Miracle-dz/UniFAR-FTUs huggingface dataset:
First 24-Hour Potassium Concentration and Variability and Association with Mortality in Patients Requiring Continuous Renal Replacement Therapy in Intensive Care Units: A Hospital-Based Retrospective Cohort Study

Serum potassium (K+) levels between 3.5 and 5.0 mmol/L are considered safe for patients. The optimal serum K+ level for critically ill patients with acute kidney injury undergoing continuous renal replacement therapy (CRRT) remains unclear. This retrospective study investigated the association between ICU mortality and K+ levels and their variability. Patients aged >20 years with a minimum of two serum K+ levels recorded during CRRT who were admitted to the ICU in a tertiary hospital in central Taiwan between January 01, 2010, and April 30, 2021 were eligible for inclusion. Patients were categorized into different groups based on their mean K+ levels: <3.0, 3.0 to <3.5, 3.5 to <4.0, 4.0 to <4.5, 4.5 to <5.0, and ≥5.0 mmol/L; K+ variability was divided by the quartiles of the average real variation. We analyzed the association between the particular groups and in-hospital mortality by using Cox proportional hazard models. We studied 1991 CRRT patients with 9891 serum K+ values recorded within 24 h after the initiation of CRRT. A J-shaped association was observed between serum K+ levels and mortality, and the lowest mortality was observed in the patients with mean K+ levels between 3.0 and 4.0 mmol/L. The risk of in-hospital death was significantly increased in those with the highest variability (HR and 95% CI = 1.61 [1.13–2.29] for 72 h mortality; 1.39 [1.06–1.82] for 28-day mortality; 1.43 [1.11–1.83] for 90-day mortality, and 1.31 [1.03–1.65] for in-hospital mortality, respectively). Patients receiving CRRT may benefit from a lower serum K+ level and its tighter control. During CRRT, progressively increased mortality was noted in the patients with increasing K+ variability. Thus, the careful and timely correction of dyskalemia among these patients is crucial.
Study of the Efficacy of Moringa Leaf Extract as an Insecticide against White Fly and Aphids Insects

In this study, we demonstrate the effect of plant extracts on whitefly and aphid’s insects that are economically harmful to crops and plants in greenhouse. A laboratory experiment was carried out to study the effect of four concentrations (0.5, 1.0, 2.0 and 3.0 g/l) of the alcoholic extract of the Moringa plant on whitefly and aphid’s insects. The results showed that the concentration of 3 g/l was significantly superior to the other concentrations used in the experiment, achieving percentage mortality rates of 95% in the nymph’s stage, where the account of insects decreased from 100 live insects before spraying to 5 live insects only after 72 hours of treatment with this concentration. In addition, the percentage mortality rate at the adult stage reached 91%, in which the counts of live insects decreased from 100 live insects before spraying to 9 insects after spraying with this concentration, where the rates of increase in the mortality efficiency rates reached at a concentration of 3 g/l compared to the other concentrations and at the nymph stage (13.09, 35.71, 50.79%), respectively, while the increase rates were at the nymph stage of aphids (16.25, 34.78, 47.61%), respectively. Whereas, the concentration of 0.5 g/l was the least effective in average efficiency of the concentrations used in the experiment in controlling the target insect, where it achieved a lower value of mortality rate, recording remarkable decrease, which reached at the nymphs and adults stages of whitefly and aphids insects (63, 60, 63, 61%), respectively. The chemical examinations for the detection of the plant extract content from the active compounds showed that it contains tannins, glycosides, phenols, resins, carbohydrates, saponins, alkaloids and terpenes.
A 5.91–8.94GHz phase‐locked loop in 65 nm CMOS for 5G applications

A low‐noise fully‐integrated charge‐pump phase‐locked loop (CPPLL) for 5G applications is presented in this letter. The PLL architecture includes a phase and frequency detector (PFD), a charge pump (CP), a low‐pass filter (LPF), a voltage‐controlled oscillator (VCO), and a programmable divider. To achieve low phase noise, class‐C VCO, TSPC logic, and other methods are employed in the PLL circuit design. Fabricated in 65 nm technology, the PLL measures a tuning range of 5.91–8.94 GHz. The minimum and maximum measured phase noise are −125 dBc/Hz and −116.6 dBc/Hz @1 MHz. The size of CPPLL core area is 0.8 mm by 0.95 mm without the pads while having a 50‐mW power consumption.
Robust Soil Water Potential Sensor to Optimize Irrigation in Agriculture

