bluuebunny/crossref_metadata_2025 huggingface dataset:
Constrained self regulating particle swarm optimization
Authors: Shaikh Tayyab Ahmed , Hussain Rizvi Syed Sajjad , Tanweer Muhammad Rizwan
Published: April 2022

Self regulating particle swarm optimization (SRPSO) is a variant of particle swarm optimization (PSO) which has proved to be a very efficient algorithm for unconstrained optimization compared with other evolutionary algorithms (EAs) and utilized recently by the researchers for solving real-world problems. However, SRPSO has not been evaluated and analyzed for constrained optimization. In this work, SRPSO has been evaluated exhaustively for constrained optimization using the 24 constrained benchmark problems by coupling it with four efficient constraint handling techniques (CHTs). The results of constrained SRPSO algorithm have been compared with two other algorithms i.e. Differential evolution (DE) and PSO. DE and PSO have also been coupled with same four CHTs and evaluated on the 24 constrained benchmark problems. Statistical analysis on performance evaluation of three algorithms on the benchmark problems shows that constrained SRPSO algorithm performance is better than constrained PSO but it is found to be deficient when compared with constrained DE with 95% confidence level. Therefore, the objective of this work is to evaluate the SRPSO algorithm comprehensively for constrained optimization with different views to come up with suitability of constrained SRPSO algorithm when coupled with particular CHT for solving specific type of problems.
Classification improvement of gene expression for bipolar disorder using weighted sparse logistic regression
Authors: Ahmed Abdulnasir Younus , Kahya Mohammed Abdulrazaq , Altamir Suhaib Abduljabbar
Published: April 2022

The computer-aided diagnosis system plays an important role in the classification of diseases and genes such as psychological or other diseases. Bipolar disorder (BD) is a commond psychological disease nowdys. Genes that describe this type of disease may include irrelative values to bipolar disorder disease. These values may adversely impact the classification performance. Logistic regression (LR) and recently sparse logistic regression (SLR) were used as a common technique to solve such binary classification problems. Gene selection has been applied to be a successful technique to get better classification output by excluding the irrelative values of genes. In this work we go further in improving the classification accuracy by restoring to incorporating the weight of these genes utilizing integrating the standardization of T-test with the sparse logistic regression, aiming to accomplish high classification accuracy. A bipolar dataset of gene expressions measured for 22283 genes using Affymetrix technology was used. Two performance indicators; classification accuracy, and geometric-mean of specificity and sensitivity are considered in evaluating the proposed method. Experimental results show an improvement over the two competitor methods; SLR-smoothly clipped absolute deviation (SCAD) and SLR-lasso in three indicators: classification accuracy, geo-means, and area under the curve. Therefore, our technique is beneficial to predict and classify BD psychopaths.
A novel phosphor structure for improving the luminous flux of white LEDs
Authors: Thi Phuong Thao Nguyen , Nedoma Jan , Anh Vu Le , An Nguyen Thi Dieu , An Nguyen Thi Dieu
Published: April 2022

This section focuses on the color uniformity and luminous production of multi-chip white-emitted LED lighting systems (MCW-LEDs) in improving illuminated performance. To accomplish the desired outcome, CaO:Sb3+ must be mixed with their phosphor compounding, which has been shown to have a massive impact on illuminating effectiveness. There is also evidence that the increasing of yellowish-green-emitted phosphorus CaO:Sb3+ concentration supports color homogeneity as well as luminescent effectiveness enhancements in MCW-LEDs featuring a 8500 K correlating colour temperature (CCT). Meanwhile, that rise in CaO:Sb3+ concentration leads to the gradually deteriorating color quality scale. Thus, if appropriate concentration and particle size of CaO:Sb3+ phosphor are determined, it is not hard to obtain such an excellent presentation in color uniformity, color quality scale and luminescence of MCW-LEDs.
A compact four port MIMO antenna for millimeterwave applications
Authors: Naik Mohini Narendra , Virani Hasanali Gulamali
Published: April 2022

