bluuebunny/crossref_metadata_2025_split huggingface dataset:
Association between different diabetes medication classes and risk of Parkinson's disease in people with diabetes
Authors: Sunnarborg Katriina , Tiihonen Miia , Huovinen Marjo , Koponen Marjaana , Hartikainen Sirpa , Tolppanen Anna‐Maija 
Published: May 2022

AbstractPurposeDiabetes has been associated with increased risk of Parkinson's disease (PD). Diabetes medications have been suggested as a possible explanation, but findings have been inconsistent. More information on the role of exposure in different time windows is needed because PD has long onset. We assessed the association between use of different diabetes medication categories and risk of PD in different exposure periods.MethodsA case–control study restricted to people with diabetes was performed as part of nationwide register‐based Finnish study on PD (FINPARK). We included 2017 cases (diagnosed 1999–2015) with PD and 7934 controls without PD. Diabetes medication use was identified from Prescription Register (1995–2015) and categorized to insulins, biguanides, sulfonylureas, thiazolidinediones (TZDs), dipeptidyl peptidase 4 (DPP‐4) inhibitors, glucagon‐like peptide‐1 (GLP‐1) analogues and glinide. Exposure for each medication class was determined as none, at least 3 years before outcome and only within the three‐year lag time before PD outcome.ResultsThe use of insulins, biguanides, sulfonylureas, DPP‐4 inhibitors, GLP‐1 analogues or glinides was not associated with PD. Use of TZDs before lag time compared to non‐use of TZDs (adjusted odds ratio (OR) 0.78; 95% Confidence interval (CI) 0.64–0.95) was associated with decreased risk of PD.ConclusionsOur nationwide case–control study of people with diabetes found no robust evidence on the association between specific diabetes medication classes and risk of PD. Consistent with earlier studies, TZD use was associated with slightly decreased risk of PD. The mechanism for this should be verified in further studies.
Indication‐based timing of tracheostomy and its effects on outcome in the pediatric intensive care unit
Authors: Sachdev Anil , Gupta Neeraj , Singh Bhanu P. , Choudhari Nilay D. , Sharma Nikhil , Gupta Suresh , Gupta Dhiren , Chugh Parul 
Published: May 2022

AbstractObjectivesThe objective of study was to find an association between the timing of tracheostomy with duration of mechanical ventilation (MV) and length of stay (LOS) in pediatric intensive care unit (PICU) and hospital.MethodsThe data were collected prospectively from 2000 to 2018 and were analyzed retrospectively. Data included clinical diagnosis, indication, and duration (days) of MV, LOS in PICU and hospital before and after tracheostomy. Patients who did not receive MV or underwent MV for <24 h were excluded. According to the indication of tracheostomy enrolled patients were divided into four groups—airways anomalies (AA), central neurological impairment (CNI), cardiopulmonary insufficiency (CPI), and neuromuscular disorders (NMD). Patients in each group were divided into early (ET) and late tracheostomy (LT) category based on the median (interquartile range interquartile range [IQR]) days of pretracheostomy MV.ResultsTwo hundred and fifty six patients were analyzed. The frequency and median [IQR] days of pretracheostomy MV were ‐AA 54 [7(3,16)], CNI 120 [12(9,16)], CPI 51 [25(16.5,30.5)], and NMD 31[12(8,16.5)]. In AA patients, median (IQR) durations of posttracheostomy MV [2(1,5.2) versus 3.5(2,12); p = 0.032], PICU [7(5,8.2) versus11(7,18); p = 0.004] and hospital [12(9.7,21) versus 21.5(12,28); p = 0.027] stays were lower in ET as compared with LT group. Posttracheostomy MV duration was significantly short in ET patients with CNI and NMD (p < 0.005). The total days of MV, PICU and hospital stay were significantly lower in ET as compared with LT patients in all four groups (p < 0.01).ConclusionAs compared with LT, ET patient had shorter durations of total MV and PICU and hospital stay.
Patient safety in home care: A multicenter cross‐sectional study about medication errors and medication management of nurses
Authors: Strube‐Lahmann Sandra , Müller‐Werdan Ursula , Klingelhöfer‐Noe Jürgen , Suhr Ralf , Lahmann Nils Axel 
Published: May 2022

