bluuebunny/crossref_metadata_2025 huggingface dataset:
Overlapping Decentralized Guaranteed Cost Control Method for Discrete-Time Systems of Building Structures with Uncertain Parameters under Earthquake Action
Authors: Xu Qinghu , Zhang Yu , Zhen Xuezhi , Man Dawei , Kang Xiaofang , Xia Guanghui , Shi Xianzeng
Published: May 2022

This paper proposes a discrete-time overlapping decentralized guaranteed cost control algorithm via state feedback. Based on the inclusion principle, a structure system is decoupled into multiple subsystems, and the discretized subsystems’ controllers are designed by using the guaranteed cost control algorithm. Finally, the subsystems’ controllers are contracted into overlapping controllers of the original system, and the design of the control system is completed. This control method is introduced to the civil engineering field to solve the seismic control problem for discrete-time systems of building structures with uncertain parameters. The numerical analysis of the nine-story building structure model with uncertain parameters is carried out. The results show that the proposed control method can still effectively reduce the seismic response of discrete-time system when the structural parameters are uncertain, and the control effect is similar to the centralized control strategy; at the same time, the sampling rate and data transmission speed of the system are improved to ensure the reliability of the system. It illustrates the feasibility and effectiveness of the presented approach.
Some Novel Solutions to a Quadratically Damped Pendulum Oscillator: Analytical and Numerical Approximations
Authors: Salas Alvaro H. , Albalawi Wedad , Alharthi M. R. , El-Tantawy S. A.
Published: May 2022

In this paper, some novel analytical and numerical techniques are introduced for solving and analyzing nonlinear second‐order ordinary differential equations (ODEs) that are associated to some strongly nonlinear oscillators such as a quadratically damped pendulum equation. Two different analytical approximations are obtained: for the first approximation, the ansatz method with the help of Chebyshev approximate polynomial is employed to derive an approximation in the form of trigonometric functions. For the second analytical approximation, a novel hybrid homotopy with Krylov–Bogoliubov–Mitropolsky method (HKBMM) is introduced for the first time for analyzing the evolution equation. For the numerical approximation, both the finite difference method (FDM) and Galerkin method (GM) are presented for analyzing the strong nonlinear quadratically damped pendulum equation that arises in real life, such as nonlinear phenomena in plasma physics, engineering, and so on. Several examples are discussed and compared to the Runge–Kutta (RK) numerical approximation to investigate and examine the accuracy of the obtained approximations. Moreover, the accuracy of all obtained approximations is checked by estimating the maximum residual and distance errors.
Mechanical Analysis of Preventing Reflection Cracks Based on Stress Absorbing Layer
Authors: Han Lingjie , Zhang Shihao , Zhang Zhengqi , Gao Taotao
Published: May 2022

After asphalt concrete overlay, the reflection crack in the old pavement remains a great challenge. In order to overcome this problem, here, we report the effect of stress absorbing layer on the reflection crack. First, the concrete measures to prevent and reduce reflection cracks at home and abroad are analyzed. Then, the mechanism of the generation and development of reflection cracks is studied, the functional characteristics of stress absorbing layer are analyzed, and the principle of antireflection crack is clarified. Further, the effects of modulus thickness and porosity of stress absorbing layer on the stress of pavement structure layer are discussed. Finally, the effect of the stress absorbing layer on preventing reflective cracks is analyzed by numerical simulation. The analyses show that the stress absorbing layer is a thin asphalt concrete layer with good fatigue resistance and low modulus between the old pavement and asphalt pavement, which delays the expansion of pavement reflection cracks. The stress absorbing layer should have high elasticity and low temperature flexibility, water damage resistance, and interlayer bonding. The simulation results suggest that the modulus of the stress absorbing layer should be 400 MPa∼600 MPa, and the thickness should be 1 cm∼2.5 cm. When the thickness of the stress absorption layer is 2.5 cm, the values of tensile stress σX, equivalent stress σMises and maximum shear stress τMax are 31.7%, 29.2%, and 25.7% lower than those of the layer without addition, respectively. The results demonstrate that the effect of stress reduction is obvious, which plays an important role in preventing or reducing the occurrence of reflective cracks. The designed void ratio of the mixture is between 1% and 2.5% for the indoor permeability resistance test. We believe that these findings have certain guiding significance for theoretical analysis and engineering application of stress absorbing layer.
Research on Multilevel Chaotic Image Encryption Algorithm Based on Optical Processing Technology
Authors: Li Guangli , Talha Muhammad
Published: May 2022

A multilevel chaotic image encryption solution based on optical processing technology is proposed to solve the difficulties of poor security and slow picture processing performance in the present avatar encryption method. The security key is created by collecting and categorising the features of multilevel chaotic pictures combined with optical processing technology. As a result, the original picture data are crystal clear and accurate. The increase in image processing security will help in simplifying and speeding the multilevel chaotic picture enrcryption process. As a result of these findings, researchers discovered that the multilevel chaotic picture encryption method based on optical processing technology is more secure in the application process, can perform image encryption faster, and improves the efficiency and accuracy of image processing overall.
Empirical Research on the Critical Success Factors of Construction Program
Authors: Zhou Chunmei , He Zheng , Hu Ping , Yan Hongyan
Published: May 2022

