bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Real Time Optimization Based Sequential Convex Program for Pressure Management in Water Distribution Systems
Authors: Pham Dai Duc 
Published: May 2023

Abstract
Optimal pressure regulation to water leakage reduction in water distribution systems (WDSs) is one of the most priority tasks for water utilities worldwide. Mathematically, this engineering problem can be casted into a nonlinear program (NLP) where decision variables are valve settings and relative speeds of pumps. With given demand parameters, by formulating and and solving the NLP, control quantities will be computed and applied to the system for the control purpose. In practice, the demand parameters change continuously in time, and solving the formulated NLP requires a huge computation time, as a result, the control quantities obtained from the last NLP are remained to regulate the system until solution of the current NLP (with updated parameters) is available and so on. For this reason, how fast the solution of the NLP is deduced is vital for improving the control system performance. In this paper, we proposed to apply a new real time scheme based sequential convex program for computing approximated control profiles with respect to the change of water demand patterns. In particular, instead of solving the NLP with newly estimated demand pattern to full accuracy, only one convex NLP is solved in the computation framework of the sequential convex program (SCP) to get approximated solution with acceptable accuracy and in a near real time fashion. To demonstrate the efficacy of the real time optimization scheme, we apply it to determine fast control quantities for a real world WDS in Vietnam and one WDS benchmark for optimal pressure management. The results have demonstrated that, by applying such the optimization scheme, the obtained control profile gains acceptable accuracy as compared with the fully accurate one while the performance of control system is significantly enhanced.
Negative Indian Ocean Dipole drives groundwater recharge in southeast Australia
Authors: Rutlidge Helen , Taschetto Andréa , Andersen Martin , Baker Andy 
Published: May 2023

Abstract

Understanding how Australian groundwater recharge is affected by the Pacific and Indian Ocean climate drivers is crucial for water resource planning and management, especially in semi-arid environments. This will allow for assessment of the impact of climate change on the occurrence and timing of groundwater recharge and the sustainable management of this resource into the future. Measuring groundwater recharge is difficult as it occurs in the subsurface. However, caves situated in the unsaturated zone give us the opportunity to observe these subsurface processes. Here we show good agreement between the recharge events measured in a cave system and groundwater bores at a nearby site. We also show that the most significant recharge event during a decade of observations occurred during a particularly strong negative Indian Ocean Dipole period. Through further analysis of recharge events dating back 1900 we show for the first time a significant link with negative Indian Ocean Dipole events.
Investigating the Dynamic Spillover among Exchange Rate, Stock Market Index, Housing Price and Inflation in Iran: Does the Severity of Sanctions Matter?
Authors: Roudari Soheil , Ahmadian-Yazdi Farzaneh , Hammoudeh Shawkat , Rajabli Yasaman 
Published: May 2023

Abstract
This study investigates the effects of the dynamic spillover between exchange rate, stock market index, housing price, and inflation in Iran by using a TVP-VAR model that is based on Diebold and Yilmaz (2012) from March 2006 to January 2022). The results show that inflation is the most influential indicator in the network. But these results are different when it comes to the percentage of influence these four indicators have on the entire network. Also, research findings suggest that during the entire period of sanctions, the exchange rate has been the main channel of transmitting shocks to the network. Besides, the increase in the exchange rate has been the main factor in creating destructive fluctuations in Iran’s economy.
JEL Classification: E44, E31, G10, F51, C22
Predicting the size of the double-lumen tube in Asian women using ultrasound: A randomized controlled trial
Authors: Yao Minmin , Yang Yuying , Wang Ying , Zhao Zhimeng , Liao Qingwu , Liang Chao 
Published: May 2023