AbstractStudies assume that up to 30% of home care recipients are exposed to a possible medication error. For the home care sector, the study situation regarding such errors is limited. The aim of the study was to find out how often medication errors occur and whether they are related to training, quality assurance measures (use of the double‐check principle (DCP)), and other structural conditions of home care services. A cross‐sectional study was conducted, comprising 485 fully trained nurses of 107 randomly selected home care services. Potential influencing factors were analyzed in a multiple logistic regression model. Of 485 fully qualified nurses, 41.6% reported medication errors within a 12‐month period, while 14.8% did not answer this question. Nurses who had attended medication training within the last 2 years compared to a longer period (frequently to rather rarely applied DCP); the odds ratio of not making medication‐related errors was 1.79[1.42–3.09] (OR 3.13; [1.88–5.20]). Years of professional experience, amount of patients per shift, and type of work contract (full/part‐time) were not statistically significantly associated with reported medication errors. Medication‐related errors occur frequently in home care. Regular training and adequate quality management measures increase patient safety. Nursing managers and other responsible individuals of home care institutions have to make sure that nursing staff take part in regular medication training and apply the DCP when they give out medication in home care.
Inhibitory role of recombinant neorudin on canine coronary artery thrombosis
Authors: Liu Yu‐bin , Zhou Xing‐chen , Liu Yun , Zhang Lin , Zhou Ying , Xu Xiao , Zheng Can , Zhao Zhuan‐you , Wu Chu‐tse , Jin Ji‐de 
Published: May 2022

AbstractThe anticoagulant application is an effective treatment modality for cardiovascular diseases such as coronary heart disease, unstable angina pectoris, and myocardial infarction. In this study, the antithrombotic effect of recombinant neorudin (EPR‐hirudin, EH) was evaluated using a canine model of coronary artery thrombosis. A canine model with platelet thrombosis in the left circumferent branch of the coronary artery was designed using Folt's method, and the anti‐thrombus activity of EH was investigated. Femoral administration of EH intravenously had a significant dose‐dependent inhibitory effect on canine coronary artery thrombosis and the effective rates were 66.7% (p < .05), 83.3% (p < .05), and 100% (p < .01) after injection of 0.3, 1.0, and 3.0 mg/kg EH, respectively. Furthermore, EH demonstrated lower bleeding, with shorter bleeding time and less bleeding loss than low molecular weight heparin (LMWH). Under the similar effect intensity of EH and LMWH (85 IU/kg), the bleeding time of the EH group at 30 min was shorter, and the blood loss at 30–120 min was less than that of LMWH (p < .05 and p < .05–.001, respectively). EH had a significant dose‐dependent inhibitory effect in the dose range of 0.3–3.0 mg/kg on the coronary artery thrombosis and lower bleeding side effects than LMWH with a similar antithrombosis effect.
A high‐specificity aniline‐based mass tag for aldehyde detection
Authors: Mungalachetty Prisca , Kulkarni Pushkar , Wang Poguang , Giese Roger 
Published: May 2022

RationaleWe studied an aldehyde‐labeling reagent, N‐{2‐[(4‐aminophenoxy)methyl]benzyl}‐N,N‐diethylethanaminium bromide (CAX‐A), containing an aniline functional group for the detection of aldehydes with high specificity.MethodsSix standard aldehydes were labeled by CAX‐A and analyzed using LC‐ESI‐Orbitrap‐MS. The aldehydes (each 40 nmol) were derivatized with CAX‐A in the presence of sodium cyanoborohydride at room temperature overnight. The labeling reaction was applied to two urine samples for the detection of putative aldehydes.ResultsAll six standard CAX‐aldehyde derivatives were detected as precursor ions by dilution to 830 fmol/injection (signal‐to‐noise [S/N] ratio 587–1573). A total of 2184 MS1 features were detected overall in urine and blanks, of which 14 were putative aldehydes found only in urine.ConclusionsCAX‐A can provide three levels of specificity for aldehyde detection. First is the known labeling specificity of the aniline functional group for aldehydes, which we confirmed here by observing a significant peak only from the aldehyde (S/N = 3388) when a mixture of an aldehyde, a ketone (no peak), and a quinone (S/N = 2.3) was tested. Second is the ease of formation of an analyte‐characteristic first product ion (via anchimeric‐assisted loss of triethylamine as a neutral) in MS2 from a CAX‐labeled analyte. Third is the formation of a characteristic second product ion via loss of CO in MS3. CAX‐A enables the specific, convenient detection of putative aldehydes in urine.
Codesign method for event‐triggered control of a class of switched nonlinear systems
Authors: Cao Zhengbao , Zhao Jun 
Published: May 2022

