bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ladd’s Syndrome in Newborns
Authors: Zyuzina O. A. 
Published: August 2023

Ladd’s syndrome is a violation of intrauterine intestinal rotation. The midgut remains fixed at one point at the origin of the superior mesenteric artery. As a result, conditions are created for the occurrence of a volvulus around the root of the mesentery and acute strangulation intestinal obstruction develops. Ladd’s syndrome includes three features: a high position of the caecum dome, duodenal hyperfixation, and lack of mesenteric fixation. In newborns, this condition is manifested by acute complete high strangulation intestinal obstruction, up to the development of shock. Examination for suspected Ladd’s syndrome should be comprehensive and include a survey abdominal radiography, abdominal ultrasound, gastric and duodenal radiography with oral contrast, irrigography. The article considers clinical cases of Ladd’s syndrome in newborns at the age of 3 and 5 days of life. Echograms made in B-mode using color Doppler sonography are presented. The high informativeness of ultrasound diagnostics for the detection of this syndrome in newborns with a clinic of bile vomiting is shown. In one of the observed cases, a pathognomonic echographic symptom of midgut volvulus was established (a whirlpool sign). In the second observation, a clearly defined vascular ring was not detected due to 180° torsion, which was subsequently confirmed intraoperatively.
Penerapan Metode Peramalan Double Exponential Smoothing Pada Indeks Harga Konsumen Kota Yogyakarta
Authors: Alivia Ayudhi Asmaradana  , Edy Widodo  
Published: August 2023

Indeks Harga Konsumen atau IHK adaIah sebuah indeks untuk perhitungan rata-rata perubahan harga dari suatu barang dan jasa yang dalam periode waktu tertentu yang dikonsumsi penduduk daIam kurun waktu tertentu. IHK adalah indikator yang digunakan dalam perhitungan infIasi dimana infIasi sangat berperan penting dalam perekonomian. Sehingga perubahan IHK akan mempengarui besar biaya hidup untuk barang dan jasa pada setiap penduduk. Selain itu, terjadinya inflasi atau deflasi dapat diketahui melalui IHK. MakaIah ini dibuat dengan tujuan untuk memberikan gambaran tentang masa depan kepada pemerintah daIam menetapkan kebijakan ke depannya. Data yang digunakan daIam peneIitian ini adalah IHK di Kota Yogyakarta pada bulan Januari 2014 hingga Februari 2022. Data IHK tersebut memilki pola data trend naik dimana data terus mengaIami kenaikan hingga Februari 2022. Namun, pada satu periode yaitu pada Januari 2020, nilai IHK Kota Yogyakarta mengaIami penurunan drastis dikarenakan adanya pandemi Covid-19. Kemudian dilakukan peramalan menggunakan metode DoubIe ExponentiaI Smoothing yang seIanjutnya dicari nilai kesalahan peramalan menggunakan perhitungan Mean Absolute Percentage Error (MAPE). Didapatkan nilai peramalan IHK pada bulan Maret 2022 adalah 109.2964, dengan nilai MAPE sebesar 0.76%. Nilai MAPE tersebut kurang dari 10% artinya dapat dikatakan bahwa peramaIan menggunakan metode Double Exponential Smoothing baik dan dapat digunakan.
Analisis Regresi Berganda pada Faktor-Faktor yang Mempengaruhi Kinerja Fisik Preservasi Jalan dan Jembatan Di Provinsi Sumatera Selatan
Authors: PRASMONO AMIMAH SHABRINA PUTRI , Atina Ahdika  
Published: August 2023

