bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of Intraoperative Fluid Balance During Pancreatoduodenectomy on Postoperative Pancreatic Fistula: An Observational Cohort Study
Authors: Zhang Le , Zhang Yuelun , Shen Le 
Published: January 2023

AbstractBackground:Perioperative fluid management during major abdominal surgery has been controversial. Postoperative pancreatic fistula (POPF) is a critical complication of pancreaticoduodenectomy (PD). We conducted a retrospective cohort study to analyze the impact of intraoperative fluid balance on the development of POPFMethods:This retrospective cohort study enrolled 567 patients who underwent open pancreaticoduodenectomy, and the demographic, laboratory, and medical data were recorded. All patients were categorized into four groups according to quartiles of intraoperative fluid balance. Multivariate logistic regression and restricted cubic splines (RCSs) were used to analyze the relationship between intraoperative fluid balance and POPF.Results:The intraoperative fluid balance of all patients ranged from -8.47 to 13.56 mL/kg/h. A total of 108 patients reported POPF, and the incidence was 19.0%. After adjusting for potential confounders and using restricted cubic splines, the dose‒response relationship between intraoperative fluid balance and POPF was found to be statistically insignificant. The incidences of bile leakage, postpancreatectomy hemorrhage, and delayed gastric emptying were 4.4%, 20.8%, and 14.8%, respectively. Intraoperative fluid balance was not associated with these abdominal complications. BMI≥25kg/m2, preoperative blood glucose<6 mmol/L, long surgery time, and lesions not located in the pancreas were independent risk factors for POPF.Conclusion:The study did not find a significant association between intraoperative fluid balance and POPF. Well-designed multicenter studies are necessary to explore the association between intraoperative fluid balance and POPF.
Analysis of influence mechanism of grinding on the gel properties of soybean protein isolate based on the changes of its structure and solubility
Authors: Liu Yue , Dai Yangyong , Cao Jian , Hou Hanxue , Wang Wentao , Zhang Hui , Ding Xiuzhen , Li Cheng 
Published: January 2023

Abstract
The compact spherical structure of soy protein isolate results in low protein flexibility and poor functional properties. In this study, the influence mechanism of grinding on its gel properties was analyzed according to the changes of soy protein isolate structure and solubility after grinding. The results indicated that at 15 min of grinding, β-sheet of the soy protein isolate decreased from 38.54% to 29.15%, the particle size became smaller, and the original solid sphere became a hollow sphere, the protein had a more disordered secondary structure, and the solubility increased to 28.24%. The glucono-δ-lactone-induced cold-set gel of this protein exhibited higher water holding capacity (76.37%), storage modulus (G') and loss modulus (G″). Creep recovery test showed that this gel had better elasticity and rigid structure at 15 min of grinding. This study could lay a theoretical foundation for research on improving the gel properties of soy protein isolate by mechanical modification in future.
Using textual similarity to identify legal precedents: appraising machine learning models for administrative courts
Authors: Mentzingen Hugo , António Nuno , Bacao Fernando , Cunha Marcio 
Published: January 2023

Abstract
Precedent is the cornerstone of the Common law system. Even in jurisdictions that follow Civil law, precedents constrain decisions when case law is sufficiently uniform. A systematic disregard of precedents makes judgments less coherent and the law less just. Nevertheless, relying on precedents can also make courts more efficient, whereas recent advances in natural language processing (NLP) and machine learning (ML) open doors for solutions to automated and reliable identification of similar cases. In this study, we investigated more than a hundred combinations of document representations and textual vectorization models to assess whether pairs of cases identified by the machine satisfy the human notion of similarity. To this point, analogous models have been evaluated using tiny validation samples. We used a statistically significant sample evaluated by legal experts from an administrative court in Brazil, constituting a gold standard sample. We also propose using evaluation metrics that are meaningful to real-world applications and build upon previous works, employing promising solutions and exploring the extraction of concepts and relationships from legal texts. The results demonstrate that such applications can identify a large proportion of similar cases that can be interpreted as legal precedents. Models that rely on more granular representations of text achieved the best performance. In addition, extracting concepts and relations proved to improve the results, while using models that are more complex and difficult to train may not be the best option. These findings can guide the development of recommendation systems to improve efficiency and consistency in law courts and motivate studies that explore other techniques for this purpose.
Bio-inspired Artificial synapse for neuromorphic computing based on NiO nanoparticle thin film
Authors: Hadiyal Keval , Ganesan Ramakrishnan , Rastogi A. , Thamankar R. 
Published: January 2023