AbstractThis article investigates the stability problem of a class of switched nonlinear systems by using the codesign of the switching law, the output feedback controller and the static output feedback based dynamic event‐triggered control (ETC). Each subsystem of such switched systems is allowed to be uncontrollable. The codesign method can not only guarantee asymptotic stability of the origin but also exclude Zeno behavior even if none of subsystems of the closed‐loop systems is stable and the switching can lead to the triggers instantaneously. A sufficient condition of using the above codesign method to ensure asymptotic stability without Zeno behavior is given. In addition, sufficient conditions of using the codesign of the output feedback controller and the static output feedback based dynamic ETC under arbitrary switching signals with dwell time for guaranteeing asymptotic stability and the positive lower bound of the interexecution times are developed even if the switching can result in the triggers instantaneously and some closed‐loop subsystems are still unstable. Further, sufficient conditions of using the codesign method to guarantee asymptotic stability without Zeno behavior under arbitrary switching signals with average dwell time are also developed. Finally, a numerical example is given to illustrate the effectiveness of the results.
Recognition of fruits and vegetables with similar‐color background in natural environment: A survey
Authors: Lv Jidong , Xu Hao , Xu Liming , Zou Ling , Rong Hailong , Yang Biao , Niu Liangliang , Ma Zhenghua 
Published: May 2022

AbstractFruit images collected by picking robots in natural environments have problems such as uneven lighting, complex backgrounds, occlusion of branches and leaves, and overlapping fruits and vegetables, which greatly increases the difficulty for picking robots to accurately identify target fruits and vegetables. Meanwhile, most fruits and vegetables have similar‐color backgrounds. Compared with the ones with different colors in the background, fruits and vegetables in similar‐color backgrounds are similar to the colors of their leaves and surrounding weeds, which increases the difficulty of identification. Therefore, realizing the accurate identification of fruits and vegetables in similar‐color backgrounds is vital to realize the dynamic monitoring of the growth of fruits and vegetables and intelligent picking, which has important value and application prospects for optimizing plantation management and automated harvesting operations. The work summarized the specific characteristics of fruits and vegetables with the close‐color background and the different processing procedures in the identification process. The following methods have been summarized, for example, image acquisition, image preprocessing, feature extraction, image segmentation, and fruit and vegetable detection in the process, and some methods were compared. Finally, the current research was discussed, and a solution was proposed for the different processing steps of fruit and vegetable recognition in similar‐color backgrounds. Deep learning methods were combined with some traditional methods to identify fruits and vegetables with close‐color background, which provides references for further research in various aspects.
Recent developments and applications of simultaneous localization and mapping in agriculture
Authors: Ding Haizhou , Zhang Baohua , Zhou Jun , Yan Yaxuan , Tian Guangzhao , Gu Baoxing 
Published: May 2022

