Miracle-dz/UniFAR-FTUs huggingface dataset:
The Association between Nutritional Status and Length of Hospital Stay among Patients with Hypertension

Background: Nutritional status is related to the prognosis and length of hospital stay (LOS) of patients with hypertension (HT). This study aimed to assess how nutritional status and body mass index (BMI) affect LOS for patients with hypertension. Method: We performed a retrospective analysis of 586 medical records of patients who had been admitted to the Institute of Heart Diseases of the University Clinical Hospital in Wroclaw, Poland. Results: A total of 586 individuals were included in the analysis. Individuals who were at a nutritional risk represented less than 2% of the study population, but more than 60% were overweight or obese. The mean BMI was 28.4 kg/m2 (SD: 5.16). LOS averaged 3.53 days (SD = 2.78). In the case of obese individuals, hospitalisation lasted for 3.4 ± 2.43 days, which was significantly longer than for patients of normal weight. For underweight patients, hospitalisation lasted for 5.14 ± 2.27 days, which was also significantly longer than for those in other BMI categories (p = 0.017). The independent predictors of shorter hospitalisations involved higher LDL concentration (parameter of regression: −0.015) and HDL concentration (parameter of regression: −0.04). Conclusions: The study revealed that with regard to the nutritional status of hypertensive patients, being either underweight or obese was associated with longer LOS. Additional factors that related to prolonged LOS were lower LDL and HDL levels and higher CRP concentrations.
Comparison of Effects from Ultrasound Thawing, Vacuum Thawing and Microwave Thawing on the Quality Properties and Oxidation of Porcine Longissimus Lumborum

The effects of vacuum thawing (VT), ultrasound thawing (UT) and microwave thawing (MT) on the quality, protein and lipid oxidation, internal temperature distribution and microstructure of porcine longissimus lumborum were compared. The results showed that a significant decrease (p < 0.05) in quality compared with those of fresh meat (FM) occurred for all of the thawing samples, especially for the MT samples. Changes in quality of the VT and UT samples were less significant than those of the MT samples. The increases in carbonyl content and TBARS value indicated that proteins and lipids in the thawing samples were oxidized. The decreases in uniform degrees of internal temperature distributions of muscles from the thawing samples were analysed by infrared thermography. Scanning electron microscopy images showed that the myofibril arrangements of thawing samples were looser than those of the FM samples with compact and ordered structure, which was proven by the obvious increase in the myofibril gap value of the thawing samples.
Data-Mining of In-Situ TEM Experiments: On the Dynamics of Dislocations in CoCrFeMnNi Alloys

High entropy alloys are a class of materials with many signiﬁcant improve-ments in terms of mechanical properties as compared to “classical” alloys. The corresponding structure-property relations are not yet entirely clear, but it is commonly believed that the good mechanical performance is strongly related to dislocation interactions with the complex energy landscape formed due to al-loying. Although in-situ Transmission Electron Microscopy (TEM) allows high-resolution studies of the structure and dynamics of moving dislocations and makes the local obstacle/energy “landscape” directly visible in the geometry of dislocations; such observation, however, are merely qualitative, and detailed three-dimensional analyses of the interaction between dislocations and the energy landscape is still missing. In this work, we utilized dislocations as “probes” for the local energy maxima which play the role of pinning points for the dislocation movement. To this end, we developed a unique data-mining approach that can perform coarse-grained spatio-temporal analysis, making ensemble averaging of a considerable number of snapshots possible. We investigate the eﬀect of pinning points on the dislocation gliding behavior of CoCrFeMnNi alloy during in-situ TEM straining and ﬁnd that (i) the pinning point strength changes when dislocations glide through and (ii) the pinning point moves along the direction close to the Burgers vector direction. Our data-mining method can be applied to dislocation motion in general, making it a useful tool for dislocation research.
Quality, satisfaction and loyalty in the emergency service of public hospitals, from the central zone of Ecuador