Scientific identification of the factors that underpin the success of construction program can effectively promote the success of construction program. Based on literature statistics, this paper developed the measurement items of key success factors of construction program in Chinese context. Based on exploratory factor analysis, seven key success factors of construction program were extracted. Then, the excellence model of construction program was constructed by referring to the ideas, concepts, and theoretical mechanisms of EFQM model. The research conclusions of this paper provide a systematic and holistic guidance for the successful implementation of the program by the construction program organization and promote the success of the program.
Role of Immune and Inflammatory Mechanisms in Stroke: A Review of Current Advances
Authors: Zhao Hui , Li Yan , Zhang Ying , He Wen-Yan , Jin Wei-Na
Published: May 2022

Stroke accounts for a large proportion of morbidity and mortality burden in China. Moreover, there is a high prevalence of the leading risk factors for stroke, including hypertension and smoking. Understanding the underlying mechanisms and developing effective therapeutic interventions for patients with stroke is a key imperative. The pathophysiology of stroke involves a complex interplay between the immune and inflammatory mechanisms. Focal brain inflammation triggered by neuronal cell death and the release of factors such as damage-associated molecular patterns can further exacerbate neuronal injury; in addition, impairment of the blood-brain barrier, oxidative stress, microvascular dysfunction, and brain edema cause secondary brain injury. Immune cells, including microglia and other infiltrating inflammatory cells, play a key role in triggering focal and global brain inflammation. Anti-inflammatory therapies targeting the aforementioned mechanisms can alleviate primary and secondary brain injury in the aftermath of a stroke. Further experimental and clinical studies are required to explore the beneficial effects of anti-inflammatory drugs in stroke.
Retinal blood vessel segmentation using multiple line operator-based methods
Authors: Cahya Wihandika Randy , Pandu Adikara Putra , Adinugroho Sigit , Arum Sari Yuita , Utaminingrum Fitri
Published: May 2022

The morphological alterations of the retinal blood vessels are important indicators that can be utilized to diagnose and track the progression of a number of disorders. Diabetic retinopathy (DR) is a condition that destroys the retina and is the major cause of visual loss caused by high blood glucose levels. One of the retinal objects impacted by DR is the blood vessel. By regularly monitoring changes in the retinal blood vessels, severe DR or even vision loss can be avoided. The condition of the blood vessel can be examined by segmenting the blood vessel area from a digital fundus image. Segmenting retinal blood vessels manually, on the other hand, is time-consuming and tedious, and especially when dealing with a high number of photographs. As a result, a system for segmenting retinal blood vessels automatically is crucial. Furthermore, methods for automatically segmenting retinal blood vessels are useful for person authentication systems based on the retina. Blood vessel segmentation can be accomplished in a number of ways. Based on the prior line operator method, an improved version of the line operator method is proposed in this paper. The proposed method demonstrates an improvement in accuracy over the previous method, with an accuracy of 94.61%.
Blockchain in fifth-generation network and beyond: a survey
Authors: Mustafa Ahmed Shamil , Al-Mashhadani Mohammad Abdulrahman , Jasim Salah Ayad , Shantaf Ahmed Muhi , Hamdi Mustafa Maad
Published: May 2022

Fifth-generation (5G) technologies enable a wide range of vertical applications by connecting heterogeneous equipment and machines, resulting in significantly improved service quality, increased network capacity, and improved system performance. As a result, the world is shifting to 5G wireless networks. Because 5G has the advantage of supporting various vertical applications, 5G systems must still overcome challenges such as transparency, data interoperability probabilities, decentralization, and network privacy. In this paper, we'll show how blockchain can be used to solve problems in 5G, as well as some of the idea’s researchers, have come up with to solve them, like resource sharing, security, and mobility.
Design of novel hexagonal s-band patches antenna array for RFID applications
Authors: Slimane Zohra , Rabah Mohammed Amin , Abdelmalek Abdelhafid , Yamani Kouther , Hachemi Kaoutar
Published: May 2022

The design and study of the behavior of antennas adapted to radio-frequency identification RFID tags take on all their importance because they must respond to integration problems and therefore the need to design a structure with minimal dimensions, without however deteriorating their performance. The rise in frequency makes it possible to have short wavelengths so that it becomes possible to have a great integrationas as well as very fast bit rate. But, this induces a smaller range due to the propagation losses according to the model of Friis. In this article, a new patch antenna array for microwave frequency band in radio-frequency identification RFID applications will be presented. The antenna covers the band for the central frequency of 2.45 GHz with better loss characteristics. In addition, the antenna offers a high gain at this frequency. After the digital design of the antenna element, which was carried out using the commercial software CST MWS®, the antenna is printed on an FR4 substrate with a dielectric constant of 4.3 and a thickness of 1.6 mm. The comparison between the simulation results and the measurement results proves that the antenna achieves satisfactory impedance matching and radiation efficiency.
Diabetes tracking panel: an on-line information system to registration and management
Authors: Salcedo Dixon , Cortes Albeiro , Ternera Yesid , Henriquez Carlos , Martes Leidy
Published: May 2022