AbstractSimultaneous Localization and Mapping (SLAM) is a process to use multiple sensors to position an unmanned mobile vehicle without previous knowledge of the environment, and meanwhile construct a map of this environment for the further applications. Over the past three decades, SLAM has been intensively researched and widely applied in mobile robot control and unmanned vehicle navigation. SLAM technology has demonstrated a great potential in autonomously navigating the mobile robot and simultaneously reconstructing the three‐dimensional (3D) information of surrounding environment. With the vigorous driving of sensor technology and 3D reconstruction algorithms, many attempts have been conducted to propose novel systems and algorithms combined with different sensors to solve the SLAM problem. Notably, SLAM has been extended to various aspects of agriculture involved with autonomous navigation, 3D mapping, field monitoring, and intelligent spraying. This paper focuses on the recent developments and applications of SLAM, particularly in complex and unstructured agricultural environment. A detailed summary of the developments of SLAM is given from three main fundamental types: light detection and ranging SLAM, Visual SLAM, and Sensor Fusion SLAM, and we also discuss the applications and prospects of SLAM technology in agricultural mapping, agricultural navigation, and precise automatic agriculture. Particular attention has been paid to the SLAM sensors, systems, and algorithms applied in agricultural tasks. Additionally, the challenges and future trends of SLAM are reported.
Danger from a distance: Executives' social distance and multinationals' responses to host‐country terrorist attacks
Authors: Liu Chang , Li Dan , Eden Lorraine , Lyles Marjorie A. 
Published: May 2022

AbstractResearch SummaryThis article examines whether and under what conditions multinational enterprises (MNEs) are likely to divest a subsidiary exposed to host‐country terrorist attacks. Drawing on construal level theory from social psychology, we propose that the association between subsidiaries' exposure to host‐country terrorist attacks and MNEs' likelihood of divesting these subsidiaries depends on their executives' social distance from the event host country. Based on a sample of Fortune US 100 MNEs and their foreign subsidiaries from 2003 to 2014, we find that on average, MNEs are more likely to divest their subsidiaries when their exposure to host‐country terrorist attacks increases; however, the effect is only prominent in host countries to which MNE executives are socially proximate.Managerial SummaryMNEs confronting terrorism threats in a host country sometimes respond by divesting subsidiaries exposed to the threats even when the high opportunity costs of divestment render this response irrational. We argue that the MNEs' divestment response may not be driven by rational economic calculations but by their executive’ subjective threat perceptions. We investigate how top executives’ subjective threat perceptions, as a function of their social distance from the event host country, influence MNEs’ divestment decisions. We find that on average, MNEs do tend to divest their subsidiaries when they are exposed to a high terrorism threat in a host country; however, they are much less likely to do so when their top executives are socially distant from the focal host country.
Towards practical application of mutation testing in industry — Traditional versus extreme mutation testing
Authors: Betka Maik , Wagner Stefan 
Published: May 2022

AbstractMutation testing is a technique that changes code instructions to assess the quality of automated software tests. Industry has not broadly adopted the technique because execution and analysis times are too long and not considered worth the effort. To change this, a variation called “extreme mutation testing” emerged, which mutates whole methods instead of instructions. The extreme variant trades accuracy for speed gains and also provides pre‐analyzed results. In this study, we aim to analyze both techniques on their granularity levels, look for benefits when combining them, and find motivations when a developer considers killing mutants. For that, we conducted a case study in a company from the semiconductor industry. We mutated a large Java software project which is tested by more than 11,000 unit tests, analyzed the results, manually inspected more than 1000 mutants, and conducted a focus group with five developers of the software. Among other results, we provide the distribution of traditional across extreme mutants as well as qualitative coding results of our mutant inspection and focus group transcript. We conclude that the traditional approach can be similarly strategically applied as the extreme one and that motivations of developers to target mutants are mostly not code related.
Success factors analysis for requirement elicitation in global software development paradigm: An empirical study
Authors: Yaseen Muhammad , Ali Sikandar , Mustapha Aida , Mazhar Nauman 
Published: May 2022