This study seeks to analyze in a holistic way the satisfaction of patients who make use of emergency services of public hospitals in the central zone of Ecuador, one of the most sensitive areas which is under constant scrutiny by users and physicians whoever give continuity to the treatment of patients. Through structural equations modeling (SEM) it was evidenced that there is a positive and significant relationship between the quality of service and satisfaction, as well as between the latter and the loyalty of the users. There was no direct relationship between the quality and the loyalty of the patients. These results highlight the importance of these variables for the integral evaluation of the satisfaction and loyalty of the clients of an organization.
Evaluating acoustic signals to reduce avian collision risk

Collisions with human-made structures are responsible for billions of bird deaths each year, resulting in ecological damage as well as regulatory and financial burdens to many industries. Acoustic signals can alert birds to obstacles in their flight paths in order to mitigate collisions, but these signals should be tailored to the sensory ecology of birds in flight as the effectiveness of various acoustic signals potentially depends on the influence of background noise and the relative ability of various sound types to propagate within a landscape. We measured changes in flight behaviors from zebra finches released into a flight corridor containing a physical obstacle, either in no-additional-sound control conditions or when exposed to one of four acoustic signals. We selected signals to test two frequency ranges (4–6 kHz or 6–8 kHz) and two temporal modulation patterns (broadband or frequency-modulated oscillating) to determine whether any particular combination of sound attributes elicited the strongest collision avoidance behaviors. We found that, relative to control flights, all sound treatments caused birds to maintain a greater distance from hazards and to adjust their flight trajectories before coming close to obstacles. There were no statistical differences among different sound treatments, but consistent trends within the data suggest that the 4–6 kHz frequency-modulated oscillating signal elicited the strongest avoidance behaviors. We conclude that a variety of acoustic signals can be effective as avian collision deterrents, at least in the context in which we tested these birds. These results may be most directly applicable in scenarios when birds are at risk of collisions with solid structures, such as wind turbines and communication towers, as opposed to window collisions or collisions involving artificial lighting. We recommend the incorporation of acoustic signals into multimodal collision deterrents and demonstrate the value of using behavioral data to assess collision risk.
Recuperation travel in China: its operating model and opportunities for tourism entrepreneurship

ABSTRACT Employer subsidized ‘recuperation travel’ has emerged in China as a workplace bonus operating predominantly in the public sector. As a novel and emerging tourism model, the potential for recuperation travel could reach as high as 250 million clients, which warrants greater attention from both practitioners and academicians. This paper sheds new insight into recuperation travel in China, through a sentiment analysis of social media posts by both recuperation travel participants and non-participants. The results suggest that most recuperation travel participants (77.6%) expressed positive sentiment, compared with 41.3% of non-participants. This paper identifies and discusses the entrepreneurial opportunities that can be derived from this billion-dollar tourism market.
Towards Holistic Enterprise Modelling: Value Creation Concept in Fractal Enterprise Model (FEM)

: Some researchers argue that traditional applications of enterprise modelling (EM) may provide limited value when performing holistic analysis due to disjoint modelling domains that comprise organizations. Fractal Enterprise Modelling (FEM) is a promising EM approach addressing this issue. FEM uses a modelling technic that articulates an organisational fractal structure of an enterprise, and has been used for representing different practical challenges in organisations. This paper is a part of an ongoing research where FEM is used for a holistic analysis of organizational change associated with a strategy implementation in an organization. Particularly, the paper discusses the application of a previously emerged modelling pattern that was useful for supporting operational decision making. In this paper, it is argued that the same pattern is also useful for representation of a value chain concept that allows to connect a high organisational level to the elements of a lower operational level. The results imply that the usage of this pattern might be beneficial to promote systematic and holistic modelling for business analysis using FEM.
A single item measure of self-control – validation and location in a nomological network of self-control, boredom, and if-then planning