A novel compact microstrip MIMO antenna with high isolation and low envelope correction coefficient has been proposed and presented in this paper. The proposed antenna is compact in size with 3.22x4.86 mm2, operating over the frequency band of 60GHz. The MIMO antennas have been designed andsimulated using electromagnetic design and verification platformIE3DTM. Two ports MIMO antenna with the size of 3.22x1.93 mm2 resonates at 58.1 GHz covering a band of 57-59.3 GHz, with the bandwidth of 2.3 GHz, gain of 5.2 dBi, and directivity of 8.67 dBi. It also provides aninput reflection coefficient of -18.41 dB with isolation of -19.98 dB. Proposed four port MIMO antenna resonates at 58 GHz covering a range of 56.9 GHz to 59.2 GHz, with a bandwidth of 2.3 GHz, gain of 5.44 dBi, and the directivity of 9.75dBi. It provides goodisolationranging from -19 dB to -30 dB with input reflection coefficient of -18.09 dB. The envelope correlation coefficient (ECC) of the proposed four-port MIMO antenna is below 0.06 in far-field radiation characteristics. The proposed MIMO antenna has been analyzed for its diversity performance in terms of ECC, mean effective gain, and diversity gain.
Multimodal deep learning model for human handover classification
Authors: Monir Islam A , Fakhr Mohamed W. , El-Bendary Nashwa
Published: April 2022

Giving and receiving objects between humans and robots is a critical task which collaborative robots must be able to do. In order for robots to achieve that, they must be able to classify different types of human handover motions. Previous works did not mainly focus on classifying the motion type from both giver and receiver perspectives. However, they solely focused on object grasping, handover detection, and handover classification from one side only (giver/receiver). This paper discusses the design and implementation of different deep learning architectures with long short term memory (LSTM) network; and different feature selection techniques for human handover classification from both giver and receiver perspectives. Classification performance while using unimodal and multimodal deep learning models is investigated. The data used for evaluation is a publicly available dataset with four different modalities: motion tracking sensors readings, Kinect readings for 15 joints positions, 6-axis inertial sensor readings, and video recordings. The multimodality added a huge boost in the classification performance; achieving 96% accuracy with the feature selection based deep learning architecture.
The multimodal parameter enhancement of electroencephalogram signal for music application
Authors: Zahari Zarith Liyana , Mustafa Mahfuzah , Abdubrani Rafiuddin
Published: April 2022

Blinding of modality has been influenced decision of multimodal in several circumstances. Sometimes, certain electroencephalogram (EEG) signal is omitted to achieve the highest accuracy of performance. Therefore, the aim for this paper is to enhance the multimodal parameters of EEG signals based on music applications. The structure of multimodal is evaluated with performance measure to ensure the implementation of parameter value is valid to apply in the multimodal equation. The modalities’ parameters proposed in this multimodal are weighted stress condition, signal features extraction, and music class. The weighted stress condition was obtained from stress classes. The EEG signal produces signal features extracted from the frequency domain and time-frequency domain via techniques such as power spectrum density (PSD), short-time Fourier transform (STFT), and continuous wavelet transform (CWT). Power value is evaluated in PSD. The energy distribution is derived from STFT and CWT techniques. Two types of music were used in this experiment. The multimodal fusion is tested using a six-performance measurement method. The purposed multimodal parameter shows the highest accuracy is 97.68%. The sensitivity of this study presents over 95% and the high value for specificity is 89.5%. The area under the curve (AUC) value is 1 and the F1 score is 0.986. The informedness values range from 0.793 to 0.812 found in this paper.
A real-time data association of internet of things based for expert weather station system
Authors: Indrabayu Indrabayu , Areni Intan Sari , Bustamin Anugrayani , Irianty Rizka
Published: April 2022