Maksud penelitian ini ialah menganalisis faktor-faktor yang mempengaruhi Kinerja Fisik Preservasi Jalan dan Jembatan di Provinsi Sumatera Selatan. Dalam penelitian ini terdapat variabel rencana fisik dan realisasi fisik yang menjadi variabel independen, dan variabel kinerja fisik Balai Besar Pelaksanaan Jalan Nasional (BBPJN) Provinsi Sumatera Selatan merupakan variabel dependen. Tipe penelitian yang dipakai ialah penelitian deskriptif dengan pendekatan korelasi. Tipe data yang dipakai ialah data sekunder berbentuk Laporan Progress Mingguan Preservasi Jalan dan Jembatan Wilayah IA (Sumatera) TA 2021 yang diperoleh dari Subdirektorat Preservasi Jalan dan Jembatan Wilayah IA. Metode analisis data yang diterapkan ialah analisis Regresi Linear Berganda. Didapatkan hasil pengolahan data dari regresi linear berganda yaitu. Dari persamaan yang diperoeh bahwa variabel Rencana Fisik dan Realisasi Fisik memiliki pengaruh yang signifikan dalam mempengaruhi Kinerja Fisik BBPJN Sumatera Selatan Tahun 2021. Didapatkan koefisien determinasi sebesar 0.9096. Artinya, variabel rencana fisik dan realisasi fisik mampu menjelaskan variabel kinerja fisik sejumlah 90.69%, sementara itu sisanya sejumlah 9.31% diterangkan sama faktor lain yang tidak dituturkan dalam model.
Assessing the Influence of Fracture Networks on Gas-Based Enhanced Oil Recovery Methods
Authors: Kharrat Riyaz , Alalim Nouri , Ott Holger 
Published: August 2023

Numerous reservoirs that play a significant role in worldwide petroleum production and reserves contain fractures. Typically, the fractures must form a connected network for a reservoir to be classified as naturally fractured. Characterizing the reservoir with a focus on its fracture network is crucial for modeling and predicting production performance. To simplify the solution, dual continuum modeling techniques are commonly employed. However, to use continuum-scale approaches, properties such as average aperture, permeability, and matrix fracture interaction parameters must be assigned, making it necessary to improve fracture depiction and modeling methods.
This study investigates a fractured reservoir with a low matrix permeability and a well-connected fracture network. The focus is on the impact of the hyrachical fracture network on the production performance of gas-based enhanced oil recovery methods. The Discrete Fracture Model (DFN) was utilized to create comprehensive two-dimensional models for three processes: Gas Injection (GI), Water Alternating Gas (WAG), and Foam Assisted Water Alternating Gas (FAWAG). Moreover, dimensionless numbers were employed to establish connections between properties across the entire fracture hierarchy, spanning from minor to major fractures and encompassing the fracture intensity.
The results indicate that the FAWAG is more sensitive to fracture types and networks than the WAG and GI processes. Hence, the sensitivity of the individual EOR method to the fracture network requires a respective depth of description of the fracture network. However, other factors, such as reservoir fluids properties and fracture properties, might influence the recovery when the minor fracture networks are excluded.
This study has determined that, among the enhanced oil recovery (EOR) techniques examined, the significance of the hyrachical depth of fracture networks diminishes as the ratio of major (primary fracture) aperture to the aperture of medium and minor fractures increases. Additionally, the impact of the assisted-gravity drainage method was greater with increased reservoir height; however, as the intensity ratio increased, the relative importance of medium and minor fracture networks decreased.
Digital Literacy Skills and System Quality as Predictors of Learning Management Systems Use of Postgraduate Students in Ibadan Nigeria
Authors: Adegbore Adebayo Muritala , Tella Adeyinka , Jide Ayoola 
Published: August 2023

<p class="Default"><span lang="EN-US">The use of learning management systems (LMS) was observed to be weak among students in Nigeria. Therefore, digital literacy skills and system quality were used as predictors to predict LMS use among postgraduate students in universities in Ibadan, Nigeria. A survey design of the correlational type was adopted. At the same time, the population of the study comprised all the 4,750 postgraduate students of two universities in Ibadan, Nigeria, and 328 postgraduate students were drawn using a multi-stage sampling technique. The instrument adopted for data collection was a questionnaire which had three sections. The questionnaire return rate was 316 copies, representing a 96.3% retrieval rate. Pearson’s Product Moment Correlation Coefficient and multiple regression analysis were conducted to test the null hypotheses at a 0.05 significance level. A significant relationship between digital literacy skills and the use of learning management (r =.319; p &lt; 0.05) was found, while a significant relationship between system quality and the use of learning management systems (r =.501; p &lt; 0.05) was equally established. There is a significant relationship between digital literacy skills and LMS system quality (r =.529; p &lt; 0.05). Furthermore, a joint influence of digital literacy skills and system quality on the use of learning management systems of postgraduate students in universities in Ibadan, Nigeria (F =53.594; R=0.505; p &lt; 0.05) was established. It was recommended that university management and lecturers should ensure the system quality of the LMS type to be adopted must support the convenience of use and have fewer technicalities in its use.</span></p>
The Effect of Adding Prim ary Epoxy on the Corrosion Rate of Low Carbon Steel in 5.25% Calcium Hypochlorite Solution
Authors: Eka Putra Ismet , Hidayat Haleri Echo Yeyen 
Published: August 2023