Abstract
The unprecedented need for data processing in the modern technological era has created opportunities in neuromorphic devices and computation. This is primarily due to the extensive parallel processing done in our human brain. Data processing and logical decision-making at the same physical location is an exciting aspects of neuromorphic computation. For this, establishing reliable resistive switching devices working at room temperature with ease of fabrication is important. Here, a reliable analog resistive switching device based on Au/NiO nanoparticles/Au nanoparticles is discussed. The application of positive and negative voltage pulses of constant amplitude results in enhancement and reduction of synaptic current, which is consistent with potentiation and depression, respectively. The change in the conductance resulting in such a process can be fitted well with double exponential growth and decay, respectively. Consistent potentiation and depression characteristics reveal that non-ideal voltage pulses can result in a linear dependence of potentiation and depression with electric pulses. Long-term potentiation (LTP) and Long-term depression (LTD) characteristics have been established, which are essential for mimicking the biological synaptic applications. The NiO nanoparticle-based devices can also be used for controlled synaptic enhancement by optimizing the electric pulses, displaying typical learning-forgetting-relearning characteristics.
Design of a blockchain based secure and efficient ontology generation model for multiple data genres using augmented stratification in healthcare industry
Authors: Purbey Suniti , Khandelwal Brijesh , Choudhary Ashutosh Kumar 
Published: January 2023

Abstract
Ontology generation is a process of relationship analysis, and representation for multiple data categories using automatic or semi-automatic approaches. This process requires a domain knowledgebase that describes given input data using entity-to-entity relations. A wide variety of approaches are proposed for this purpose, and each of them processes & converts input data using multiple relationship evaluation stages. These stages include data-preprocessing, correlation analysis, entity mapping, and ontology generation. A very few of these approaches are dataset independent, and most of them do not implement security measures during ontology generation, which limits their security, scalability & deployment capabilities during real-time implementation. Thus, in this text a blockchain based secure & efficient ontology generation model for multiple data genres using augmented stratification (BOGMAS) is described. The BOGMAS model uses a semi-supervised approach for ontology generation from almost any structured or unstructured dataset. It uses a variance-based method (VBM) for reduction of redundant numerical features from the dataset, while textual features are converted to numerical values via standard word2vec model, and then processed using VBM. This model uses a combination of linear support vector machine (LSVM), and extra trees (ET) stratifiers for variance estimation, which makes the model highly efficient, and reduces redundant features from the output ontology. These feature sets & their variances are given to a correlation engine for relationship estimation, and ontology generation. Each ontology record is secured using a mutable proof-of-work (PoW) based blockchain model, which assists in imbibing transparency, traceability, and distributed peer-to-peer processing capabilities. The generated ontology is represented using an incremental OWL (W3C Web Ontology Language) format, which assists in dynamically sizing the ontology depending upon incoming data. Performance of the proposed BOGMAS model is evaluated in terms of precision & recall of representation, memory usage, computational complexity, and accuracy of attack detection. It is observed that the proposed model is highly efficient in terms of precision, recall & accuracy performance, but has incrementally higher computational complexity & delay of ontology formation when compared with existing approaches. Due to this incremental increase in delay, the proposed model is observed to be applicable for a wide variety of real-time scenarios, which include but are not limited to, medical ontology generation, sports ontology generation, and internet of things (IoT) ontology generation with high security levels.
IoT-Based Low-Cost Children Tracker System
Authors: Marhoon Hamzah M. , Basil Noorulden , Abdulnabi Hussein A. 
Published: January 2023