The wind carries moisture into an atmosphere and hot or cold air into a climate, affecting weather patterns. Knowing where the wind is coming from gives essential insight into what kind of temperatures are to be expected. However, the wind is affected by spatial and temporal variabilities, thus making it difficult to predict. This study focuses on finding data associations from the weather station installed at Hasanuddin University Campus based on internet of things (IoT) using Raspberry Pi as a gateway that associated all the meteorological data from sensors. The generation of association rules compares the Apriori and FP-growth algorithms to determine relations among itemsets. The results show that high humidity and warm temperature tend to associate with a westerly wind and occur at night. In contrast, conditions with less humid and moderate temperatures tend to have southerly and southeasterly wind.
Breast cancer disease classification using fuzzy-ID3 algorithm based on association function
Authors: Idris Nur Farahaina , Ismail Mohd Arfian , Mohamad Mohd Saberi , Kasim Shahreen , Zakaria Zalmiyah , Sutikno Tole
Published: April 2022

Breast cancer is the second leading cause of mortality among female cancer patients worldwide. Early detection of breast cancer is considerd as one of the most effective ways to prevent the disease from spreading and enable human can make correct decision on the next process. Automatic diagnostic methods were frequently used to conduct breast cancer diagnoses in order to increase the accuracy and speed of detection. The fuzzy-ID3 algorithm with association function implementation (FID3-AF) is proposed as a classification technique for breast cancer detection. The FID3-AF algorithm is a hybridisation of the fuzzy system, the iterative dichotomizer 3 (ID3) algorithm, and the association function. The fuzzy-neural dynamicbottleneck-detection (FUZZYDBD) is considered as an automatic fuzzy database definition method, would aid in the development of the fuzzy database for the data fuzzification process in FID3-AF. The FID3-AF overcame ID3’s issue of being unable to handle continuous data. The association function is implemented to minimise overfitting and enhance generalisation ability. The results indicated that FID3-AF is robust in breast cancer classification. A thorough comparison of FID3-AF to numerous existing methods was conducted to validate the proposed method’s competency. This study established that the FID3-AF performed well and outperform other methods in breast cancer classification.
State of charge estimation of lithium-ion batteries using adaptive neuro fuzzy inference system
Authors: Chaoufi Imane , Abdelkhalek Othmane , Gasbaoui Brahim
Published: April 2022

A battery’s state of charge (SOC) is used to assess its residual capacity. It is a very important parameter for the control of the electric vehicle (EV). The objective of this paper is to estimate the SOC of a lithium-ion battery (LIB) using an adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN) because SOC of a battery must be estimated from measurable battery parameters such as current, voltage or temperature. Two intelligent SOC estimation methods are compared according to their suitability and accuracy. ANN estimation is more precise and perfectly represents the experimental data.
DistractNet: a deep convolutional neural network architecture for distracted driver classification
Authors: Nasri Ismail , Karrouchi Mohammed , Snoussi Hajar , Kassmi Kamal , Messaoudi Abdelhafid
Published: April 2022

Distracted driving has been considered one of the reasons for traffic accidents. The american national highway traffic safety administration (NHTSA) defines distracted driving as any activity that takes attention away from driving, such as doing makeup, texting, calling, and reaching behind. Most deaths, physical injuries, and economic losses could have been prevented if the distracted driver is alerted on time. This paper has proposed a new convolutional neural network (CNN) called DistractNet to detect drivers' distractions. The proposed model was trained and tested by state farm distracted driver detection image datasets available at Kaggle that contains images of drivers in the most common activities performed, which lead to distraction while driving divided into ten classes. Also, we have studied the performances of the proposed CNN model based on accuracy, training time, and model size. The performance of the proposed model was compared with four pre-trained networks such as ResNet-50, GoogLeNet, InceptionV3, and AlexNet using transfer learning techniques. The obtained experimental results show that the developed model-based CNN can achieve an overage accuracy of more than 99.32% with 93 min of training time and 7.99 MB of size. The extracted model can classify driver states into ten different classes with the predicted label and probability % for each class.
Intrusion prevention system using convolutional neural network for wireless sensor network
Authors: Chandre Pankaj Ramchandra , Mahalle Parikshit , Shinde Gitanjali
Published: April 2022