Self-control is a highly adaptive human capacity and research on self-control is booming. To further facilitate self-control research, especially in conditions where time-constraints might render the use of multi-item measures of self-control problematic, a validated time-efficient single item measure would be an asset. However, such a measure has not yet been developed and tested. Here, we address this gap by reporting the psychometric properties of a single item measure of self-control and by assessing its localization within a larger theorized psychometric network consisting of self-control, boredom and if-then planning. In a high-powered (N = 1553) study with paid online workers from the US (Gender: 47.3% female, 51.7% male, 1% other; Age: 40.36 ± 12.65 years), we found evidence for the convergent validity (Brief Self-Control Scale), divergent validity (Short Boredom Proneness Scale and If-Then Planning Scale), and criterion validity (objective and subjective Socio-Economic Status) of the single item measure of self-control (“How much self-control do you have? ”). Network psychometrics further revealed that the single item was part of the self-control subnetwork and clearly distinguishable from boredom and if-then planning, which together with self-control form a larger psychometric network of psychological dispositions that are relevant for orienting goal directed behavior. Thus, the present findings indicate that self-control can be adequately captured with the single item measure presented here, thereby extending the methodological toolbox of self-control researchers by a highly-time efficient measure
Klasifikasi Penyakit Daun Jagung Menggunakan Metode Convolutional Neural Network

Jagung merupakan tanaman pangan utama ketiga setelah padi dan terigu di dunia dan menempati posisi kedua setelah padi di Indonesia. Penyakit tanaman sering kali disebabkan oleh aktifitas atau serangan organism di dalam bagian tubuh tanaman, di luar tubuh, atau di sekitarnya. Penelitian ini bertujuan untuk mengklasifikasikan penyakit daun jagung menggunakan metode convolutional neural network (CNN) dengan arsitektur Resnet 50 dengan optimizer Adam, Nadam dan SGD. Dataset terdapat 4225 citra di pisahkan menjadi 3380 data train, 845 data test. Citra yang digunakan di resize menjadi ukuran 224x224. Pada penelitian ini mendapatkan hasil tingkat akurasi tertinggi untuk arsitektur Resnet 50 dengan menggunakan optimizer Adam didapatkan tingkat akurasi sebesar 98,4%.
Blood Coagulation Time Determination by AC Current Phase Shift Measurement

The phase shift of the AC current resulting from the applied AC potential is one of the important parameters determining the shape of the registered curve in the EIS studies. However, its self-sufficient employment is limited while the Nyquist and Bode diagrams are widely applied in the common EIS analysis so far. In this work a new approach was proposed, tested and applied for rapid and precise blood coagulation time determination, a parameter of a great importance for the diagnosis and monitoring of many diseases. The proposed approach is based on AC current phase shift measurement in respect to the applied AC potential with small amplitude as a self-sufficient blood properties characterizing parameter. A specially developed LabVIEW based virtual instrument was used providing results which relative RSD does not exceed 1.9% in the frequency range from 100 Hz up to 10 KHz.
Semantic Metadata Requirements for Data Warehousing from a Dimensional Modeling Perspective

: The era of big data has brought on new challenges to data warehousing. Emerging architectural paradigms such as data fabric , data mesh , lakehouse and logical data warehouse are promoted as solutions to big data analytics challenges. However, such hybrid environments, aimed at offering universal data platforms for analytics, have schemas that tend to grow in size and complexity and become more dynamic and decentralized, having a drastic impact on data management. Data integrity, consistency and clear meaning are compromised in large architectures where traditional (relational) database principles do not apply. This paper proposes an investigation into semantic metadata solutions in modern data warehousing from a (logical) dimensional modeling perspective. The primary goal is to determine which metadata and types of semantics are required to support automated dimensionalization as it is assumed to be a good approach to integrate data with different modalities. A secondary goal is finding a suitable model to represent such metadata and semantics for both human and computer interpretability and use. The proposal includes a description of the research problem, an outline of the objectives, the state of the art, the methdology and assumptions, the exepected outcome and current stage of the research.
A Context Feature Enhancement Network for Building Extraction from High-Resolution Remote Sensing Imagery

