introduced by Abram, Scholl and Yakoubov (Eurocrypt ’22), are a one-round, multi-party protocol for securely sampling from any distribution. We give new lower and upper bounds for constructing distributed samplers in challenging scenarios. First, we consider the feasibility of distributed samplers with a malicious adversary in the standard model; the only previous construction in this setting relies on a random oracle. We show that for any UC-secure construction in the standard model, even with a CRS, the output of the sampling protocol must have low entropy. This essentially implies that this type of construction is useless in applications. Secondly, we study the question of building distributed samplers in the party-dynamic setting, where parties can join in an ad-hoc manner, and the total number of parties is unbounded. Here, we obtain positive results. First, we build a special type of unbounded universal sampler, which after a trusted setup, allows sampling from any distributed with unbounded size. Our construction is in the shared randomness model, where the parties have access to a shared random string, and uses indistinguishability obfuscation and somewhere statistically binding hashing. Next, using our unbounded universal sampler, we construct distributed universal samplers in the party-dynamic setting. Our first construction satisfies one-time selective security in the shared randomness model. Our second construction is reusable and secure against a malicious adversary in the random oracle model. Finally, we show how to use party-dynamic, distributed universal samplers to produce ideal, correlated randomness in the party-dynamic setting, in a single round of interaction.
Shifts in stream salt loads during and after prolonged droughts

It has been widely assumed that after prolonged droughts, catchment runoff recovers to pre‐drought levels. This assumption has recently been evaluated and challenged using empirical observations. However, water quality response and recovery, or otherwise, during and after prolonged droughts remains an open question. Answering this question potentially identifies any changes in catchment hydrological processes and water balance (e.g., the proportion of groundwater contribution to streamflow), thus informing the mechanisms for runoff non‐recovery after prolonged drought. Water quality responses to drought can also inform any long‐term water quality changes beyond what is observable from trend analyses. Here stream salt load changes were investigated using hidden Markov models (HMMs), where monthly rainfall was included as a predictor of stream salt loads. Monthly riverine salt fluxes at eight sites in Victoria (Australia) were examined before, during and after a prolonged drought in South‐East Australia—the Millennium Drought. Two‐state models, where salt loads varied between ‘normal’ and ‘low’ states, were found to better predict in‐stream salt loads compared to single‐state models. The results showed that catchments shifted to a low salt load state generally after the catchment changed to a low runoff state. As groundwater is understood to be the major source of salts in these catchments, this suggests that reductions in groundwater flow into rivers occur as a result of the shift to a lower runoff state. Understanding how readily water quality in catchments shift to different states during and after prolonged droughts enables appropriate catchment management based on our understanding of changes to catchment hydrology.
Prognostic Value of sST2 in Heart Failure

In recent years, there has been growing interest in the risk stratification for heart failure, and the use of multiple biomarkers to identify different pathophysiological processes associated with this condition. One such biomarker is soluble suppression of tumorigenicity-2 (sST2), which has shown some potential for integration into clinical practice. sST2 is produced by both cardiac fibroblasts and cardiomyocytes in response to myocardial stress. Other sources of sST2 are endothelial cells of the aorta and coronary arteries and immune cells such as T cells. Indeed, ST2 is also associated with inflammatory and immune processes. We aimed at reviewing the prognostic value of sST2 in both chronic and acute heart failure. In this setting, we also provide a flowchart about its potential use in clinical practice.
Exploring the Influence of YouTube Videos on Purchase Intentions among Millennial Consumers in Tasikmalaya City

The paradigm of consumer purchase decisions has been altered by the digital marketing landscape. Presently, consumers actively seek reliable and truthful information to assist them in their purchasing decisions. A noteworthy group in this regard is the Millennial generation, who dedicate a substantial amount of their time to online activities, with a particular focus on social media platforms. This generation, often referred to as "technology savvy," demonstrates their reliance on technology and employs it for various decisions that impact them, including their purchasing intentions. Prior to making a purchase, Millennial extensively research product information and align it with their individual needs and interests. The objective of this research was to examine the impact of user-generated content (UGC) on the purchasing intentions of Millennials in Tasikmalaya city. The investigation was conducted utilizing the prominent social media platform, YouTube. The primary aims of this research were to identify the factors that influence purchasing intentions and to comprehend the attitudes of Millennials towards purchasing after watching product-related videos on YouTube.To achieve these goals, the researcher administered an online questionnaire to individuals who had viewed smartphone product videos on YouTube. The questionnaire, comprising 350 valid responses, served as the means to test the hypotheses using the Structural Equation Modelling approach. The research yielded significant findings, that factors such as video quality, duration, and the adeptness and delivery of the presentation are crucial in influencing the purchase decisions of Millennial consumers. In summary, these findings imply that those aspects play a substantial and positive role in heightening the purchase intentions of Millennials in Tasikmalaya City.
Multi-Criteria Decision Making Based on Choquet Integral under Hesitant Fuzzy Environment

This paper investigates the multi-criteria decision making under hesitant fuzzy environment in which the weight vectors of criteria are known. First, we use the Choquet integral to propose a hesitant fuzzy aggregation operator, which considers the interactions phenomena among the decision making criteria. Then, some of its desirable properties and special cases are investigated. Furthermore, a procedure of multi-criteria decision making based on hesitant fuzzy Choquet integral operator is given under hesitant fuzzy environment. Finally, an example is given to illustrate the practicability of the proposed method.