Abstract
Background Asian women are often faced with difficult intubation with double-lumen tube (DLT). Previous studies have illustrated that cricoid and left main bronchus diameter together can predict the DLT size better, but it will take extra computed tomography (CT) scans for the patients. We hypothesized that predicting the best-fit left double-lumen tubes (LDLTs) size, ultrasound will show better efficacy than CT without increasing intubating complications for Asian women.
Methods Our study enrolled 152 female patients undergoing elective thoracic surgery between March 2021 to October 2021. Patients were randomized into two groups: 75 in ultrasound group and 77 in the computed-tomography group. Patients in ultrasound group (US group) chosen the LDLT size according to the transverse diameter of the cricoid cartilage measured by ultrasound (TD-US). Controlled group based on the equivalent diameter of the left main bronchus (ED-LMB) measured by airway rebuilding of the helix CT (CT group).
Results The overall accuracy of LDLT was compared. The proportion of the appropriate DLTs was similar between two groups (78.7 vs. 67.5%, P =0.161). The number of inappropriate cases in CT group increased when height of Asian women is under 160 cm (P <0.05). US group showed less resistance to pass the glottis (P <0.001) and took shorter time in intubating (P =0.002).
Conclusion: Using ultrasound alone to select LDLT size has higher accuracy among Asian women less than 160 cm compared with CT.
Trial registration Chictr.org.cn, registration number: ChiCTR2100043764
Effect of additives on sulfur resistance of catalytic filter material during denitrification and synergistic decomposition of 1,2-DCBz
Authors: Wan Jun , Liu Meng , Li Tao , Shi Guangwei , Duan Yufeng 
Published: May 2023

Abstract
Modified Mn-Ce/P84 catalytic filter material can be used to achieve high removal efficiency of NOx and 1,2-DCBz in bag-filtering dust precipitator synergistic removal of multiple pollutants. However, the presence of SO2 in the actual industrial flue gas has an adverse impact on the catalytic performance of the catalytic filter material. In this paper, a kind of Mn-Ce catalytic filter material was prepared by impregnation method, which was modified by Fe, Cu and Co, respectively. As a result, the sulfur resistance of the catalytic filter material was improved. The change of catalytic activity of the three kinds of modified catalytic filter material at different concentrations was compared in SO2 flue gas fixed bed system. And the modified catalytic filter materials were characterized by SEM, BET, XPS, XRD and H2-TPR. When the temperature was over 80 ℃, [NH3] = [NO] = 400 ppm, [O2] = 8%, [1,2-DCBz] = 320 ppm, and [Flow rate] = 1 m/min, different concentrations of SO2 were injected into the simulated flue gas to test the denitrification activity of the catalytic filter material. The results showed that the sulfur resistance of the catalyst could be effectively increased by the introduction of three elements. Under the low SO2 concentration of 150 ppm, the denitrification activity and 1,2-DCBz activity of Fe, Co and Cu modified filter material were increased, and the sulfur resistance of Fe was better under the flue gas conditions of 300 ppm and 450 ppm SO2. Under the condition of 450 ppm SO2 and 200 ℃ reaction, 93.4% denitrification efficiency and 96.1% 1,2-DCBz removal efficiency could be achieved by using modified Fe-Mn-Ce catalytic filter material.
A unified and self-reinforcing mechanism of tumor cell immortality
Authors: Stevers Nicholas , Barger Carter , Yuan Jimmy , Kim Somang , Hong Chibo , Lenzo Olivia , McKinney Andrew , Wu Samuel , Lee Yu-Jin , Kwok Darwin , Suwala Abigail , Appin Christina , Gordan John D. , Molinaro Annette , Song Jun , Costello Joseph 
Published: May 2023

Abstract

Activating mutations in the Telomerase Reverse Transcriptase (TERT) promoter are the single most common non-coding mutation in cancer and enable limitless cell division characteristic of immortal cells1–12. Solving the immortality mechanism represents a major step towards selectively reversing it in cancer cells. TERT promoter mutations create a de novo E26 transformation specific (ETS) transcription factor binding motif, however most of the 28 ETS factors and many other transcriptional regulators have been implicated13–22. Cancer type and mutation specific mechanisms have also been proposed. Here, we uniformly and robustly analyzed fifty-three cell lines representing sixteen cancer types and six recurrent mutations and found that a tetramer of the GA-binding protein (GABP) is specifically responsible for mutant TERT promoter activation in all cases, with no such role in TERT promoter wild type cells. Strikingly, TERT expression is maintained in tetramer depleted tumor cells. We show how and why the tetramer is serially replaced, not by other transcription factors, but by GABP dimers and then weakly by a paralogous tetramer complex. Elimination of the tetramer and dimer reinstates epigenetic repression of TERT, activates checkpoint programs and prevents cancer cell division. We conclude that unique features of the GABP tetramer must therefore determine positive selection of nearly all TERT promoter mutations in human cancer. Furthermore, domains shared among the three GABP complexes present pan-cancer vulnerabilities.
Identifying Two Novel Mutations and MDS/AML Outcome of Severe Congenital Neutropenia/Cyclic Neutropenia
Authors: Komwilaisak Patcharee , Yudhasompop Najwa , Kanchanakamhaeng Kittima , Hongeng Suradej , Pakakasama Samart , Anurathapan Usanarat , Pongphitcha Pongpak , Songdej Duantida , Sasanakul Werasak , Sirachainan Nongnuch 
Published: May 2023