The complexity and diversity of buildings make it challenging to extract low-level and high-level features with strong feature representation by using deep neural networks in building extraction tasks. Meanwhile, deep neural network-based methods have many network parameters, which take up a lot of memory and time in training and testing. We propose a novel fully convolutional neural network called the Context Feature Enhancement Network (CFENet) to address these issues. CFENet comprises three modules: the spatial fusion module, the focus enhancement module, and the feature decoder module. First, the spatial fusion module aggregates the spatial information of low-level features to obtain buildings’ outline and edge information. Secondly, the focus enhancement module fully aggregates the semantic information of high-level features to filter the information of building-related attribute categories. Finally, the feature decoder module decodes the output of the above two modules to segment the buildings more accurately. In a series of experiments on the WHU Building Dataset and the Massachusetts Building Dataset, our CFENet balances efficiency and accuracy compared to the other four methods we compared, and achieves optimality on all five evaluation metrics: PA, PC, F1, IoU, and FWIoU. This indicates that CFENet can effectively enhance and fuse buildings’ low-level and high-level features, improving building extraction accuracy.
FSS superstrate loaded SIW circular cavity-backed cross-shaped slot antenna for wireless applications

In this paper, a low profile circular-shaped cavity-backed substrate integrated waveguide (SIW) antenna is designed and fabricated to operate at 5.38 GHz frequency in the U-NII-2B band in the dominant TM010 mode. A narrow cross-shaped slot is inserted in the ground plane of the parent antenna for radiation purposes. The antenna produces a gain of 4.7 dBi with an impedance bandwidth extending from 5.36–5.42 GHz. The gain of the antenna is augmented to 7.1 dBi through the use of a multi-layered cascaded frequency selective surface (FSS) as a superstrate. Arlon substrate materials are used to fabricate the antenna and frequency selective surface respectively. Parametric studies have been carried out in terms of return loss, antenna gain, and spacing between the antenna and FSS layer to obtain the best antenna results. All the simulation results have been carried out using HFSS v19.0. Both the simulated and the experimentally measured results show alike behavior.
Typhoon-Induced Fragility Analysis of Transmission Tower in Ningbo Area Considering the Effect of Long-Term Corrosion

The purpose of this paper was to investigate the influence of long-term corrosion on the deterioration of wind resistance of a steel transmission tower during its service life. An analytical model for predicting the long-term corrosion depth of carbon steel was established, and the corrosion depth of carbon steel in the Ningbo area was predicted based on the local atmospheric environment data. With the help of typhoon full-track simulation and wind field simulation technology, a joint probability distribution model of multidirectional extreme wind speeds was constructed using the t-Copula function to determine the typhoon climate of the transmission tower site. Finite element models of the ZM4 cathead transmission tower under 30/60/90 corrosion years were then established, respectively, according to the predicted corrosion depth of carbon steel in Ningbo. Three damage modes, i.e., minor damage, moderate damage and severe damage, corresponding to the transmission tower under wind loads, were defined, and pushover analyses were used to determine the limit values of each damage mode so as to obtain the typhoon-induced fragility curves of the transmission tower within 30/60/90 corrosion years. The results show that the increase in corrosion age leads to a deterioration in the nominal mechanical properties of the transmission tower components, making the damage probability to the transmission tower increase. Under the typhoon wind loads of a 50-year return period in the most unfavorable wind direction in Ningbo, the probability of moderate damage of the tower is within 10% and the probability of minor damage is controlled between 10% and 40%.
Kızılırmak Nehrinde Bazı İstasyonlardaki Akımların Trend Analizi