Now-a-days, there is exponential growth in the field of wireless sensor network. In wireless sensor networks (WSN’s), most of communication happen through wireless media hence probability of attacks increases drastically. With the help of intrusion prevention system, we can classify user activities into two categories, normal and suspicious activity. There is need to design effective intrusion prevention system by exploring deep learning for WSN. This research aims to deal with proposing algorithms and techniques for intrusion prevention system using deep packet inspection based on deep learning. In this, we have proposed deep learning model using convolutional neural network. The proposed model includes two steps, intrusion detection and intrusion prevention. The proposed model learns useful feature representations from large amount of labeled data and then classifies them. In this work, convolutional neural network is used to prevent intrusion for WSN. To evaluate and check the effectiveness of the proposed system, the wireless sensor network dataset (WSNDS) dataset is used and the tests are performed. The test results show that proposed system has an accuracy of 97% and works better than existing system. The proposed work can be used as future benchmark for the deep learning and intrusion prevention research communities.
Modeling of artificial neural networks for silicon prediction in the cast iron production process
Authors: Cardoso Wandercleiton , Di Felice Renzo , Dos Santos Bruna Nunes , Schitine Arthur Nascimento , Pires Machado Thiago Augusto , Sousa Galdino André Gustavo de , Morbach Dixini Pedro Vitor
Published: April 2022

The main way to produce cast iron is in the blast furnace. In the production of hot metal, the control of silicon is important. Alumina and silica react chemically with limestone and dolomite to form blast furnace slag. In this work, 12 artificial neural networks (ANNs) were modeled with different numbers of neurons in each hidden layer. The number of neurons varied between 10 and 200 neurons. ANNs were used to predict the silicon content of hot metal produced. The ANN with 30 neurons showed the best performance. In the test phase, the mathematical correlation was 97.5% and the mean square error (MSE) was 0.0006, and in the cross-validation phase, the mathematical correlation was 95.5% while the MSE was 0.00035.
Efficient de-noising technique for electroencephalogram signal processing
Authors: Dalal Virupaxi , Bhairannawar Satish
Published: April 2022

An electroencephalogram (EEG) is a recording of various frequencies of electrical activity in the brain. EEG signal is very useful for diagnosis of various brain related diseases at early stage to prevent severe issues which may lead to loss of life. The raw EEG signal captured through the leads contain different type of noises which is not susceptible for diagnosis. In this paper, an efficient algorithm is proposed to process the raw EEG signal to combat the noise. To obtain noiseless EEG data, the likelihood test ratio is applied to interference computation block. The likelihood ratio test converts EEG data signal into segmented data with nearly constant noise characteristics. This will aid in detecting the noise present in a tiny segment which ensures proper signal denoising. The processed signal is compared with the database of noiseless EEG of the same person using principal component analysis (PCA) classifier. The proposed algorithm is 99.01% efficient to identify and combat noise in the EEG signal.
Redesigning U-Net with dense connection and attention module for satellite based cloud detection
Authors: Kumthekar Aarti , Reddy Gudheti Ramachandra
Published: April 2022

In this paper, we present an upgraded U-Net technique for satellite-based cloud detection, with additional features, such as, more relevant spatial information, improvement in gradient propagation, feature reuse and controlling the network parameters using growth rate by adding dense connections. Furthermore, incorporation of attention module helps to learn strong inter-spatial and inter-channel relationships of feature maps by adding a few trainable parameters to the network. The two attention blocks namely position attention module (PAM) and channel attention module (CAM) focus on important parts of the image by neglecting the redundant information. The experimental results prove that the put forward technique with dense and attention modules could detect cloud with an accuracy of 95.69%.
Forward feature selection for toxic speech classification using support vector machine and random forest
Authors: Gumelar Agustinus Bimo , Yogatama Astri , Adi Derry Pramono , Frismanda Frismanda , Sugiarto Indar
Published: April 2022