Abstract
Severe congenital neutropenia (SCN)/cyclic neutropenia (CyN), a rare disease, is caused by ELANE or ELA2 gene mutations. The study reported that 4 children (2 SCN and 2 CyN) presented with recurrent infections. The two novel mutations, p. Ala79del and p.Val197GlufsTer18, in exons 3 and 4, were identified, causing SCN and CyN, respectively. One patient with the longest follow-up time of 12.9 years developed MDS/AML with a complex karyotypes and SETBP1 (c.2602G > A, p.D868N) and NRAS (c.34G > A, p.G12S) mutations, was successfully treated with azacytidine and matched unrelated hematopoietic stem cell transplantation.
Topology Robustness Modelling against Targeted Attacks for Smart Healthcare System using Go-GA
Authors: Changazi Sabir Ali , Bakhshi Asim Dilawar , Yousaf Muhammad , Islam Muhammad Hasan , Mohsin Syed Muhammad , Mufti Mohammad Rafiq , Ahmad Bashir 
Published: May 2023

Abstract
The Internet of Things (IoT) has become a pivotal component of modern technology, enabling the interconnection of numerous intelligent devices. It is envisioned to revolutionize various fields through the realization of numerous applications across industries, including healthcare, precision farming, transportation, and smart cities. However, the practical problem of node and link failures due to various constraints, such as low power backup, adverse environmental conditions, fragile metallurgy, and targeted attacks, can negatively impact the overall functionality of IoT networks. To address these challenges, soft and intelligent computing techniques, such as classical heuristic and genetic algorithms, can be utilized to improve the topology robustness of future IoT networks. In this study, we present a system model for a smart healthcare network and evaluate the effectiveness of optimization techniques, including the newly proposed Optimization of Topology for Efficient Convergence (OTEC), which combines a geometric approach in a genetic algorithm with two mechanisms, Efficient Edge Swap (EES) and Node Removal based on Threshold (NRT), to address key limitations in existing techniques. The metric of Schneider R is used to assess the robustness of the topology, with geographic information about IoT nodes and their neighbors stored on a central big data server. The OTEC approach utilizes a nested approach, demonstrating significant improvement over classical genetic algorithms by achieving a 21% increase in Schneider R. Additionally, OTEC effectively addresses limitations present in traditional heuristic algorithms such as ROSE, Simulated Annealing and Hill Climbing. The concept of trustworthiness is also considered from an overall perspective of system functionality. The optimized topology not only improves the robustness of the network but also enhances its trustworthiness, ensuring that the system can operate reliably and ethically. By leveraging soft and intelligent computing techniques, this study provides a valuable contribution to the development of future IoT networks that can handle the challenges of node and link failures while remaining trustworthy and dependable.
Sediment Management using Bandal-like Structures as Nature-Based Solution
Authors: Rahman Md. Munsur , Shampa Shampa , Haque Anisul , Nakagawa Hajime , Zhang Hao , Rahman Ashikur , Dustegir Maruf , Hoaasin Motaher , Hussain Muhammad Muktadir , Islam Johurul , Hore Sudipto Kumar 
Published: May 2023

Abstract
To materialize the inherent opportunities of incoming sediment load, various interventions are being practiced for sediment management in rivers and delta systems. Broadly, the practiced methods can be divided into two categories: (i) management for accelerating siltation to enhance land reclamation and counterbalancing bank erosion (ii) management for de-siltation in the channels to maintain required navigational flow depth. The pre-requisites to achieve the above targets, simultaneously, are quite contradictory as land reclamation need more sediment, while less sediment load is necessary for the maintaining the navigational depth. To overcome the above constraints, Bandal-like Structures (BLS), the indigenous nature-based solution, has conceptualized to utilize through redistributing the local flow-sediment regime to create a sediment deficit zone within the river side and a sediment surplus zone along the bankside that can eventually, be useful for the maintenance of navigational channels and bank stabilization, simultaneously. In this article, the experiences of BLS, to achieve both functions simultaneously are discussed based on the research experiences for last 20 years. Out of many implemented BLS at different scales in the Ganges-Jamuna-Brahmaputra (GBM) system, a well-documented case study of its application is showcased along a reach of the braided Jamuna River. Based on the evaluation of the performance of the implemented case study coupled with the existing indigenous knowledge, a hybrid approach integrating the conventional and community sciences, is proposed as a nature-based solution for sustainable sediment management in the river systems of Bangladesh.
Morphological and ultrastructure studies of the cecum of dromedary camels (Camelus dromedarius)
Authors: Elseory Abdelrahman M. A. , Taha A. A.M. , Ali A. M. , Alkhodair K. M. , Ibrahim Zarroug Hassan , Althnaian Thnaian 
Published: May 2023

