Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparative study of analytical/semi-analytical methods for prediction of axial strength of cold-formed steel wall panels with sheathing

ABSTRACT Load-bearing cold-formed steel (CFS) wall panels comprise of a stud (C-section), track (U-section) and sheathing. Sheathing is fastened to the CFS frame with self-drilling screws, which has an effect on the axial load-carrying capacity of panels. Experiments are complex and often expensive as they require use of different resources (raw material, manpower etc.). Therefore, conducting experiments is not always possible and an efficient design tool is necessary. Few studies are present in literature on comparing the effectiveness of available design methodologies. For the first time, an attempt is made to compare all the three (03) presented mathematical models together to predict the axial strength of CFS wall panels with sheathing. The present study examines the effectiveness of such analytical/semi-analytical tools, namely, Rayleigh-Ritz (R-R) method, Differential equation of equilibrium (DEEq) method and Constrained and Unconstrained Finite Strip Method – Direct Strength Method (CUFSM-DSM) for estimation of axial load-carrying capacity of sheathed CFS panels. The results show that CUFSM-DSM can be utilized meritoriously for evaluation of sheathed CFS wall panels.
Identification of CT Imaging Phenotypes of Colorectal Liver Metastases from Radiomics Signatures—Towards Assessment of Interlesional Tumor Heterogeneity

Simple Summary Tumoral heterogeneity, which is a major challenge in therapy planning, is often characterized by genetic alterations. In this study, an image-based approach was used to identify metastases subtypes by radiomics features. Feature selection and reduction using Pearson correlation threshold and LASSO regression resulted in four final features. After unsupervised clustering and following visual assessment, five lesion clusters could be identified and defined, which had a significant (p < 0.01) correlation with sex, primary location, T- and N-status, and mutational status. Abstract (1) Background: Tumoral heterogeneity (TH) is a major challenge in the treatment of metastatic colorectal cancer (mCRC) and is associated with inferior response. Therefore, the identification of TH would be beneficial for treatment planning. TH can be assessed by identifying genetic alterations. In this work, a radiomics-based approach for assessment of TH in colorectal liver metastases (CRLM) in CT scans is demonstrated. (2) Methods: In this retrospective study, CRLM of mCRC were segmented and radiomics features extracted using pyradiomics. Unsupervised k-means clustering was applied to features and lesions. Feature redundancy was evaluated by principal component analysis and reduced by Pearson correlation coefficient cutoff. Feature selection was conducted by LASSO regression and visual analysis of the clusters by radiologists. (3) Results: A total of 47 patients’ (36% female, median age 64) CTs with 261 lesions were included. Five clusters were identified, and the categories small disseminated (n = 31), heterogeneous (n = 105), homogeneous (n = 64), mixed (n = 59), and very large type (n = 2) were assigned based on visual characteristics. Further statistical analysis showed correlation (p < 0.01) of clusters with sex, primary location, T- and N-status, and mutational status. Feature reduction and selection resulted in the identification of four features as a final set for cluster definition. (4) Conclusions: Radiomics features can characterize TH in liver metastases of mCRC in CT scans, and may be suitable for a better pretherapeutic classification of liver lesion phenotypes.
Parsimonious sensing with Active Learning: applications with context mining and environmental sensing

The unprecedented success of Web 2.0, and with it, social media services, has resulted in massive amounts of user-generated data. Traditional techniques are no longer adequate to deal with this sheer amount of information. In an attempt to address this problem, new techniques that can be applied to big data, are being proposed in an increasingly frequent way. In this dissertation, the concept of parsimonious sensing and some of its applications are presented. Parsimonious sensing attempts to select the most relevant information from a large dataset, thus reducing the cost of its analysis. To do this, it employs different techniques such as active learning, also know as optimal experimental design in the field of statistics. We also explore some innovative methods of identifying relevant anomalies from a large dataset to be subsequently explored. This dissertation studies the application of parsimonious sensing on three unique datasets. The first main experience studies the employment of active learning in an environmental sensing network system with air quality parameters. The second experience depicts an attempt to predict the number of hits for a certain query related to events happening in Singapore, thus decreasing the number of required queries. The third and last experiment makes use of a dataset provided by a major taxi company in Singapore and tries to identify traffic anomalies and later, synthesize queries that are run through a search engine in order to identify the context of the anomalies. We found the application of parsimonious sensing to be successful when implemented in the context of environmental sensing. We have further developed a system capable of identifying traffic anomalies and returning a number of links that can potentially explain why they happened. The fully automated system has been shown to be better than a hybrid system, composed of information retrieved both automatically and manually. The findings from this dissertation can hopefully shed some light on the possible applications of parsimonious sensing to diverse contexts.
Optimization of culture condition for the gellan production by Pseudomonas elodea ATCC 31461