Online hospital information systems enable health care providers to ensure information. Although nowadays there are great technological advances; in Colombia, the impact on the health sector has been low. As a result, there is an increasing deficiency in cities with less access to new technologies. Therefore, it is necessary for the government and health care providers to join efforts to expand the use of information technologies in the health area to improve the overall quality of the service provided. Therefore, this project introduces diabetes tracking panel tests system to improve the management process. The development system is based on several Open-Source platforms, such as MySQL, among others. Finally, we found that implemented system can reduce the time management of diabetes tests by the staff medical and assistance care personal.
Evaluating multi-state systems reliability with a new improved method
Authors: Lamalem Yasser , Hamida Soufiane , Tazouti Yassine , Gannour Oussama El , Housni Khalid , Cherradi Bouchaib
Published: May 2022

The computation of network reliability for a system with many states is an NP-hard issue. Finding all the minimum path vectors (d-MPs) lower boundary points for each level d is one of the few approaches for computing such dependability. This research proposed enhancements to the technique described in Chen's "Searching for d-MPs with rapid enumeration" paper. We propose additional adjustments to the method that creates the flow vector F in this enhancement. This decreases the number of required steps and the temporal complexity of the method. Comparing the newly suggested approach to the old algorithm reveals that the adjustment has increased the enumeration's efficiency and degree of complexity.
Detection and mitigation of DDoS attacks in internet of things using a fog computing hybrid approach
Authors: Hassan Karrar Falih , Manaa Mehdi Ebady
Published: May 2022

The introduction of a new technology has aided the exponential growth of the internet of things (IoT), allowing for the connecting of more devices in the IoT network to be made possible by the availability of quicker connections and reduced latency. As IoT networks have become more prevalent and widely used, security has become one of the fundamental requirements, and a distributed denial of service (DDoS) attack poses a significant security threat due to the limited resources (CPU, memory, open source, persistent connection) that can be used to either intentionally or unintentionally increase DDOS attacks. Fog computing is proposed in this study as a framework for real-time detection and mitigation of DDoS assaults. Fog computing is accurate and quick in detecting attacks due to its proximity to IoT devices. DDOS assaults are detected using an approach that combines randomness measurement of traffic with k-nearest neighbors (KNN) machine learning algorithm. Suggested system obtained 100% detection accuracy for transmission control protocol TCP attacks, 98.79% detection accuracy for UDP attacks, and 100% detection accuracy for internet control message protocol ICMP attacks.
Fast and accurate classifying model for denial-of-service attacks by using machine learning
Authors: Kareem Mohammed Ibrahim , Jasim Mahdi Nsaif
Published: May 2022

A denial of service (DoS) attack is one of the dangerous threats to networks that Internet resources and services will be less available, as they are easily operated and difficult to detect. As a result, identifying these intrusions is a hot issue in cybersecurity. Intrusion detection systems that use classic machine learning algorithms have a long testing period and high computational complexity. Therefore, it is critical to develop or improve techniques for detecting such an attack as quickly as possible to reduce the impact of the attack. As a result, we evaluate the effectiveness of rapid machine learning methods for model testing and generation in communication networks to identify denial of service attacks. In WEKA tools, the CICIDS2017 dataset is used to train and test multiple machine learning algorithms. The wide learning system and its expansions and the REP tree (REPT), random tree (RT), random forest (RF), decision stump (DS), and J48 were all evaluated. Experiments have shown that J48 takes less testing time and performs better, whereases it is performed by using 4-8 features. An accuracy result of 99.51% and 99.96% was achieved using 4 and 8 features, respectively.
Intelligent university timetable scheduling system using sudoku grid with magic square
Authors: Alkallak Isra Natheer , Shaban Ruqaya Zedan , Alnema Yazen Hudhaifa Shakir
Published: May 2022

Examination timetabling is problem faced by many academic educational institutions. The situation formulated as artificial intelligence problems as Sudoku grid with Magic square. Problem assigning a set of examinations to a fixed number of examination periods so that no student is required to take more than one examination at a time. The research describes two proposed heuristic algorithms to create university examination timetabling and avoiding the overlapping of exams. We proposed two algorithms, the first algorithm is based on Sudoku grid, a number of hard constraints as well as a number of soft constraints are proposed. We assigned exams as 9 to period as 27 slot times and to 3 rooms, with 3 classes. Each student in each class takes 9 exams While, the second algorithm simulates the classic manual methods while observing the hard and soft constraints of the problem. The heuristic approach used to further optimize the result to include hard constraints with soft. The proposed methodology for creating the Exam timetabling problem has been implemented in Matlab and closing the gap between classical methods and intelligent methods. The results obtained with very less computational effort through two algorithms.
Proposed model for data protection in information systems of government institutions
Authors: Jassim Muhasin Haifaa , Yahya Gheni Ali , Adil Yousif Hiba
Published: May 2022