Extreme weather phenomena are on the rise due to ongoing climate change. Therefore, the need for irrigation in agriculture will increase, although it is already the largest consumer of water, a valuable resource. Soil moisture sensors can help to use water efficiently and economically. For this reason, we have recently presented a novel soil moisture sensor with a high sensitivity and broad measuring range. This device does not measure the moisture in the soil but the water available to plants, i.e., the soil water potential (SWP). The sensor consists of two highly porous (>69%) ceramic discs with a broad pore size distribution (0.5 to 200 μm) and a new circuit board system using a transmission line within a time-domain transmission (TDT) circuit. This detects the change in the dielectric response of the ceramic discs with changing water uptake. To prove the concept, a large number of field tests were carried out and comparisons were made with commercial soil water potential sensors. The experiments confirm that the sensor signal is correlated to the soil water potential irrespective of soil composition and is thus suitable for the optimization of irrigation systems.
Towards strategic Kriegspiel play with opponent modeling (Extended Abstract)

Kriegspiel is a chess variant belonging to the family of invisible chess that encompasses partially observable variants of the popular game. Playing Kriegspiel is difficult, first, because the player needs to maintain a belief over all possible board configurations. Second, the player needs to select his move, given his belief about the board configuration and given the likely responses of the opponent. Predicting the likely responses is crucial and has a long tradition in minimax approaches to fully observable games. Minimax assumes that the players are rational and have opposing preferences, which is common knowledge. 1 Further, minimax is applicable only to fully observable games. In partially observable games one needs to model not only the opponent’s preferences, but also the opponent’s belief about the board configuration, and possibly his belief about the original player. Further, the opponent’s level of expertise may also be in question in realistic settings. Our approach is based on interactive partially observable Markov decision process [2] (I-POMDPs). Like POMDPs, I-POMDPs provide a framework for sequential planning. However, they generalize POMDPs to multi-agent settings by including the models of the other agent in the state space. The models are used to form an informed prediction of the other agent’s actions, which is then used during the move selection. Given the complications of maintaining the beliefs over the board configurations in Kriegspiel, the need to include the possible models of the other player further adds to the difficulty. We argue that without opponent modeling some important aspects of the game are necessarily neglected. In particular, without modeling the state of belief of the opponent the impact of moves which have the effect of supplying the opponent with information cannot be taken into account. As should be expected, I-POMDPs reduce to classical POMDPs if there are no other agents in the environment. One of the obvious sources of complexity of solving IPOMDPs, apart from complexity inherent in POMDPs, is the need for considering all possible models of the opponent, and, if further levels of nesting are used, all possible models the opponent may have of the original agent, and so on. This 1 We should remark that common knowledge is a very strong,
Confirmation of a Phenotypic Entity for TSPEAR Variants in Egyptian Ectodermal Dysplasia Patients and Role of Ethnicity

Ectodermal dysplasia (ED) are hereditary disorders characterized by the disturbance of the ectodermal development of at least two of four ectodermal tissues: teeth, hair, nails and sweat glands. Clinical classification of ED is challenged by overlapping features, variable expressivity, and low number of patients, hindering full phenotypic spectrum identification. Disease-causing variants in elements of major developmental pathways, e.g., Ectodysplasin/NFκB, Wnt, and Tp63 pathways, have been identified in fewer than half of ED phenotypes. Whole-exome sequencing (WES) was performed for ten Egyptian ED patients presenting with tooth agenesis, normal sweating, scalp hypotrichosis, and sharing characteristic facial features. WES was followed by in silico analysis of the effects of novel detected genetic variants on mRNA and protein structure. The study identified four novel rare pathogenic and likely pathogenic TSPEAR variants, a gene which was recently found to be involved in ectodermal organogenesis. A novel in-frame deletion recurred in eight patients from six unrelated families. Comparing our cohort to previously reported TSPEAR cohorts highlighted the influence of ethnicity on TSPEAR phenotypic affection. Our study expands the clinical and mutational spectrum of the growing TSPEAR associated phenotypes, and pinpoints the influence of WES and in silico tools on identification of rare disease-causing variants.
IRAS 07027-7934: a probable new [WC11] star