Bu calismada, Şen (2012) ve Şen (2015) tarafindan onerilen oldukca yeni bir trend metodu, Kizilirmak havzasindan secilen Şefaatli, Kuylus, Salur Koprusu ve Bulakbasi akim gozlem istasyonlarinda aylik olarak olculen akim verilerine uygulanmistir. Ayni verilere Mann-Kendall trend testi de uygulanarak sonuclar tartisilmistir. Mann-Kendall testine gore %95 guven araliginda Kuylus ve Bulakbasi istasyonlarinda trend olmayip Şefaatli ve Salur Koprusu istasyonlarinda azalan bir trend gorulmustur. Şen trend testine gore ise her bir istasyon icin dusuk, orta ve yuksek akim degerlerinde farkli trendler gozlenmistir. Neticede, yeni onerilen Şen metodunda, ozellikle gorsel olarak veri degerlendirme asamasinda tum araliklardaki trendlerin yorumlanabilmesi onemli bir avantaj olarak gorulmustur.
Mauritia vinifera Mart Substrates and Nitrogen Doses in Acacia mangium Willd Growth

The objective of this study was to evaluate the effect of the combination of a substrate formulated with decomposed buriti stem (Mauritia vinifera Mart.) and nitrogen doses in the production of Acácia mangium Willd seedlings. A completely randomized design was used in a 3 × 5 factorial scheme, being the factors constituted of substrates formulated from decomposed buriti stem (DBS) mixed with dystrophic yellow oxisol in three proportions (0; 25 and 50%) and nitrogen doses (0; 100; 200; 300 and 400 mg dm-3) applied in cover. After 60 days from the emergency, it was made the following evaluations: Plant Height (PH), stem diameter (SD), internodes number (IN), dry mass of the shoot part (DMA), length and dry mass of the roots, robustness quotient through stem height/diameter relation, roots/dry mass relation and Dickson Quality Index (DQI). The multivariate analysis of variance showed a significant difference (p < 0.01) among averages vectors of treatments. The grouping analysis for the evaluated treatments allowed the division into four distinct groups. In the bi-dimensional plane formed by the first two canonical variables (Can.1 and Can.2) that withheld 99,47% of the total variance contained in the nine original variables, it is observed that the group II of treatments, composed of substrates formulated with 50% of soil + 50% of DBS supplemented with the doses of 200, 300 and 400 mg dm-3 of nitrogen, has provided a greater initial growth of A. mangium plants, as stated by the highest averages in all evaluated variables.
Pairing Fieldworkers with Patrol Officers: A Study of Supervising Officers’ Selections

Qualitative, field-based studies of police tend not to rely on random sampling, but, instead, navigate a well-trodden path to cases. The first step is gaining a supervising officer’s (SO) consent to study their department, and the last step is convincing patrol officers (POs) to reveal what they normally do and think. Also, there is an indispensable intermediary step in which fieldworkers are paired with particular POs, a choice sometimes left up to SOs. Despite its importance, the basis on which such couplings are made is not well documented, much less understood. Thus, this article analyzes qualitative data obtained from nine SOs about why they assigned particular POs to accompany the first-author on ride-alongs. The SOs largely explained their assignments as meant to help the research by placing the fieldworker with POs who would yield more data in terms of quantity, variety, and ‘better’ answers. The article concludes by discussing the findings’ broader implications.
Social Bots Detection: A Method based on a Sentiment Lexicon Learned from Messages

: The use of bots on social networks for malicious purposes has grown significantly in recent years. Among the last generation techniques used in the automatic detection of social bots, are those that take into account the sentiment existing in the messages propagated on the network. This information is calculated based on sentiment lexicons with content manually annotated and, hence, susceptible to subjectivity. In addition, words are analyzed in isolation, without taking into account the context in which they are inserted, which may not be sufficient to express the sentiment existing in the sentence. With these limitations, this work raises the hypothesis that the automatic detection of social bots that considers the sentiment characteristics of the words of the messages can be improved if these characteristics were previously learned by machines from the data, instead of using manually annotated lexicons. To verify such hypothesis, this work proposes a method that detects bots based on Sentiment-Specific Word Embedding (SSWE), a lexicon of sentiment learned by a homonymous recurrent neural network, trained in a large volume of messages. Preliminary experiments carried out with data from Twitter have generated evidence that suggests the adequacy of the proposed method and confirms the raised hypothesis.