Information systems and data exchange between government institutions are growing rapidly around the world, and with it, the threats to information within government departments are growing. In recent years, research into the development and construction of secure information systems in government institutions seems to be very effective. Based on information system principles, this study proposes a model for providing and evaluating security for all of the departments of government institutions. The requirements of any information system begin with the organization's surroundings and objectives. Most prior techniques did not take into account the organizational component on which the information system runs, despite the relevance of this feature in the application of access and control methods in terms of security. Based on this, we propose a model for improving security for all departments of government institutions by addressing security issues early in the system's life cycle, integrating them with functional elements throughout the life cycle, and focusing on the system's organizational aspects. The main security aspects covered are system administration, organizational factors, enterprise policy, and awareness and cultural aspects.
Using liquid phase precursor method to create a high-efficiency Ca2SiO4:Eu2+ green-emitting phosphor
Authors: Huu Phuc Dang , Thi Dieu An Nguyen
Published: May 2022

A standard solid-state reaction (SSR), a new fluid phase preparatory method utilizing LPP-SiO2(sol), and a water-based soluble silicone compound were employed to manufacture green Eu2+-based Ca2SiO4 phosphors liquid phase precursor (LPP-WSS). The generated phosphors feature large excitation spectra in the range of 225–450 nm and a strong green emission reaches the peak value at 502 nm owing to a 4f65d1→4f7(8S7/2) transition of Eu2+. These samples burned at 1100 1C produce the highest luminous intensity. The luminous properties of phosphors, which are manufactured by the liquid phase precursor LPP-WSS technique, were investigated at the range of 0.1-5.0 mol percent of Eu2+, with the maximum emission density observed at the value of 3.0 mol percent of Eu2+. The phosphors produced by the LPP-WSS technique exhibited a more uniform phase dispersion and higher luminous strength than those produced using the other procedures, according to a detailed report based on numerous characterizations. As a result, Ca2SiO4:Eu2+ has an indisputable possibility in white light-emitting diodes WLEDs and fluorescent lighting.
Random forest and support vector machine based hybrid liver disease detection
Authors: Admassu Assegie Tsehay , Subhashni Rajkumar , Komal Kumar Napa , Prasath Manivannan Jijendira , Duraisamy Pradeep , Fentahun Engidaye Minychil
Published: May 2022

This study develops an automated liver disease detection system using a support vector machine and random forest detection techniques. These techniques are trained on data containing the information collected from the Mayo Clinic trial in primary biliary cirrhosis (PBC) of the liver conducted between 1974 and 1984. The proposed system can detect the presence of liver disease in the test set. The random forest model is used for recursive feature elimination at the pre-processing stage and the support vector machine is trained on the optimal feature set. The experimental result shows that the proposed support vector machine (SVM) model has achieved 78.3% accuracy.
A review of electricity consumer behavioural change under sustainable energy management scheme
Authors: Sulaima Mohamad Fani , Jumidey Nurul Fasihah , Ahmad Arfah , Kadir Aida Fazliana Abdul , Sukri Mohamad Firdaus , Tahir Mustafah Mohd
Published: May 2022

Many authorities launched their energy sustainability plan that involve the sustainable energy management scheme to improve energy efficiency. The sustainable energy management scheme consists of several measures to encourage energy efficiency in three primary energy consumers by pursuing implementation measures in the industrial, commercial, and residential sectors. Meanwhile, energy performance is quantifiable in energy efficiency and energy consumption become one of scheme measure aspects. In this review, the ASEAN Energy Management Scheme (AEMAS) was discussed as a regionally structured training and certification system for ASEAN Energy Managers. Besides that, Energy Management Gold Standard (EMGS) is AEMAS's first regional achievement certification for global excellence in energy management systems. Previous literatures exposed the key to energy efficiency goals is behavioural change, which means individual attitudes affect energy consumption.
Power losses analysis of multiphase DC-DC buck converter using OrCAD PSpice software
Authors: Abdul Ghani Ahmad Faiz , Hazwaj Poad Mhd , Abu Bakar Afarulrazi , Nuraini Norazman Siti , Noor Amran Mohd Azlee
Published: May 2022

DC-DC buck converters have wide applications in portable electronic devices, battery chargers, and telecommunications. However, single-phase DC-DC buck converters have some drawbacks, especially in high current applications, where the increase in the size of the inductor will increase power losses, which significantly affects the overall efficiency of the converter. The multiphase configuration offers several advantages, such as reduction in output voltage ripple, input current ripple, conduction loss, and the physical size of the hardware. This paper presents an analysis of the power losses of the multiphase DC-DC buck converter with output power ranging between 50 watts to 250 watts. To verify the effectiveness of the multiphase converter, performance analysis was done using OrCAD PSpice software, where the number of phases was limited to five phases. This paper focused on power losses in the converter, namely conduction losses in diodes and MOSFETs, switching loss in MOSFETs, as well as losses in the inductor and capacitor. The relationship between the number of phases and factors of switching frequency, output, and the components’ internal resistance was also highlighted and discussed in detail.
Impact of Racial Disparities in Preoperative Cardiovascular Evaluation and Surgical Outcomes in Patients Undergoing Metabolic and Bariatric Surgery: A Retrospective Cohort Analysis
Authors: Ibrahim Kaitlyn D. , Tragesser Lauren A. , Soans Rohit , Haddad Abdullah , Eddy Vikram J. , McComb Joseph , Keane Martin G. , Whitman Isaac R.
Published: May 2022

Background

We investigated preoperative referral patterns, rates of cardiovascular testing, surgical wait times, and postoperative outcomes in White versus Black, Hispanic, or other racial or ethnic groups of patients undergoing metabolic and bariatric surgery.