This study describes the methods for eliminating irrelevant features in speech data to enhance toxic speech classification accuracy and reduce the complexity of the learning process. Therefore, the wrapper method is introduced to estimate the forward selection technique based on support vector machine (SVM) and random forest (RF) classifier algorithms. Eight main speech features were then extracted with derivatives consisting of 9 statistical sub-features from 72 features in the extraction process. Furthermore, Python is used to implement the classifier algorithm of 2,000 toxic data collected through the world's largest video sharing media, known as YouTube. Conclusively, this experiment shows that after the feature selection process, the classification performance using SVM and RF algorithms increases to an excellent extent. We were able to select 10 speech features out of 72 original feature sets using the forward feature selection method, with 99.5% classification accuracy using RF and 99.2% using SVM.
Mulheres e periferias como fronteiras: o tempo-espaço das moradoras do Conjunto Habitacional José Bonifácio (Coleção Caramelo Volume 2)
Authors:   Universidade de São Paulo. Faculdade de Arquitetura e Urbanismo, Freitas Carolina Alvim de Oliveira
Published: April 2022

O intuito deste livro, volume II da Coleção Caramelo é enxergar ligações, similaridades, evidências e causas comuns entre transformações – processos em movimento – tratadas frequentemente de maneira distinta e não associada às produções científicas. Estes processos são relativos, por um lado, às atividades sociais femininas na passagem do século 20 para o século 21, sua importância no âmbito da reestruturação capitalista, própria de uma era de “acumulação flexível”. O que se busca compreender aqui é sobre quais sentidos novos brotam das necessidades reprodutivas nesse contexto, e como são imputadas socialmente às mulheres combinações entre representações novas e tradicionais.
Time Found Footage: material de arquivo Proustiano editado reflexivamente.
Authors: Nader Carlos
Published: April 2022

Como toda obra que primeiro se debruça sobre temas essenciais da condição humana e que depois revela-se ela mesma também essencial para a condição humana, À La Recherche du Temps Perdu de Marcel Proust é milionária em paradoxos. Um deles, absolutamente periférico para a humanidade mas central para mim, é o fato de que por um lado a Recherche traz a receita mais extensa e exata do cinema que eu escolhi fazer e que, por outro, Proust sequer achava que o cinema fosse uma arte digna do nome.
Recycled Images: the Art and Politics of Found Footage Films
Authors: Wees William C.
Published: April 2022

Whatever the filmmaker may do to them — including nothing more than reproduce them exactly as he or she found them — recycled images call attention to themselves as images, as products of the image-producing industries of film and television, and therefore as pieces of the vast and intricate mosaic of information, entertainment, and persuasion that constitute the media-saturated environment of modern — or many would say, postmodern — life. By reminding us that we are seeing images produced and disseminated by the media, found footage films open the door to a critical examination of the methods and motives underlying the media's use of images.
O Roteiro de Sobras
Authors: Favre Michel
Published: April 2022

O entusiasmo geral que acompanhou a exposição do l’Elysée e a recente publicação de um livro, Fotoformas, contribuíram sem dúvida para a retomada, pelo artista, de um trabalho em fotografia. Além disso, em perfeita adequação com suas limitações físicas, decorrentes das inúmeras isquemias cerebrais que o deixaram com uma parte do corpo inválida, Geraldo conseguia desenvolver um trabalho artístico que lhe fosse possível: dirigia uma assistente que, segundo suas instruções, decupava negativos de família. O artista buscava esse material numa gaveta ao alcance da mão a partir da poltrona na qual passava a maior parte do tempo. Foi assim que, à sua maneira, ele se apropriou dos conceitos de restos, como se, no crepúsculo da vida, pudesse reciclar tudo, incluindo as lembranças da felicidade familiar. Iniciada em segredo em 1996, a série Sobras nascia, assim, do seu desejo, sempre presente, de criar apesar dos imprevistos da vida.
The IFNγ-PDL1 Pathway Enhances CD8T-DCT Interaction to Promote Hypertension
Authors: Benson Lance N. , Liu Yunmeng , Wang Xiangting , Xiong Yunzhao , Rhee Sung W. , Guo Yunping , Deck Katherine S. , Mora Christoph J. , Li Lin-Xi , Huang Lu , Andrews J. Tucker , Qin Zhiqiang , Hoover Robert S. , Ko Benjamin , Williams Ryan M. , Heller Daniel A. , Jaimes Edgar A. , Mu Shengyu
Published: April 2022