Abstract
Recently many cases of missing children between ages 14 and 17 years have been reported. Parents always worry about the possibility of kidnapping their children. This work proposes an Android-based solution to aid parents to track their children in real-time. Nowadays, most mobile phones are equipped with internet service capabilities allowing them to connect with the world. The system's architecture is built on two main components: GPS satellite and IoT technology. The most important features of this work are the low cost, lightweight, and small size. The Blynk app is installed on the mobile phone and the GPS is attached to the NodeMCU microcontroller. The location information is reached through the Blynk app with the help of map services.
Engineered symbiotic bacteria interfering Nosema redox system inhibit microsporidia parasitism in honeybees
Authors: Lang Haoyu , Wang Hao , Wang Haoqing , Xie Xianbing , Hu Xiaosong , Zhang Xue , Zheng Hao 
Published: January 2023

Abstract
Nosema ceranae is an intracellular parasite invading the midgut of honeybees, which causes serious nosemosis implicated in honeybee colony losses worldwide. The core gut microbiota is involved in protecting against parasitism, and the genetic engineering of the native gut symbionts provides a novel and efficient way to fight pathogens. Here, using laboratory-generated bees mono-associated with gut members, we find that Snodgrassella alvi inhibited microsporidia proliferation, potentially via the stimulation of host oxidant-mediated immune response. Accordingly, N. ceranae employs the thioredoxin and glutathione systems to defend against oxidative stress and maintain a balanced redox equilibrium, which is essential for the infection process. We knocked down the gene expression using nanoparticle-mediated RNA interference, which targets the γ-glutamyl-cysteine synthetase and thioredoxin reductase genes of microsporidia. It significantly reduces the spore load, confirming the importance of the antioxidant mechanism for the intracellular invasion of the N. ceranae parasite. Finally, we genetically modified the symbiotic S. alvi to deliver dsRNA corresponding to the genes involved in the redox system of the microsporidia. The engineered S. alvi induces RNA interference and represses parasite gene expression, thereby inhibits parasitism by up to 99.8%. Specifically, N. ceranae was most suppressed by the recombinant strain corresponding to the glutathione synthetase or by a mixture of bacteria expressing variable dsRNA. Our findings extend our previous understanding of the protection of gut symbionts against N. ceranae and provide a symbiont-mediated RNAi system for inhibiting microsporidia infection in honeybees.
Database Development and Recognition of Facial Expression using Deep Learning
Authors: Bapat M. M. , Patil C. H. , Mali S. M. 
Published: January 2023

Abstract
Facial expressions reflect human emotions and an individual's intentions. To detect facial expressions
by human beings is a very easy task whereas it’s a very difficult task using computers. They perform a vigorous part in everyday life. It is a non-verbal mode that may include feelings, opinions, and thoughts without speaking. Deep neural networks, Convolutional Neural Networks, Neural networks, Artificial Intelligence, Fuzzy Logic, and Machine Learning are the different technologies used to detect facial expressions. To detect facial expressions, static images, video, webcam data, or real-time images can be used. This research paper focused on developing the SMM Facial Expression dataset and proposes a convolutional neural network model to identify facial expressions. The proposed method was tested on two different benchmarked datasets namely FER2013 and CK+ for facial expression detection. We have explored the proposed model on CK+ and achieved 93.94% accuracy and 67.18 % for FER2013 respectively. To analyze and test the accuracy of the proposed model, we have implemented it on the SMM Facial Expression dataset and achieved 96.60% of accuracy.
Isoflurane alleviates systemic inflammation-induced neuroinflammation by decreasing the blood-brain barrier's damage and regulating the microglia's polarization
Authors: Li Zhendong , Guo Yizhe , Zhao Xingkai , Wang Donglu , Zhou Zhenlei 
Published: January 2023