Methods and Results

This was a single center retrospective cohort analysis of 797 consecutive patients undergoing metabolic and bariatric surgery from January 2014 to December 2018; 86% (n=682) were Black, Hispanic, or other racial or ethnic groups. White versus Black, Hispanic, or other racial or ethnic groups had similar baseline comorbidities and were referred for preoperative cardiovascular evaluation in similar proportion (65% versus 68%,
P
=0.529). Black, Hispanic, or other racial or ethnic groups of patients were less likely to undergo preoperative cardiovascular testing (unadjusted odds ratio [OR], 0.56; 95% CI, 0.33–0.95;
P
=0.031; adjusted for Revised Cardiac Risk Index OR, 0.59; 95% CI, 0.35–0.996;
P
=0.049). White patients had a shorter wait time for surgery (unadjusted hazard ratio [HR], 0.7; 95% CI, 0.58–0.87;
P
=0.001; adjusted HR, 0.7; 95% CI, 0.56–0.95;
P
=0.018). Reduction in body mass index at 6 months was greater in White patients (12.9 kg/m
2
versus 12.0 kg/m
2
,
P
=0.0289), but equivalent at 1 year (14.9 kg/m
2
versus 14.3 kg/m
2
,
P
=0.330).

Conclusions

White versus Black, Hispanic, or other racial or ethnic groups of patients were referred for preoperative cardiovascular evaluation in similar proportion. White patients underwent more preoperative cardiac testing yet had a shorter wait time for surgery. Early weight loss was greater in White patients, but equivalent between groups at 12 months.
Effects of Sodium Nitroprusside Administered Via a Subdural Intracranial Catheter on the Microcirculation, Oxygenation, and Electrocortical Activity of the Cerebral Cortex in a Pig Cardiac Arrest Model
Authors: Lee Hyoung Youn , Jung Yong Hun , Mamadjonov Najmiddin , Jeung Kyung Woon , Kim Min Chul , Lim Kyung Seob , Jeon Chang‐Yeop , Lee Youngjeon , Kim Hyung Joong
Published: May 2022

Background

Postischemic cerebral hypoperfusion has been indicated as an important contributing factor to secondary cerebral injury after cardiac arrest. We evaluated the effects of sodium nitroprusside administered via a subdural intracranial catheter on the microcirculation, oxygenation, and electrocortical activity of the cerebral cortex in the early postresuscitation period using a pig model of cardiac arrest.

Methods and Results

Twenty‐nine pigs were resuscitated with closed cardiopulmonary resuscitation after 14 minutes of untreated ventricular fibrillation. Thirty minutes after restoration of spontaneous circulation, 24 pigs randomly received either 4 mg of sodium nitroprusside (IT‐SNP group) or saline placebo (IT‐saline group) via subdural intracranial catheters and were observed for 5 hours. The same dose of sodium nitroprusside was administered intravenously in another 5 pigs. Compared with the IT‐saline group, the IT‐SNP group had larger areas under the curve for tissue oxygen tension and percent changes of arteriole diameter and number of perfused microvessels from baseline (all
P
<0.05) monitored on the cerebral cortex during the 5‐hour period, without severe hemodynamic instability. This group also showed faster recovery of electrocortical activity measured using amplitude‐integrated electroencephalography. Repeated‐measures analysis of variance revealed significant group–time interactions for these parameters. Intravenously administered sodium nitroprusside caused profound hypotension but did not appear to increase the cerebral parameters.

Conclusions

Sodium nitroprusside administered via a subdural intracranial catheter increased post–restoration of spontaneous circulation cerebral cortical microcirculation and oxygenation and hastened electrocortical activity recovery in a pig model of cardiac arrest. Further studies are required to determine its impact on the long‐term neurologic outcomes.
Biased Competition between Targets and Distractors Reduces Attentional Suppression: Evidence from the Positivity Posterior Contralateral and Distractor Positivity
Authors: Kerzel Dirk , Huynh Cong Stanislas
Published: May 2022

The biased competition account claims that competition between two stimuli increases when they are close together compared with when they are far apart. The reason is that nearby stimuli are more likely to be represented in the same receptive fields, requiring top–down or bottom–up biases to resolve the ambiguity. Consistent with biased competition, previous research showed that an index of attentional enhancement, the N2pc component, was attenuated when two targets were close together. In contrast, it is unclear whether distractor processing would also be attenuated when the distractor is close to the target. To answer this question, we used the additional singleton paradigm where a target is sometimes accompanied by a more salient, but entirely irrelevant, distractor. In the conditions of interest, the distance between the target and the distractor was systematically manipulated whereas the eccentricity to central fixation was always the same. The results showed that two indices of attentional suppression, the positivity posterior contralateral and distractor positivity components, were attenuated when the distractor was close to the target. Consistent with biased competition, attentional suppression of distractors was inhibited when the distance between target and distractor was short. The reduced attentional suppression of distractors with nearby targets may contribute to the increased behavioral interference with close distractors.
Turkish Causatives Are Recursive: A Response to Key 2013
Authors: Nie Yining
Published: May 2022