Abstract

The current study aimed to clarify the morphology and electron microscopic structure of the adult dromedary’s cecum (Camelus dromedarius). For measurement work, the long axis of the body, the length of the cecum, the small and large intestines of the 15 camels were used. The topography of the cecum was studied in one healthy camel fixed by formalin. Scanning (SEM) and transmission (TEM) electron microscopy were conducted in samples collected from camels immediately after slaughtering in abattoirs in Omdurman, Sudan. According to measurements, the dromedary's cecum comprised 3.2% of the length of the large intestine, 1% of the total length of the small and large intestines, and 0.10 of the body's long axis. The cecum had a diameter of 20.25 cm when it began at the cecocolic junction at the level of the 5th lumbar vertebra, but it diminished towards the apex. It was an S-shaped structure and had an apex that pointed mid-ventrally. It was located ventrally at the right side of the abdominal cavity, caudal to the abomasum, and directed caudally to the pelvic inlet. The mucosa of the cecum had been thrown into several folds, according to SEM. A layer of epithelial cells and many goblet cells covered these folds. Two different types of enterocytes and goblet cells were shown by TEM, one with light cytoplasm and the other with dark cytoplasm. In conclusion, this study indicated that the dromedary camel has a short cecum that is located in the same region as domestic animals.
Molecular detection of Citrus exocortis viroid (CEVd), Citrus viroid-III (CVd-III), and Citrus viroid-IV (CVd-IV) in Palestine
Authors: Abualrob Aswar , Alabdallah Osama , Kubaa Raied Abou , Naser Sabri , Alkowni Raed 
Published: May 2023

Abstract

Citrus is hosting several phytopathogens that impacted production where viroids are among that. Missing data about viroids status in citrus in Palestine was not reported. This study aimed to detect any of Citrus exocortis viroid (CEVd), Citrus viroid-III (CVd-III), and Citrus viroid-IV (CVd-IV) in the germplasm collection of Palestinian National Agricultural Research Center (NARC). Field inspections revealed symptoms such as leaf epinasty; vein discoloration, and bark cracking on varies citrus varieties. Molecularly, high prevalence of CVd-IV CEVd and CVd-III (47%, 31%, and 22%; respectively) were recorded by RT-PCR. Two variants of CVd-III were reported, with 91.3% nucleic acid sequence homology. The sequence of each viroid were deposited in GenBank as (OP925746 for CEVd, OP902248 and OP902249 for CVd-III-PS-1 and -PS-2 isolates, and OP902247 for CVd-IV). This was the first to report three of citrus viroids in Palestine, appealing to apply phytosanitary measurements to disseminate healthy propagating materials free from viroids.
Bioplastic (poly-3-hydroxybutyrate)-producing Massilia endophytica sp. nov., isolated from Cannabis sativa L. ‘Cheungsam’
Authors: Jeon Doeun , Jiang Lingmin , Peng Yuxin , Cho Donghyun , Jeong Rae-dong , Jeong Jaecheol , Lee Jiyoung , Kim Cha Young 
Published: May 2023