The corrosion process occurs in almost all materials, especially metals, slowly but surely, which can cause a material to have a limited service life. Corrosion cannot be prevented but the rate can be reduced. One of t he methods to inhibit the effective corrosion rate is by giving epoxy primer treatment. This study aims to examine the effect of adding epoxy primer on the corrosion rate of low carbon steel immersed in a 5.25% Calcium hypochlorite solution. This research was conducted using 27 specimens in 9 vessels, each vessel contained 3 specimens immersed in low carbon steel without treatment, oil paint and epoxy primer. Volume of 1 liter of solution for 1 vessel. The results of this study indicate that the epoxy primer is able to inhibit the corrosion rate well. The reduction in weight of low carbon steel treated with oil paint is much greater than that of untreated low carbon steel using epoxy primer. The lowest corrosion rate was given by applying epoxy primer in 30 days of immersion with an average value of 0.001001695 mpy and the highest corrosion rate without treatment in 15 days of immersion with an average value of 0.005008473 mpy.
Emergent false vacuum decay processes in a two-dimensional electronic crystal: experiment vs. simulations on a noisy superconducting quantum processor
Authors: Vodeb Jaka , Diego Michele , Vaskivskyi Yevhenii , Logaric Leonard , Gerasimenko Yaroslav , Kabanov Viktor , Lipovsek Benjamin , Topic Marko , Mihailovic Dragan 
Published: August 2023

Abstract

Emergent metastability in non-equilibrium systems is a subject that touches everything from the origins of life1 to the quantum nature of the universe2. In condensed quantum matter, a good topical example is the metastability of topologically inhibited self-organization of electronic domains in a correlated electronic crystal in the aftermath of a symmetry-breaking phase transition3. Understanding the dynamics of such systems is crucial for developing new quantum technologies and exploring fundamental aspects of many-body non-equilibrium quantum mechanics. Here, a non-equilibrium state is set up by carrier injection in the quantum material (M), resulting in a domain structure, whose time-evolution is investigated by scanning tunneling microscopy. Demonstrating a new approach to modelling of emergent non-equilibrium quantum behavior, we use an array of 2008 qubits in a programmable noisy superconducting quantum simulator (NSQS) without error correction (P), in which mutual qubit interconnections correspond directly to the electronic interactions on the triangular lattice of the electronic crystal material. The success of the simulations critically depends on both the faithfulness of the model correspondence between the two systems and careful management of the decoherence pathways. Importantly, decoherence of both P and M is driven by noise with a characteristic 1/ν frequency spectrum. The simulations reveal how an emergent false vacuum state arises, describing the time evolution and temperature dependence of the observed electronic domain dynamics of M solely on the basis of microscopic electronic interactions. The parallel experiments demonstrate the potential of NSQSs for studying emergent non-equilibrium dynamics in complex many-body quantum systems.
Development of Machine Learning Models for Studying the Premixed Turbulent Combustion of Gas-To-Liquids (GTL) Fuel
Authors: Sadeq Abdellatif , Hedayati Amin , Sleiti Ahmad , Ahmed Samer 
Published: August 2023

Abstract
Studying the spatial and temporal evolution in turbulent flames represents one of the most challenging problems in the combustion community. Based on previous 3D numerical analyses, this study aims to develop data-driven Machine Learning (ML) models for predicting the flame radius evolution and turbulent flame speeds for diesel, GTL, and their 50/50 blend (by volumetric composition) under different thermodynamic and turbulence operating conditions. Two ML models were developed in this study. Model 1 predicts the variations of the flame radius with time, equivalence ratio, and turbulence intensity, whereas Model 2 predicts the variations of the turbulence flame speed with the operating parameters. The k-fold cross-validation technique is used for model training, and the developed neural network-based model is used to investigate the effects of operating parameters on the premixed turbulent flames. In addition, the possible minimum and maximum values of responses at the corresponding operating parameters are found by using a Genetic Algorithm (GA) approach. Model 1 could capture the CFD outputs with high precision at different flame radiuses and time instants with a maximum absolute error percentage of 5.46%. For Model 2, the maximum absolute error percentage was 6.58%. Overall, this study demonstrates the applicability and promising performance of the proposed ML models, which will be used in subsequent research to analyze turbulent flames a posteriori.
A 16-yr movie of the spotted surface of the K-giant
XX Trianguli: evidence for a chaotic stellar dynamo
Authors: Strassmeier Klaus , Kovari Zsolt , Weber Michael , Granzer Thomas 
Published: August 2023