Abstract
Background
The fundamental pathological role of neuroinflammation is caused by the overactivation of microglia cells in various neurological diseases. Isoflurane has been shown to alleviate neuroinflammation and plays a neuroprotective role in cerebral ischemia-reperfusion, but its role in systemic inflammation remains unclear. This study investigated the role and potential mechanism of isoflurane in neuroinflammation induced by systemic inflammation.
Methods
Mice were injected with LPS intraperitoneally as the animal model. The cell models were BV2 microglia treated directly with LPS and HT22 neurons treated with the conditioned medium. FCM, IF, IHF, and other methods were used to explore the polarization state of microglia by comparing the effects of minocycline and blockers. WB, qPCR, and other methods were used to reveal the molecular mechanism.
Results
In this study, systemic inflammation triggers neuroinflammation, microglia activation, and neuronal impairment one day after modeling. Isoflurane attenuates brain edema, immune cell infiltration, and microglia activation by decreasing blood-brain barrier deterioration. In addition, isoflurane plays a neuroprotective role by regulating microglia polarization and inhibiting neuroinflammation. Simultaneously, data collected from in vitro cell experiments support the above findings.
Conclusion
These data prove that isoflurane plays a protective role in alleviating blood-brain barrier damage and regulating microglial cell polarization by signal axis to alleviate neuronal damage.
The Inhibitory Effect of cLF-chimera, a Recombinant Antimicrobial Peptide, on Avian Influenza Virus Subtype H9N2
Authors: Khodayari Moein , Sekhavati Mohammad Hadi , Peighambari Seyed Mostafa , Barin Abbas , Dezfoulian Omid , Razmyar Jamshid 
Published: January 2023

Abstract
Avian influenza subtype H9N2 is the most prevalent influenza virus in poultry worldwide. It imposes economic losses on the poultry industry and has zoonotic potential. Currently, there are two main groups of anti-influenza drugs in use; Adamantanes and Neuraminidase inhibitors. In recent years, there has been increasing resistance to existing anti-influenza drugs. Antimicrobial peptides are a group of potential drug candidates with broad-spectrum activity. cLF-chimera is an antimicrobial peptide synthesized from camel milk lactoferrin. This study's objective is to evaluate the inhibitory effects of cLF-chimera on avian influenza, subtype H9N2. For this purpose, one hundred and seventy 11-day-old embryonated eggs were randomly distributed in 17 groups. Different virus and peptide concentrations were injected into the eggs. The eggs were incubated for four days with daily candling for viability assessment. On the 4th day of incubation, each group's alive or dead embryos were sorted and evaluated for gross anomalies. Next, the chick embryos were fixed with 10% neutral buffered formalin for one week for histopathological studies. The MTT assay was also performed for the peptide and virus concentrations. Overall, the embryo viability results and macroscopic and histopathologic findings showed that the peptide has inhibitory effects against the virus. These findings agree with the MTT assay. Moreover, the peptide has proven effects against pathogenic bacteria that can be advantageous compared to common anti-influenza medications.
Existence of Solutions for Two-point Integral Boundary Value Problems with Impulses
Authors: Georgiev Svetlin G. , Tikare Sanket , Kumar Vipin 
Published: January 2023

Abstract
In this paper, we investigate the existence of at least one solution and at least two nonnegative solutions of impulsive differential equations with the two-point integral boundary conditions. We employ the recent fixed point theorems for the sum of two operators on Banach spaces. The applicability of the results is illustrated through an example.
Mathematics Subject Classification: 34B10; 34B37; 47H10
Integration of Fractal Geometry and Correspondence Analysis Geochemistry Methods to Reconnaissance High-Potential Promising Areas in a Field of NE Iran
Authors: Hosseini Seyed Aliakbar , Khah Nasser Keshavarz Faraj , Kianoush Pooria , Shirinabadi Reza 
Published: January 2023