Pseudomonas elodea ATCC 31461에 의해 생산되는 미생물 다당류인 gellan의 최적 조건을 확립하기 위해 flask상에서 inoculum size, 탄소원 종류 및 농도, 질소원 종류, C/N ratio등을 조사하였다. Gellan 생산을 위한 최적 inoculum size는 5%(v/v)로 나타났으며, 1.0%(w/v)의 glucose에서 2. 22의 최대 specific yield 와 0.03 g/l의 생산성을 얻을 수 있었다. 또한 ammonium nitrate가 없을 때 최대 생산을 얻을 수 있어, gellan 생산을 위해서 nitrogen limitation이 필요함을 알 수 있었다. Glucose와 bactopeptone을 이용하여 C/N ratio를 조사한 결과 20에서 gellan 생산이 가장 높게 나왔다.
Exploring institutional competing logic for sustainability implementation of retail chains

PurposeTaking into account retailers' critical position in the value chain, their sector's economic significance and environmental externalities, in addition to the institutional agenda, this paper aims to explore the drivers influencing retailers to shift to more sustainable business models.Design/methodology/approachThe paper utilises the institutional competing logic, including in-depth interviews with major supermarket retail chains and one expert group discussion. The data gathered in Germany and Lithuania were complemented by desk research analysis, including corporate social responsibility (CSR) reports and management reports.FindingsThe paper provides empirical insights into how multiple drivers through institutional competing logic are brought about influencing the shift to more sustainable business models. The results show that retail chains in both countries implement their sustainability based on triple environmental-legal-financial drivers. However, different types of retail chains–namely premium retailers, typical retailers and discounters–implement their sustainability discourse differently.Research limitations/implicationsBecause of the chosen research approach, the results may lack generalisability. Therefore, researchers are encouraged to test the proposed propositions further.Social implicationsInterestingly, retailers “shift” their responsibility to the consumers rather than encourage themselves to make more sustainable choices. The authors observe a more passive and responsive role of retailing chains because of the inherent trade-off between revenue growth and sustainable consumption.Originality/valueThe original contribution lies in exploring how retail chains adapt institutional competing logic and are influenced by multiple drivers when implementing their sustainability activities. In addition, the authors propose a conceptual model for retailers' sustainability management, as well as formulate three research propositions.
"ShowerPower" New Cooling Concept for Automotive Applications

A new concept for liquid cooling is presented that solves the two mayor problems relat ed with liquid cooling of power modules: The high cost associated with creating complicated structures in metal parts and the inhomogeneous cooling. Superior thermal performance is offered at a very low c ost because it is possible to cool standard flat - baseplate power modules using simple low cost plastic parts ; this is a typical example of metal replacement because the expensive structuring of metal parts has been transferred to plastic parts. Odd -shape non -planar applications are readily applicable as well. The trick is to supply many individual cooling cells with coolant in parallel, thus achieving uniform cooling; going a step further the cooling cells can be designed individually, e.g. for dealing wi th hot spots.
Assessing behaviour states of a forest carnivore in a road-dominated landscape using Hidden Markov Models

Anthropogenic infrastructures and land-use changes are major threats to animal movements across heterogeneous landscapes. Yet, the behavioural consequences of such constraints remain poorly understood. We investigated the relationship between the behaviour of the Common genet (Genetta genetta) and road proximity, within a dominant mixed forest-agricultural landscape in southern Portugal, fragmented by roads. Specifically, we aimed to: (i) identify and characterise the behavioural states displayed by genets and related movement patterns; and (ii) understand how behavioural states are influenced by proximity to main paved roads and landscape features. We used a multivariate Hidden Markov Model (HMM) to characterise the fine-scale movements (10-min fixes GPS) of seven genets tracked during 187 nights (mean 27 days per individual) during the period 2016–2019, using distance to major paved roads and landscape features as predictors. Our findings indicated that genet’s movement patterns were composed of three basic behavioural states, classified as “resting” (short step-lengths [mean = 10.6 m] and highly tortuous), “foraging” (intermediate step-lengths [mean = 46.1 m] and with a wide range in turning angle) and “travelling” (longer step-lengths [mean = 113.7 m] and mainly linear movements). Within the genet’s main activity-period (17.00 h-08.00 h), the movement model predicts that genets spend 36.7% of their time travelling, 35.4% foraging and 28.0% resting. The probability of genets displaying the travelling state was highest in areas far away from roads (> 500 m), whereas foraging and resting states were more likely in areas relatively close to roads (up to 500 m). Landscape features also had a pronounced effect on behaviour state occurrence. More specifically, travelling was most likely to occur in areas with lower forest edge density and close to riparian habitats, while foraging was more likely to occur in areas with higher forest edge density and far away from riparian habitats. The results suggest that, although roads represent a behavioural barrier to the movement of genets, they also take advantage of road proximity as foraging areas. Our study demonstrates that the HMM approach is useful for disentangling movement behaviour and understanding how animals respond to roadsides and fragmented habitats. We emphasise that road-engaged stakeholders need to consider movement behaviour of genets when targeting management practices to maximise road permeability for wildlife.
Valve-in-Valve Transcatheter Aortic Valve Implantation With Acute Left and Right Coronary Artery Occlusion: A Case Report