AbstractRequirement's elicitation is the process of gathering requirements from users, customers, and stakeholders using traditional or collaborative elicitation techniques. Software requirement gathering is a challenging task particularly in a Global Software Development (GSD) paradigm due to geographical distance, limited face to face meetings, time zone differences, and language and cultural barriers. As more companies begin to adopt GSD in order to save costs, the success factors need to be identified and evaluated in order to ensure a successful elicitation process. This paper offers an in‐depth analysis on success factors for requirement elicitation within GSD environment. First, all possible success factors are identified from the literature via a Systematic Literature Review (SLR). Next, these factors are evaluated by software industries via a questionnaire survey across different types and levels of experts, size of organizations, and from the client–vendor perspective. The relationships between the success factors and the survey results were evaluated using the Spearman's correlation coefficient. The results produced a 0.835 Spearman's correlation coefficient at significance level ρ = 0.000, which showed a strong positive correlation between the outcome of SLR and survey with no significant difference.
Development of a novel I‐beam to box column connection with welded steel plates
Authors: Twizere Moussa , Taşkın Kivanc 
Published: May 2022

SummaryBox steel columns have significant advantages compared with H‐columns. However, box steel columns have the detrimental tendency of developing a plastic hinge at the column panel zone due to stress concentration. One of the methods for moving the concentration of the stresses at the column panel zone is to use a reduced beam. Nevertheless, a reduced beam decreases the capacity of the beam. This paper proposes a solution to the plastic hinge location without reducing the capacity of the beam. In this study, 106 connection configurations were numerically investigated using ABAQUS software. Two relevant experimental studies were used to validate the modeling techniques. The proposed joint was classified as semi‐rigid and full strength according to Eurocode‐3. To predict the cyclic behavior of the proposed connection, analytical simulation was performed using a Matlab program that uses the Richard and Abbot function. The program was able to accurately reproduce the connection behavior. Through parametric studies, the influence of plate thickness, column, and beam geometry on the connection's initial stiffness and moment resistance was examined. Finally, by using regression analysis, linear functions capable of predicting the initial stiffness and moment resistance of the connection were proposed.
Alzheimer's disease drug development pipeline: 2022
Authors: Cummings Jeffrey , Lee Garam , Nahed Pouyan , Kambar Mina Esmail Zadeh Nojoo , Zhong Kate , Fonseca Jorge , Taghva Kazem 
Published: May 2022

AbstractIntroductionAlzheimer's disease (AD) represents a global health crisis. Treatments are needed to prevent, delay the onset, slow the progression, improve cognition, and reduce behavioral disturbances of AD. We review the current clinical trials and drugs in development for the treatment of AD.MethodsWe searched the governmental website clinicaltrials.gov where are all clinical trials conducted in the United States must be registered. We used artificial intelligence (AI) and machine learning (ML) approaches to ensure comprehensive detection and characterization of trials and drugs in development. We use the Common Alzheimer's Disease Research Ontology (CADRO) to classify drug targets and mechanisms of action of drugs in the pipeline.ResultsAs of January 25, 2022 (index date for this study) there were 143 agents in 172 clinical trials for AD. The pipeline included 31 agents in 47 trials in Phase 3, 82 agents in 94 trials in Phase 2, and 30 agents in 31 trials in Phase 1. Disease‐modifying therapies represent 83.2% of the total number of agents in trials; symptomatic cognitive enhancing treatments represent 9.8% of agents in trials; and drugs for the treatment of neuropsychiatric symptoms comprise 6.9%. There is a diverse array of drug targets represented by agents in trials including nearly all CADRO categories. Thirty‐seven percent of the candidate agents in the pipeline are repurposed drugs approved for other indications. A total of 50,575 participants are needed to fulfill recruitment requirements for all currently active clinical trials.DiscussionThe AD drug development pipeline has agents representing a substantial array of treatment mechanisms and targets. Advances in drug design, outcome measures, use of biomarkers, and trial conduct promise to accelerate the delivery of new and better treatments for patients with AD.Highlights
There are 143 drugs in the current Alzheimer's disease (AD) drug development pipeline.
Disease‐modifying therapies represent 83.2% of the candidate treatments.
Current trials require 50,575 participants who will donate 3,878,843 participant‐weeks to clinical trials.
The biopharmaceutical industry sponsors 50% of all clinical trials including 68% of Phase 3 trials.
Sixty‐three percent of Phase 3 trials and 46% of Phase 2 trials include non–North American clinical trial site locations indicating the global ecosystem required for AD drug development.