Abstract

Sunspots are the most well-known manifestations of solar magnetic fields and exhibit a range of phenomena related to the interior dynamo. Among the observables from the spatially resolved solar disk are the number, size, and morphology of sunspots, their growth and decay, and their migration in latitude and longitude. Starspots are the direct analogs
of sunspots on other stars but with the big observational restriction that we usually can not resolve other star’s surfaces. An indirect technique exists though, a technique historically called Doppler imaging. Typically, only occasional snapshots of spots on stellar surfaces are obtained while it is well-known that spots systematically change with time and, like on the Sun, only then tell us about the interior dynamo and structure of the target in question. Here we present a 16-year long time series of Doppler images for one of the most spotted stars in the sky. Creating this unique times series was only possible thanks to the continuous operation of the STELLA robotic telescope on Tenerife and its high-resolution echelle spectrograph SES. The robot has observed the star on every available clear night since July 2006, acquiring a total of over 2000 high-resolution, high signal-to-noise-ratio (S/N) spectra that are used to create 99 independent Doppler images. We combine these images into a movie visualizing XX Tri’s surface spot evolution for the past 16 years. Stellar-disk photocenter displacements of up to 24 µas, or ≈10% of the stellar disk radius, are reconstructed for XX Tri, but do not conclusively show the typical solar-like periodic behavior that could be interpreted as an activity cycle. A period of ≈4.1 yr is retrieved only from the effective temperature time series but could not be clearly confirmed from other surface tracers. It suggests a mostly chaotic, likely unperiodic, dynamo. The images also indicate missing (blocked) flux due to cool spots of up to 10% of the total flux.
Integrated frequency-modulated optical parametric oscillator
Authors: Safavi-Naeini Amir , Stokowski Hubert , Dean Devin , Hwang Alexander , Park Taewon , Celik Oguz , Jankowski Marc , Langrock Carsten , Ansari Vahid , Fejer Martin 
Published: August 2023

Abstract
Optical frequency combs have revolutionized precision measurement, time-keeping, and molecular spectroscopy.1-5 A substantial effort has developed around ``microcombs'': integrating comb-generating technologies into compact, reliable photonic platforms6. Current approaches for generating these microcombs involve either the electro-optic7 (EO) or Kerr mechanisms8. Despite rapid progress, maintaining high efficiency and wide bandwidth remains challenging. Here, we introduce a new class of microcomb -- an integrated optical frequency comb generator that combines electro-optics and parametric amplification to yield a frequency-modulated optical parametric oscillator (FM-OPO). In stark contrast to EO and Kerr combs, the FM-OPO microcomb does not form pulses but maintains operational simplicity and highly efficient pump power utilization with an output resembling a frequency-modulated laser9. We outline the working principles of FM-OPO and demonstrate them by fabricating the complete optical system in thin-film lithium niobate (LNOI). We measure pump to comb internal conversion efficiency exceeding 93% (34% out-coupled) over a nearly flat-top spectral distribution spanning ≈ 1,000 modes (≈ 6 THz). Compared to an EO comb, the cavity dispersion rather than loss determines the FM-OPO bandwidth, enabling broadband combs with a smaller RF modulation power. The FM-OPO microcomb, with its robust operational dynamics, high efficiency, and large bandwidth, contributes a new approach to the field of microcombs and promises to herald an era of miniaturized precision measurement, and spectroscopy tools to accelerate advancements in metrology, spectroscopy, telecommunications, sensing, and computing.
Low-Pressure Plasma as a Seed Coat to Enhance the Growth of Wheat Seedlings for Obtaining Future Outcomes Under Salinity Conditions
Authors: Elgendy Abdelfattah T. , Elsaid Hesham , Rizk Sameh A. , Saudy Hani S. , Wehbe Nimer , Hassine Mohamed Ben , Al-Nemi Ruba , Jaremko Mariusz , Emwas Abdul-Hamid 
Published: August 2023