Acute coronary artery occlusion is a relatively rare procedural adverse event in valve-in-valve transcatheter aortic valve implantation. Here we present a case of a 26-mm Sapien 3 prosthetic valve implantation in a degenerated 23-mm Freedom Solo bioprosthetic surgical valve with subsequent left and right coronary occlusion. Left coronary artery occlusion was managed immediately with the use of an upfront coronary artery protection technique and drug-eluting stent placement. Right coronary artery occlusion presented with right-sided heart failure and cardiac arrest that required resuscitation and additional hemodynamic support. As the artery could not be engaged with a catheter, a combination of intravenous antithrombotic and anticoagulant therapy was used as a successful bailout step to restore adequate coronary flow.
Estimators of long range dependence : a survey of finite samples and robustness

In traditional financial theory the returns of prices are assumed to be independent of each other, they are said to have short memory. However, it has been shown that returns in many cases are correlated and these instance are said to possess long memory or long range dependence. This phenomenon is also found in other research disciplines such as biology, economics, physics, linguistics and hydrology. Long memory can not be established on beforehand but has to be estimated. The goal of this thesis is to evaluate seven estimators of long range dependence by generating time series with varying known long memory parameters and then measure the performance of the estimators under such environments. The estimators are also evaluated when estimating a long memory time series distorted by heavy tailed noise for varying levels of corruption. The noise has similar features to what is observed in financial data. To the author’s knowledge this study of estimation algorithms has the broadest coverage of long memory parameters and noise in terms of numbers of replications which make the results statistically valid. The general observation is that a heavy persistent or heavy anti-persistent series leads to less accurate estimates although some estimators are unaffected by this. There are also differences among the point estimators in how they perform under different sample sizes. When adding noise to the time series the estimation is affected little by persistent series but is affected heavily by the anti-persistent series.
Detecting fake reviews with supervised machine learning algorithms

ABSTRACT This study provides an applicable methodological procedure applying Artificial Intelligence (AI)-based supervised Machine Learning (ML) algorithms in detecting fake reviews of online review platforms and identifies the best ML algorithm as well as the most critical fake review determinants for a given restaurant review dataset. Our empirical findings from analyzing 16 determinants (review-related, reviewer-related, and linguistic attributes) measured from over 43,000 online restaurant reviews reveal that among the seven ML algorithms, the random forest algorithm outperforms the other algorithms and, among the 16 review attributes, time distance is found to be the most important, followed by two linguistic (affective and cognitive cues) and two review-related attributes (review depth and structure). The present study contributes to the literature on fake online review detection, especially in the hospitality field and the body of knowledge on supervised ML algorithms.
Parâmetros de qualidade física e química do eixo central, mesocarpo e semente de jaca submetidos a diferentes processos de secagem

O processo de secagem tem como objetivo a redução do teor de água, contribuindo na conservação, armazenamento e prolongamento da vida útil dos alimentos. Diferentes métodos de secagem influenciam o rendimento e a qualidade do produto. Assim, objetivou-se observar a influência da secagem em estufa e forno de micro-ondas nas propriedades físicas e químicas dos resíduos de jaca. As matérias-primas foram reaproveitas das jacas adquiridas no sítio Bujari, Cuité, PB. Eixo central, mesocarpo e semente foram secos a 60 °C por 300, 360 e 300 min, respectivamente. A rampa de aquecimento em forno de micro-ondas foi de 3 ciclos de 5 min, potência de 100% e 40 g de amostra. Os dois métodos de secagem ocasionaram a concentração do teor de resíduo mineral, sólidos solúveis totais e proteínas. Entretanto, houve redução no teor de água, atividade de água e pH, aumentando a estabilidade das farinhas e, consequentemente, a vida útil. Na secagem em forno micro-ondas, a concentração proteica foi de 2,14, 5,33 e 1,45 vezes para o eixo central, mesocarpo e semente, respectivamente, em relação aos resíduos in natura. As farinhas elaboradas podem ser consideradas fontes de diferentes minerais. A secagem em forno de micro-ondas foi considerada mais eficiente na redução do teor de água, tempo de secagem e qualidade do produto desidratado. O uso de resíduos de jaca e a transformação em farinhas com valor agregado é importante para a sustentabilidade e o meio ambiente, uma vez que reduz perdas de alimentos, desperdícios e impacto ambiental.
Research on Forecast of Macroeconomic Indicators Based on Multiobjective Optimization