It is claimed in Key 2013 that Turkish, despite allowing multiple causative morphemes on a single complex verb, does not in fact allow causative recursion, where one causing event is embedded by another causing event. This squib argues against Key’s conclusion, using evidence from eventhood diagnostics to show that “double” causatives in Turkish encode two distinct, syntactically represented causing events in addition to the caused event. Thus, Turkish causatives are indeed recursive. This finding supports approaches to productive affixal causatives that allow recursive embedding of the same category over approaches that rely on a fixed functional hierarchy.
Etudes de genre et population fictionnelle des Mille et une nuits : nouvelle approche
Authors: Chraïbi Aboubakr
Published: May 2022

Feminist approaches and gender studies are among the most notable works devoted to the Thousand and One Nights. Šahrazād monopolizes the attention and is treated as a monolithic character, there are in fact several Šahrazāds, depending on the textual version considered. The one who learns history and has three children (ZER) is not the same as the one who learns medicine and has no children (G/Kayseri). On the other hand, Šahrazād would benefit from being reintegrated into her universe beside the other characters: in the Nights, a story can occur with male protagonists (The Second Shaykh) and be repeated with female protagonists (The Eldest Lady), or feature characters who biologically change their gender, through metamorphosis or, in their appearance, through disguise. Such behavioral variations can affect the entire population of the Nights, which new work proposes to approach in the manner of demographers, as has been practiced for illustrated albums (Brugeilles, Cromer, and Cromer) and as Françoise Lavocat’s research on the French novel shows. Now, with some adjustments (Katz; van Renterghem), it seems possible to transpose this type of approach to medieval Arabic literature and more particularly to the Thousand and One Nights.
Sponsorship and Negotiation for Women Otolaryngologists at Midcareer: A Content Analysis
Authors: Farlow Janice L. , Mott Nicole M. , Standiford Taylor C. , Dermody Sarah M. , Ishman Stacey L. , Thompson Dana M. , Malloy Kelly M. , Bradford Carol R. , Malekzadeh Sonya
Published: May 2022

Objective

To explore challenges and opportunities for supporting midcareer women otolaryngologists in the areas of negotiation and sponsorship.

Study Design

Qualitative approach using semistructured interviews.

Setting

Online multi‐institutional interviews.

Methods

This study was performed from June to August 2021. Women otolaryngologists representing diverse subspecialties, training, and practice environments were recruited via a purposive criterion‐based sampling approach. Semistructured interviews were transcribed, coded, and analyzed via an inductive‐deductive approach to produce a thematic content analysis.

Results

Among the 12 women interviewees, who represented 7 subspecialties, the majority were Caucasian (58%) and in academic practice (50%). The median residency graduation year was 2002 (range, 1982‐2013). Participants expressed several challenges that women otolaryngologists face with respect to negotiation, including the absence of systematic formal negotiation training, gendered expectations that women experience during negotiations, and a perceived lack of power in negotiations. Obstacles to effective sponsorship included difficulty in the identification of sponsors and the influence of gender and related systemic biases that hindered sponsorship opportunities.

Conclusion

Notable gender disparities exist for negotiation and sponsorship in the midcareer stage for women otolaryngologists. Women start at a disadvantage due to a lack of negotiation training and access to sponsors, which is exacerbated by systemic gender bias and power differentials as women advance in their careers. This study highlights opportunities to improve negotiation and sponsorship for women, with the goal of promoting a more diverse workforce.
Fractal variational principle for an optimal control problem
Authors: Ma Hongjin
Published: May 2022

The optimal control of a system governed by an elliptic equation has been widely applied in engineering, and it requires twice differentiability. Furthermore, the optimal control cannot effectively deal with unsmooth boundaries. Now, the condition will not be maintained for a long time because this paper suggests a fractal optimal control of a system governed by a fractal variational principle to deal with unsmooth boundaries. The new optimal theory has obvious advantages in low differentiability for an unsmooth boundary problem. The air conditioning in a room is used as an example to show how to maintain maximum comfortableness of the workplace and maximum efficiency of energy saving.
A successful hybrid deep learning model aiming at promoter identification
Authors: Wang Ying , Peng Qinke , Mou Xu , Wang Xinyuan , Li Haozhou , Han Tian , Sun Zhao , Wang Xiao
Published: May 2022

Background

The zone adjacent to a transcription start site (TSS), namely, the promoter, is primarily involved in the process of DNA transcription initiation and regulation. As a result, proper promoter identification is critical for further understanding the mechanism of the networks controlling genomic regulation. A number of methodologies for the identification of promoters have been proposed. Nonetheless, due to the great heterogeneity existing in promoters, the results of these procedures are still unsatisfactory. In order to establish additional discriminative characteristics and properly recognize promoters, we developed the hybrid model for promoter identification (HMPI), a hybrid deep learning model that can characterize both the native sequences of promoters and the morphological outline of promoters at the same time. We developed the HMPI to combine a method called the PSFN (promoter sequence features network), which characterizes native promoter sequences and deduces sequence features, with a technique referred to as the DSPN (deep structural profiles network), which is specially structured to model the promoters in terms of their structural profile and to deduce their structural attributes.