Abstract
The increased drought and soil salinity are two effects of climate change that threaten global food security and food production. Soil salinity is a major challenge for agriculture in arid areas, creating conditions that may be unsuitable for the growth of crop plants. Here, we use recycled organic tree waste combined with low-pressure plasma treatment as grain coating to improve the ability of Egyptian wheat seeds (Misr-1 and Gemme-za-11) to survive, germinate and produce seedlings in highly saline soil. We coated the seeds with biofilms of lignin and hash carbon to form a protective extracellular polymeric matrix and then exposed them to low-pressure plasma for different periods of time. The effectiveness of the coating and plasma was evaluated by characterizing the physical and surface properties of coated seeds using X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), nuclear magnetic resonance (NMR) spectroscopy, and wettability testing. We also evaluated biological and physiological properties of coated seeds and plants they produced by studying germination and seedling vigor, as well as by characterizing fitness parameters of the plants derived from the seeds. The analysis revealed the optimal plasma exposure time to enhance germination and seedling growth. Taken together, our study suggests that combining the use of recycled organic tree waste and low-pressure plasma may represent a viable strategy for improving crop performance in salty environments.
Warming and Disturbances Affect North American Arctic-Boreal
Vegetation Resilience
Authors: Liu Yanlan , Zhang Yue , Wang Jonathan , Berner Logan , Goetz Scott , Zhao Kaiguang 
Published: August 2023

Abstract

Rapid warming and increasing disturbances in Arctic-boreal regions have caused extensive vegetation shifts and uncertain future carbon budgets. Better predictions of vegetation dynamics and functions require characterizing resilience–the capability to recover from climate perturbations and disturbances. Here, we quantify time-varying vegetation resilience using temporal autocorrelation of remotely sensed greenness during 2000–2019 across North American Arctic-boreal ecosystems. We find vegetation resilience significantly decreased in most boreal forests, including in forests showing greening trends, while likely increased in the majority of Arctic tundra. Warm and dry areas with high elevation and dense vegetation cover were among the hotspots of reduced resilience. Resilience further diminished both before and after most land cover changes and fires. The findings highlight warming and disturbance have been undermining vegetation resilience, especially in relatively warm boreal forests, potentially undermining the expected long-term increase of high latitude carbon uptake under future climate.
Machine Learning Ensemble Directed Engineering of Genetically Encoded Fluorescent Calcium Indicators
Authors: Berndt Andre , Wait Sarah , Rappleye Michael , Lee Justin , Goy Marc , Smith Netta 
Published: August 2023

Abstract
In this study, we focused on the transformative potential of machine learning in the engineering of genetically encoded fluorescent indicators (GEFIs), protein-based sensing tools that are critical for real-time monitoring of biological activity. GEFIs are complex proteins with multiple dynamic states, rendering optimization by trial-and-error mutagenesis a challenging problem. We applied an alternative approach using machine learning to predict the outcomes of sensor mutagenesis by analyzing established libraries that link sensor sequences to functions. Using the GCaMP calcium indicator as a scaffold, we developed an ensemble of three regression models trained on experimentally derived GCaMP mutation libraries. We used the trained ensemble to perform an in silico functional screen on 1423 novel, uncharacterized GCaMP variants. As a result, we identified the novel ensemble-derived GCaMP (eGCaMP) variants, eGCaMP and eGCaMP+, that achieve both faster kinetics and larger fluorescent responses upon stimulation than previously published fast variants. Furthermore, we identified a combinatorial mutation with extraordinary dynamic range, eGCaMP2+, that outperforms the tested 6th, 7th, and 8th generation GCaMPs. These findings demonstrate the value of machine learning as a tool to facilitate the efficient pre-screening of mutants for functional characteristics. By leveraging the learning capabilities of our ensemble, we were able to accelerate the identification of promising mutations and reduce the experimental burden associated with trial-and-error mutagenesis. Overall, these findings have significant implications for optimizing GEFIs and other protein-based tools, demonstrating the utility of machine learning as a powerful asset in protein engineering.