La source IRAS 07027-7934 possede un spectre nebulaire ainsi que des raies d'emission de C II et C III superposees sur un continuum faible. Les caracteristiques optiques et IR suggerent que cette source est un nouveau membre de la classe des nebuleuses planetaires avec des etoiles centrales froides de type Wolf-Rayet.
Numerical Methods for Model Reduction of Time-Varying Descriptor Systems

Science and technology have profoundly influenced the course of human civilization on earth and opened a new horizon of enormous possibilities in various fields of application. Almost all technological applications require a solid understanding of processes, components, and the physical and dynamical features of the concerned systems. Mathematical models are the key towards representing our knowledge and understanding of dynamical systems. In most of those applications, such models become extremely huge and complex and sometime impossible to handle for the purpose of simulation, analysis or control system design. A solution to simplify the preceding task in both fields of simulation and system analysis is to find a low order approximation of the original high order complex model that still preserves the input-output behavior of the original complex model as good as possible. This is the basic concept of model reduction. This dissertation concerns the model reduction of linear periodic descriptor systems both in continuous and discrete-time case. Linear periodic descriptor systems represent a broad class of time evolutionary processes in micro-electronics and circuit simulation. They are suitable models for several natural as well as man-made phenomena, and have applications in modeling of periodic time-varying filters and networks, multirate sampled-data systems, circuit simulation, micro-electronics, aerospace realm, control of industrial processes and communication systems. In this dissertation, mainly the projection based approaches are considered for model order reduction of linear periodic time varying descriptor systems. Krylov based projection method is used for large continuous-time periodic descriptor systems and balancing based projection technique is applied to large sparse discrete-time periodic descriptor systems to generate the reduce systems. For very large dimensional state space systems, both the techniques produce large dimensional solutions. Hence, a recycling technique is used in Krylov based projection methods which helps to compute low rank solutions of the state space systems and also accelerate the computational convergence. The outline of the proposed model order reduction procedure is given with more details. The accuracy and suitability of the proposed method is demonstrated through different examples of different orders and
Role of general anesthetic agents in postoperative nausea and vomiting: A review of literature

Postoperative nausea and vomiting (PONV) is considered to be the most unpleasant experience associated with surgery and is believed to be one of the most common reasons for poor patient satisfaction in the postoperative period. It also results in prolonged hospitalization and increased use of resources such as intravenous fluids and drug supplements along with prolonged medical attention, all of which have psychological and financial implications. In addition to this, PONV can result in aspiration, laryngospasm, dehydration, electrolyte disturbances, gastric bleeding, increased intracranial pressure, increased intraocular pressure, and wound dehiscence particularly when the surgical intervention is performed through an intraoral approach. It is a well-known fact that there are many etiological factors as well as predisposing factors for PONV. Hence, this review is intended to evaluate as an individual factor what the role was played by the anesthetic agents used for GA in the incidence of PONV.
Validity and Reliability of the Korean Version of the Holistic Nursing Competence Scale

This methodological study aimed to verify the validity and reliability of the Korean version of the Holistic Nursing Competence Scale (HNCS), which comprises five dimensions and 36 items. The English version of the HNCS was forward and backward translated and administered to 251 participants with more than a year of work experience in a general hospital. Data were analyzed using SPSS WIN 24.0(Chicago, IL, USA), and AMOS program was used for confirmatory factor analysis. Additionally, the “Task Performance Evaluation Instrument for Clinical Nurses” was used for concurrent validity. Reliability assessed using Cronbach’s α was 0.969. Convergent, discriminant, and concurrent validity were good. Average variance extracted and construct reliability ranged from 0.845 to 0.932 and 0.980 to 0.987, respectively. The model was suitable with the chi-square value being 1216.563 (df = 584, p < 0.001), and Q value being less than three. Goodness-of-fit index, root mean square residual, and root mean square error of approximation were 0.784, 0.066, and 0.066, respectively. Moreover, comparative fit index, Tucker–Lewis index, and incremental fit index were 0.913, 0.906, and 0.913, respectively. Thus, this study verified the validity and reliability of the Korean version of the HNCS. Our findings suggest that the scale is helpful in measuring and developing the holistic nursing competence of clinical nurses.
Neuroprotective effects of a 40% ethanol extract of the black walnut bark (Juglans nigra L.)