Results

The HMPI was applied to human, plant and Escherichia coli K-12 strain datasets, and the findings showed that the HMPI was successful at extracting the features of the promoter while greatly enhancing the promoter identification performance. In addition, after the improvements of synthetic sampling, transfer learning and label smoothing regularization, the improved HMPI models achieved good results in identifying subtypes of promoters on prokaryotic promoter datasets.

Conclusions

The results showed that the HMPI was successful at extracting the features of promoters while greatly enhancing the performance of identifying promoters on both eukaryotic and prokaryotic datasets, and the improved HMPI models are good at identifying subtypes of promoters on prokaryotic promoter datasets. The HMPI is additionally adaptable to different biological functional sequences, allowing for the addition of new features or models.
Hypoxia classifier for transcriptome datasets
Authors: Puente-Santamaría Laura , Sanchez-Gonzalez Lucia , Ramos-Ruiz Ricardo , del Peso Luis
Published: May 2022

Molecular gene signatures are useful tools to characterize the physiological state of cell populations, but most have developed under a narrow range of conditions and cell types and are often restricted to a set of gene identities. Focusing on the transcriptional response to hypoxia, we aimed to generate widely applicable classifiers sourced from the results of a meta-analysis of 69 differential expression datasets which included 425 individual RNA-seq experiments from 33 different human cell types exposed to different degrees of hypoxia (0.1–5%$$\hbox {O}_{2}$$

O
2

) for 2–48 h. The resulting decision trees include both gene identities and quantitative boundaries, allowing for easy classification of individual samples without control or normoxic reference. Each tree is composed of 3–5 genes mostly drawn from a small set of just 8 genes (EGLN1, MIR210HG, NDRG1, ANKRD37, TCAF2, PFKFB3, BHLHE40, and MAFF). In spite of their simplicity, these classifiers achieve over 95% accuracy in cross validation and over 80% accuracy when applied to additional challenging datasets. Our results indicate that the classifiers are able to identify hypoxic tumor samples from bulk RNAseq and hypoxic regions within tumor from spatially resolved transcriptomics datasets. Moreover, application of the classifiers to histological sections from normal tissues suggest the presence of a hypoxic gene expression pattern in the kidney cortex not observed in other normoxic organs. Finally, tree classifiers described herein outperform traditional hypoxic gene signatures when compared against a wide range of datasets. This work describes a set of hypoxic gene signatures, structured as simple decision tress, that identify hypoxic samples and regions with high accuracy and can be applied to a broad variety of gene expression datasets and formats.
Comparative genomics of the Western Hemisphere soft tick-borne relapsing fever borreliae highlights extensive plasmid diversity
Authors: Kneubehl Alexander R. , Krishnavajhala Aparna , Leal Sebastián Muñoz , Replogle Adam J. , Kingry Luke C. , Bermúdez Sergio E. , Labruna Marcelo B. , Lopez Job E.
Published: May 2022

Background

Tick-borne relapsing fever (TBRF) is a globally prevalent, yet under-studied vector-borne disease transmitted by soft and hard bodied ticks. While soft TBRF (sTBRF) spirochetes have been described for over a century, our understanding of the molecular mechanisms facilitating vector and host adaptation is poorly understood. This is due to the complexity of their small (~ 1.5 Mb) but fragmented genomes that typically consist of a linear chromosome and both linear and circular plasmids. A majority of sTBRF spirochete genomes’ plasmid sequences are either missing or are deposited as unassembled sequences. Consequently, our goal was to generate complete, plasmid-resolved genomes for a comparative analysis of sTBRF species of the Western Hemisphere.

Results

Utilizing aBorreliaspecific pipeline, genomes of sTBRF spirochetes from the Western Hemisphere were sequenced and assembled using a combination of short- and long-read sequencing technologies. Included in the analysis were the two recently isolated species from Central and South America,Borrelia puertoricensisn. sp. andBorrelia venezuelensis, respectively. Plasmid analyses identified diverse sequences that clustered plasmids into 30 families; however, only three families were conserved and syntenic across all species. We also compared two species,B. venezuelensisandBorrelia turicatae, which were isolated ~ 6,800 km apart and from different tick vector species but were previously reported to be genetically similar.

Conclusions

To truly understand the biological differences observed between species of TBRF spirochetes, complete chromosome and plasmid sequences are needed. This comparative genomic analysis highlights high chromosomal synteny across the species yet diverse plasmid composition. This was particularly true forB. turicataeandB. venezuelensis,which had high average nucleotide identity yet extensive plasmid diversity. These findings are foundational for future endeavors to evaluate the role of plasmids in vector and host adaptation.
De novo transcriptome assembly of the cotyledon of Camellia oleifera for discovery of genes regulating seed germination
Authors: Long Wei , Yao Xiaohua , Wang Kailiang , Sheng Yu , Lv Leyan
Published: May 2022

Background

Camellia oleifera (C.oleifera) is one of the most important wood oil species in the world. C.oleifera was propagated by nurse seedling grafting. Since the morphology of rootstocks has a significant impact on grafting efficiency and seedling quality, it is necessary to understand the molecular mechanism of morphogenesis for cultivating high-quality and controllable rootstocks. However, the genomic resource for this species is relatively limited, which hinders us from fully understanding the molecular mechanisms of seed germination in C.oleifera.