Abstract
A rod-shaped, motile, Gram-negative bacterial strain named DM-R-R2A-13T was isolated from the plant Cannabis sativa L. ‘Cheungsam’. The phylogenetic analysis of the 16S rRNA gene sequence revealed that strain DM-R-R2A-13T belongs to the family Oxalobacteraceae and is closely related to members of the genus Massilia, with Massilia flava (97.58% sequence similarity) and Massilia armeniaca (97.37% sequence similarity) being the closest members. The digital DNA-DNA hybridization (dDDH) values between strain DM-R-R2A-13T and Massilia flava CGMCC 1.10685T and Massilia armeniaca ZMN-3Twere 22.2% and 23.3%, while the average nucleotide identity (ANI) values were 78.85% and 79.63%, respectively. The DNA G + C content was measured to be 64.6 mol%. Moreover, the bacterium was found to contain polyhydroxyalkanoate (PHA) granules based on transmission electron microscopy, indicating its potential to produce bioplastic. Genome annotation revealed the presence of PHA synthase genes (phaC, phaR, phaP, and phaZ), and the biopolymer was identified as poly-3-hydroxybutyrate (PHB) based on nuclear magnetic resonance (NMR) and Fourier transform infrared spectroscopy (FTIR) analyses. Using maltose as a carbon source, the strain produced PHB of up to 13.5% of its dry cell weight. Based on the phenotypic, chemotaxonomic, and phylogenetic characteristics, it has been determined that DM-R-R2A-13T represents a novel species belonging to the genus Massilia. As such, the name Massilia endophytica sp. nov. is proposed for this newly identified species. The type strain is DM-R-R2A-13T (= KCTC 92072T = GDMCC 1.2920T).
Estimating pitting descriptors of 316L stainless steel by machine learning and statistical analysis
Authors: Torres Daniel , vangrunderbeek vincent , Bernal Miguel , Paldino Gian , Bontempi Gianluca , Ustarroz Jon , Coelho Leonardo Bertolucci 
Published: May 2023

Abstract

A hybrid rule-base/ML approach using linear regression and artificial neural networks (ANN) determined pitting corrosion descriptors from high-throughput data obtained with Scanning Electrochemical Cell Microscopy (SECCM) on 316L stainless steel. Non-parametric density estimation determined the central tendencies of the Epit/log(jpit) and Epass/log(jpass) distributions. Descriptors estimated using conditional mean or median curves were compared to their central tendency values, with the conditional medians providing more accurate results. Due to their lower sensitivity to high outliers, the conditional medians were more robust representations of the log(j) VsEdistributions. An observed trend of passive range shortening with increasing testing aggressiveness was attributed to delayed stabilisation of the passive film, rather than early passivity breakdown.
Machine learning on longitudinal multi-modal data enabling the understanding and prognosis of Alzheimer’s disease progression
Authors: Zhang Suixia , Yuan Jing , Sun Yu , Wu Fei , Liu Ziyue , Zhai Feifei , Zhang Yaoyun , Somekh Judith , Peleg Mor , Zhu Yi-Cheng , Huang Zhengxing 
Published: May 2023

Abstract
Background Alzheimer’s disease (AD) is a complex pathophysiological disease. Its progression is heterogenous and associated with clinical symptoms as well as prognosis. Hence, understanding the progression of AD is important in guiding patient management, evaluating treatment response and designing therapeutic trials. We developed and validated a novel machine learning model for revealing the underlying disease progression patterns from longitudinal multi-modal data of AD.
Methods The prospective ADNI study data (1192 patients with cognitive impairment and 388 healthy controls) was used to train, validate and test a novel personalized hidden Markov model to identify disease-related states. The transition diagram of disease-related states exhibited two distinct disease progression patterns. We used the index of disease-related states as a predictor, and evaluated the prediction performance on time to conversion to AD dementia. External validation was performed on the AIBL cohort (87 patients with cognitive impairment and 179 healthy controls).
Findings Our model identified ten biologically and clinically meaningful disease-related states from longitudinal multi-modal data, which constitute three non-overlapping stages (i.e., neocortical atrophy [NCA], medial temporal atrophy [MTA], and whole brain atrophy [WBA]) and two distinct disease progression patterns (i.e., NCA→WBA and MTA→WBA) hidden in the trajectories of AD patients. Disclosed patterns showed different atrophy trends of brain regions, and presented distinct genetic, clinical and biomarker characteristics, especially in the early course of the disease. The index of the identified disease-related states provided a remarkable performance on predicting the time to conversion to AD dementia (C-Index: 0.923±0.007), in comparison with the other commonly recognized AD risk factors, including APOE (0.607±0.012), MMSE score (0.808±0.006), Abeta (0.7445±0.013), pTau (0.689±0.006), and hippocampal volume (0.774±0.010).
Interpretation A machine learning algorithm was proposed to capture the full spectrum of AD progression by identifying meaningful AD-related states as well as distinct disease progression patterns from longitudinal multi-modal data, showing its potential for promoting the understanding of heterogeneous disease progression, and early predicting the conversion time to AD dementia.