In recent years, with China’s economic development entering a new normal, the total scale and complexity of economic development have increased unprecedentedly, and the requirements of government management and regulation of the economy are getting higher and higher. Traditional management concepts, methods, and tools are difficult to meet the needs of the new situation. Therefore, using computer science and technology to fully consider the correlation between various industries and explore new laws of economic operation under the new normal can provide new technical support for promoting the precision of government governance. In previous studies, Most of them take statistics and econometrics as the theoretical basis of macroeconomic decision-making research. This study is based on the analysis of the relationship between the macroeconomic indicators, the establishment of forecasting models to predict the trend of the macroeconomic indicators, and according to the relationship between various economic indicators to build a multiobjective optimization problem, through the multiobjective optimization algorithm to obtain optimal data for the government decision-making basis. In the research process, we focus on solving the problem of prediction overfitting caused by small samples of economic index data and high feature dimension of samples and how to balance the convergence and diversity of solution set in high-dimensional multiobjective optimization problems. In view of the above problems, we propose two economic index forecasting models to solve a variety of fitting problems. On the premise of optimizing space decomposition, an adaptive generation strategy based on inflection point and center point is proposed, and an adaptive solution set selection strategy based on included angle, inflection point, and strong dominance relationship is proposed to balance the convergence and diversity of the multiobjective optimization algorithm.
Treatment of alfalfa silage with chitosan at different levels
to determine chemical, nutritional, fermentation,
and microbial parameters

Chitosan is a biodegradable, antimicrobial, antifungal polysac-charide, thus used as an additive in different industries. Effects of chitosan supplementations on silage quality traits of alfalfa were investigated in the present study. Chitosan was supplemented into alfalfa silages at four different levels: 0% – CONT group; 0.5% – CHTS0.5 group; 1% – CHTS1.0 group; and 2% – CHTS2.0 group. Neutral detergent fibre (NDF) and neutral detergent insoluble crude protein (NDICP) values increase in CHTS 2.0 group ( P < 0.05). Lactic acid and butyric acid contents decreased ( P < 0.05), acetic and propionic acid contents increased with chitosan treatments. On the day of opening the silages, mould production was not encountered, and yeast production decreased in chitosan-supplemented groups. Excessive yeast production was encountered, but mould development was not seen in chitosan-supplemented groups 5 days after opening the silages. Silage pH values increased with chitosan treatments ( P < 0.05). So, it can be concluded that chitosan negatively influenced fermen tation quality of alfalfa silage, but reduced mould and clostridial development.
Breast Radiotherapy after Oncoplastic Surgery—A Multidisciplinary Approach

Simple Summary This article aims to review and summarize the current evidence for the role of oncoplastic breast surgery and the implications this may have on other therapies, such as radiotherapy and chemotherapy. Abstract Oncoplastic breast surgery encompasses a range of techniques used to provide equitable oncological outcomes compared with standard breast surgery while, simultaneously, prioritizing aesthetic outcomes. While the outcomes of oncoplastic breast surgery are promising, it can add an extra complexity to the treatment paradigm of breast cancer and impact on decision-making surrounding adjuvant therapies, like chemotherapy and radiotherapy. As such, early discussions at the multidisciplinary team meeting with surgeons, medical oncologists, and radiation oncologists present, should be encouraged to facilitate best patient care.
An isolation‐enhanced quad‐element antenna using suspended solid wires for LTE small‐cell base stations

This paper presents a multiple‐input‐multiple‐output (MIMO) antenna that has four‐unit elements enabled by an isolation technique for long‐term evolution (LTE) small‐cell base stations. While earlier studies on MIMO base‐station antennas cope with either a lower LTE band (698–960 MHz) or an upper LTE band (1710–2690 MHz), the proposed antenna meets the full LTE specification, yet it uses the maximum number of unit elements to increase channel capacity. The antenna configuration is optimized for good impedance matching and high radiation efficiency. In particular, as the spacing between unit elements is so small that severe mutual coupling occurs, we propose a simple structure with extremely low costs to enhance the isolation. By using suspended solid wires interconnecting the position having strong coupled current of two adjacent elements, an isolation enhancement of 37 dB is achieved. Although solid wires inherently aim at direct‐current applications, this work successfully employs such a low‐cost technique to microwave antenna development. Experimental results have validated the design guidelines and the proposed configuration, showing that antenna performances including impedance matching, isolation, radiation features, signal correlation, and channel capacity gain are highly desired for LTE small‐cell base stations.