Introduction: Neuroprotection is a promising area of adjuvant therapy of ischemic brain lesions. At the same time, among potentially effective neuroprotectors, herbal remedies are distinguished due to their high efficiency and safety of use. In this work, some aspects of the neuroprotective effect of 40% ﻿ethanol﻿ extract of black walnut bark were investigated in comparison with its major component ﻿juglone﻿. Materials and methods: The work was performed on male Wistar rats, which were simulated with cerebral ischemia by irreversible occlusion of the middle cerebral artery. The acute toxicity of the extract was preliminarily evaluated. During the work, the following parameters were determined: changes in the behavior of animals in the Morris water maze, cerebral blood flow, brain necrosis zone area, the activity of mitochondrial complexes, citrate synthase activity, lactic, pyruvic, and ATP concentrations. The activity of the studied extract was compared with ﻿juglone﻿ in a concentration of 1 mg/kg (per os). Discussion: The study showed that the use of black walnut bark extract in conditions of cerebral ischemia contributed to an increase in the activity of mitochondrial complexes I-V, citrate synthase, which in turn led to the normalization of aerobic-anaerobic metabolism reactions. The increase in the activity of respiratory complexes is probably mediated by the antioxidant properties of ﻿juglone﻿, which is a major component of the test extract of black walnut bark. Conclusion: Thus, the test extract can be a potentially effective neuroprotective agent and requires further study.
ANALISIS PERBANDINGAN KINERJA KEUANGAN PERUSAHAAN SEBELUM DAN SESUDAH AKUISISI (STUDY PADA PERUSAHAAN PENGAKUISISI YANG TERDAFTAR DI BEI PERIODE 2000-2011)

This research is to analyze the company's financial performance comparison before and after the acquisition. Is there a significant difference or not, and the difference is increased or decreased. Financial performance here is measured by the ratio of ROI, ROE, DER, TATO, CR, and EPS. This study takes population from all company that acquisition activity in period 2000-2011. The samples in this study using purposive sampling method, andÂ and obtained a sample of 17 companies in the period 2000-2011, with the appropriate criteria have been determined, the ratio of data obtained from the Indonesian Capital Market Directory (ICMD). The analysis used to test the hypothesis of this research is quantitative analysis with Wilcoxon Signed Rank Test and Manova. Based on descriptive statistics, changes in the average value (mean) of the ratio of DER, tato and EPS have increased, but the results are not strong enough to prove the existence of significant differences in financial performance as measured by these ratios. The Test results using the Wilcoxon Signed Rank Test showed that there was no significant difference for all ratios after the acquisition, and it is also supported by the results of testing with Manova.
Teaching Statistics and Data Analysis with R

Abstract We developed an interactive online textbook that interleaves R programming activities with text as a way to facilitate students’ understanding of statistical ideas while minimizing the cognitive and emotional burden of learning programming. In this exploratory study, we characterize the attitudes and experiences of 672 undergraduate students as they used our online textbook as part of a 10-week introductory course in statistics. Students expressed negative attitudes and concerns related to R at the beginning of the course, but most developed more positive attitudes after engaging with course materials, regardless of demographic characteristics or prior programming experience. Analysis of a subgroup of students revealed that change in attitudes toward R may be linked to students’ patterns of engagement over time and students’ perceptions of the learning environment.
Emotion Recognition using BiLSTM Classifier