Abstract
The background Anomaly separation is one of the most essential stages in geochemical explorations. Most geochemical, statistical, and geostatistical works in mining exploration aim to identify better an anomaly based on scientific discussions. In this paper, Integrating the correspondence analysis and fractal method, the results of analysis data for river sediment sampling at the Khusf area in NE Iran have been investigated. Correspondence analysis with 170 data samples and 20 elements was done. According to correspondence analysis, separating one or several elements is the reason for anomalous value in the study area, and separating one or several samples is the reason for the mentioned elements at the mentioned samples. The results of seven samples show the highest concentration relative to the variables Pb, As, and Cd elements. The correspondence analysis results show that the Khusf area at some locations for Pb, Cd, and as elements have been probability anomalous. After the correspondence analysis, the best variogram for the Khusf area using Win_Gslib software was obtained. The obtained variogram and designed network for estimation by the kriging method at the mentioned area was used. Therefore using the fractal method, three statistical sets determined that the third set showed the anomaly for Pb, Cd and As elements nearly. Finally, it is suggested that this region has the potential of essential metals, especially of the above elements, and will carry out geophysical operations on a local identification scale.
Optical embodiments of Rabi splitting based in photonic integrated waveguide-coupled resonators
Authors: Moss David 
Published: January 2023

Abstract
Realizing optical analogues of quantum phenomena in atomic, molecular, or condensed matter physics has underpinned a range of photonic technologies. Rabi splitting is a quantum phenomenon induced by a strong interaction between two quantum states, and its optical analogues are of fundamental importance for the manipulation of light-matter interactions with wide applications in optoelectronics and nonlinear optics. Here, we propose and theoretically investigate purely optical analogues of Rabi splitting in integrated waveguide-coupled resonators formed by two Sagnac interferometers. By tailoring the coherent mode interference, the spectral response of the devices is engineered to achieve optical analogues of Rabi splitting with anti-crossing behavior in the resonances. Transitions between the Lorentzian, Fano, and Rabi splitting spectral lineshapes are achieved by simply changing the phase shift along the waveguide connecting the two Sagnac interferometers, revealing interesting physical insights about the evolution of different optical analogues of quantum phenomena. The impact of the device structural parameters is also analyzed to facilitate device design and optimization. These results suggest a new way for realizing optical analogues of Rabi splitting based on integrated waveguide-coupled resonators, paving the way for many potential applications that manipulate light-matter interactions in the strong coupling regime.
ANALISIS KEAMANAN JARINGAN UNIVERSITAS KRISTEN DUTA WACANA DENGAN SERANGAN SSL/TLS
Authors: Dharmawan Nathanael , Gani Indriyanta  , I Kadek Dendy Senapartha  
Published: January 2023

Keamanan komunikasi data melalui jaringan sudah menjadi kewajiban yang perlu di pertimbangkan dalam sebuah ekosistem teknologi. Keamanan data memiliki berbagai layer, salah satu layer yang perlu dilindungi adalah layer presentasi dimana SSL/TLS berada. Jika pada layer ini terdapat kerentanan dimana data sensitif seperti cookie, username, dan password, maka kebocoran data akan berdampak besar bagi semua pelaku kepentingan di bidang teknologi yang menggunakan teknologi SSL/TLS.
Dalam rangka penelitian dan peningkatan keamanan data di jaringan kampus Universitas Kristen Duta Wacana (UKDW), maka peneliti melakukan pengujian kerentanan SSL/TLS pada situs web SSAT UKDW dan E-Class UKDW menggunakan Test SSL dari Qualys dan script dari testssl.sh, penulis juga melakukan pengecekan Mixed Content dengan GeekFlare serta pengecekan HSTS Preload meenggunakan situs web HSTS Preload yang disediakan Google. Peneliti juga melakukan uji penetrasi SSL Strip di 12 titik gedung Universitas Kristen Duta Wacana dan juga di Lab D.
Berdasarkan hasil penelitian, ada beberapa hasil yang ditemukan. Hasil pada SSL Test menggunakan Qualys menemukan situs web SSAT dan E-Class sudah menggunakan aturan HTTP Strict Transport Security (HSTS) dengan Max-Age 31536000 (1 tahun) namun HSTS Preload belum di terapkan, pengujian Mixed Content dengan GeekFlare menunjukkan bahwa seluruh transaksi pada SSAT dan E-Class sudah menggunakan jalur HTTPS, lalu pada uji menggunakan script testssl.sh terdapat kerentanan yang terbaca, serta serangan SSL Strip dimungkinkan terjadi di jaringan Universitas Kristen Duta Wacana dengan beberapa kondisi.