Results

In this paper, using transcriptome sequencing, we measured the gene expression in the C.oleifera cotyledon in different stages of development and the global gene expression profiles. Approximately 45.4 gigabases (GB) of paired-end clean reads were assembled into 113,582 unigenes with an average length of 396 bp. Six public protein databases annotate 61.5% (68,217) of unigenes. We identified 11,391 differentially expressed genes (DEGs) throughout different stages of germination. Enrichment analysis revealed that DEGs were mainly involved in hormone signal transduction and starch sucrose metabolism pathways. The gravitropism regulator UNE10, the meristem regulators STM, KNAT1, PLT2, and root-specific transcription factor WOX11 all have higher gene expression levels in the CAM2 stage (seed soaking), which indicates that the cotyledon-regulated program for germination had initiated when the seeds were imbibition. Our data showed differentially reprogrammed to multiple hormone-related genes in cotyledons during C.oleifera seed germination.

Conclusion

Cotyledons play vital roles, both as the main nutrient provider and as one primary instructor for seed germination and seedling growth. Together, our study will significantly enrich the genomic resources of Camellia and help us understand the molecular mechanisms of the development in the seed germination and seedling growth of C.oleifera. It is helpful to culture standard and superior quality rootstock for C.oleifera breeding.
The relationships between IBS and perceptions of physical and mental health—a Norwegian twin study
Authors: Kutschke Julia , Harris Jennifer R. , Bengtson May-Bente
Published: May 2022

Background and aims

Poor quality of life is a main complaint among individuals with irritable bowel syndrome (IBS). Self-rated health (SRH) is a powerful predictor of clinical outcomes, and also reflects psychological and social aspects of life and an overall sense of well-being. This population-based twin study evaluates how IBS affects ratings of physical and mental health, and influences perceptions of hindrance of daily activity by physical or mental health. Further, we examine how IBS is related to these SRH measures.

Methods

The sample included 5288 Norwegian twins aged 40–80, of whom 575 (10.9%) suffer from IBS. Hierarchical regressions were used to estimate the impact of IBS on perceptions of health, before and after accounting for other chronic physical and mental health conditions. Two dimensions of SRH, physical and mental, and two aspects of functional limitations, the extent to which physical or mental health interferes with daily activities, were included as outcomes in separate models. Co-twin control analyses were used to explore whether the relationships between IBS and the four measures of SRH are causal, or due to shared genetic or shared environment effects.

Results

IBS was an independent predictor of poor self-rated physical health (OR = 1.82 [1.41; 2.33]), the size of this effect was comparable to that predicted by chronic somatic conditions. However, in contrast to somatic diseases, IBS was associated with the perception that poorer ratings of mental health (OR = 1.45 [1.02; 2.06]), but not physical health (OR = 1.23 [0.96; 1.58]), interfered with daily activity. The co‐twin control analyses suggest that causal mechanisms best explain the relationships between IBS with self-rated physical health and with hindrance of daily activities. In contrast, the relationship between IBS and self-rated mental health was consistent with shared genetic effects.

Conclusion

IBS is predictive of poor self-rated physical health. The relationship between IBS and self-rated mental health is best explained by shared genetic effects which might partially explain why mental health interferes with daily activity to a larger degree among those with IBS.
Prevalence of oral anticoagulant use among people with and without Alzheimer’s disease
Authors: Ali Babar Barkat , Vu Mai , Koponen Marjaana , Taipale Heidi , Tanskanen Antti , Kettunen Raimo , Tiihonen Miia , Hartikainen Sirpa , Tolppanen Anna-Maija
Published: May 2022

Background

Although cardio- and cerebrovascular diseases are common among people with Alzheimer’s disease (AD), it is unknown how the prevalence of oral anticoagulant (OAC) use changes in relation to AD diagnosis. We investigated the prevalence of OAC use in relation to AD diagnosis in comparison to a matched cohort without AD.

Methods

Register-based Medication use and Alzheimer’s disease (MEDALZ) cohort includes 70 718 Finnish people with AD diagnosed between 2005–2011. Point prevalence of OAC use (prescription register) was calculated every three months with three-month evaluation periods, from five years before to five years after clinically verified diagnosis and compared to matched cohort without AD. Longitudinal association between AD and OAC use was evaluated by generalized estimating equations (GEE).

Results

OAC use was more common among people with AD until AD diagnosis, (OR 1.17; 95% CI 1.13–1.22), and less common after AD diagnosis (OR 0.87; 95% CI 0.85–0.89), compared to people without AD. At the time of AD diagnosis, prevalence was 23% and 20% among people with and without AD, respectively. OAC use among people with AD began to decline gradually two years after AD diagnosis while continuous increase was observed in the comparison cohort. Warfarin was the most common OAC, and atrial fibrillation was the most common comorbidity in OAC users.

Conclusion

Decline in OAC use among people with AD after diagnosis may be attributed to high risk of falling and problems in monitoring. However, direct oral anticoagulants (DOACs) that are nowadays more commonly used require less monitoring and may also be safer for vulnerable people with AD.