Human emotions are play a vital role in work locations and clinical studies. Speech emotion recognition (SER) is easy for humans and it is bit difficult for machines like computers and robots. These systems are unable to identify emotion of a user and are unable to react to their feelings. To improve human-machine interaction, a deep learning (DL) based approach is proposed. This paper presents a SER system using Bidirectional Long Short-Term Memory (Bi-LSTM). Features such as Gamma tone & Mel-frequency cepstral coefficients (GTCC & MFCC) are extracted for SER. Ability of proposed DL approach is observed at different noisy conditions, testing rates and with EMO-DB data set.
Scaling properties of viscous fingering

We present a study of viscous fingering using the Volume Of Fluid method and a central injection geometry, assuming a Laplacian field and a simple surface tension law. As in experiments we see branched structures resulting from the Saffman-Taylor instability. We find that the area $A$ of a viscous-fingering cluster varies as a simple power law $A \sim L^{\alpha}$ of its interface length $L$. Our results are compared to previously published simulations in which the viscosity of the invading fluid is vanishing. We find differences in exponent $\alpha$ and in the appearance of detached droplets and bubbles.
Skin Lesion Segmentation Based on Edge Attention Vnet with Balanced Focal Tversky Loss

Segmentation of skin lesions from dermoscopic images plays an essential role in the early detection of skin cancer. However, skin lesion segmentation is still challenging due to artifacts such as indistinguishability between skin lesion and normal skin, hair on the skin, and reflections in the obtained dermoscopy images. In this study, an edge attention network (ET-Net) combining edge guidance module (EGM) and weighted aggregation module is added to the 2D volumetric convolutional neural network (Vnet 2D) to maximize the performance of skin lesion segmentation. In addition, the proposed fusion model presents a new fusion loss function by combining balanced binary cross-entropy (BBCE) and focal Tversky loss (FTL). The proposed model has been tested on the ISIC 2018 Task 1 Lesion Boundary Segmentation Challenge dataset. The proposed model outperformed the state-of-the-art studies as a result of the tests.
Rancang Bangun Modul IoT untuk Pembelajaran Dasar di Laboratorium di Jurusan Teknik Elektro Universitas Lampung

The employment sector is the one that has been hit the worst by the consequences of Revolution 4.0 in Indonesia. The Internet of Things is one area that human resources, particularly students in the Electrical Engineering Department, must improve (IoT). As a result, IoT learning media was developed in the laboratory, where the current IoT modules are insufficient. The goal of this research is to provide students a fundamental understanding of the Internet of Things. Arduino and ESP8266 are used in this IoT module. The Blynk and ThinkSpeak platforms are used to connect to an internet network based on web services. In this module, you can perform three different types of experiments. The first is the ThingSpeak Application for Temperature and Humidity Monitoring. The temperature in the room was 23°C, with a humidity level of 56%. The second method is to use the Blynk application to measure distance using an ultrasonic sensor. The comparison of measurements on the LCD and the Blynk application yielded results that were consistent with measurements taken using a ruler. The third option is to use the Blynk App to control water volume. As an automatic switch on the tank, a relay module is used in this experiment. The pump will turn on when the water volume is less than 100 liters and turn off when the water volume reaches 265 liters. Finally, this module can be used as a basic learning materials in the Laboratory of the Department of Electrical Engineering, Faculty of Engineering, University of Lampung.
Gatekeepers in Regional Networks of Innovators

The internal density of a local network is said to increase the region-specific knowledge-stock and might lead to a comparative advantage. However, it might also lead to a lock-in situation, if local trajectories are directed towards inferior solutions. Accordingly it is argued that successful clusters are characterised by the existence of gatekeepers, i.e. actors that generate novelty by drawing on local and external knowledge. We attempt to answer questions related to the role and characteristics of gatekeepers within regional innovation systems by applying social network analysis based on patent data for four East-German regions. The regional networks appear to be significantly different with respect to the overall degree of interaction and with respect to their relative outward orienta- tion. Concerning the characteristics of gatekeepers, we find that size does not play the major role for being a gatekeeper. It is rather absorptive capacity that matters for gatekeepers. It also shows that public research organisations serve the functions of a gatekeeper to a higher degree than private actors.