Background:

Renal T cells contribute importantly to hypertension, but the underlying mechanism is incompletely understood. We reported that CD8Ts directly stimulate distal convoluted tubule cells (DCTs) to increase NCC (sodium chloride co-transporter) expression and salt reabsorption. However, the mechanistic basis of this pathogenic pathway that promotes hypertension remains to be elucidated.

Methods:

We used mouse models of DOCA+salt (DOCA) treatment and adoptive transfer of CD8
+
T cells (CD8T) from hypertensive animals to normotensive animals in in vivo studies. Co-culture of mouse DCTs and CD8Ts was used as in vitro model to test the effect of CD8T activation in promoting NCC-mediated sodium retention and to identify critical molecular players contributing to the CD8T-DCT interaction. Interferon (IFNγ)-KO mice and mice receiving renal tubule-specific knockdown of PDL1 were used to verify in vitro findings. Blood pressure was continuously monitored via radio-biotelemetry, and kidney samples were saved at experimental end points for analysis.

Results:

We identified critical molecular players and demonstrated their roles in augmenting the CD8T-DCT interaction leading to salt-sensitive hypertension. We found that activated CD8Ts exhibit enhanced interaction with DCTs via IFN-γ-induced upregulation of MHC-I and PDL1 in DCTs, thereby stimulating higher expression of NCC in DCTs to cause excessive salt retention and progressive elevation of blood pressure. Eliminating IFN-γ or renal tubule-specific knockdown of PDL1 prevented T cell homing into the kidney, thereby attenuating hypertension in 2 different mouse models.

Conclusions:

Our results identified the role of activated CD8Ts in contributing to increased sodium retention in DCTS through the IFNγ-PDL1 pathway. These findings provide a new mechanism for T cell involvement in the pathogenesis of hypertension and reveal novel therapeutic targets.
Cardiac Resident Macrophage-Derived Legumain Improves Cardiac Repair by Promoting Clearance and Degradation of Apoptotic Cardiomyocytes After Myocardial Infarction
Authors: Jia Daile , Chen Siqin , Bai Peiyuan , Luo Chentao , Liu Jin , Sun Aijun , Ge Junbo
Published: April 2022

Background:

Cardiac resident macrophages are self-maintaining and originate from embryonic hematopoiesis. After myocardial infarction, cardiac resident macrophages are responsible for the efficient clearance and degradation of apoptotic cardiomyocytes (efferocytosis). This process is required for inflammation resolution and tissue repair; however, the underlying molecular mechanisms remain unknown. Therefore, we aimed to identify the mechanisms of the continued clearance and degradation of phagolysosomal cargo by cardiac resident macrophages during myocardial infarction.

Methods:

Multiple transgenic mice such as Lgmn
−/−
, Lgmn
F/F
; LysM
Cre
, Lgmn
F/F
; Cx3cr1
CreER
, Lgmn
F/F
; Lyve
Cre
, and cardiac macrophage Lgmn overexpression by adenovirus gene transfer were used to determine the functional significance of Lgmn in myocardial infarction. Immune cell filtration and inflammation were examined by flow cytometry and quantitative real-time polymerase chain reaction. Moreover, legumain (Lgmn) expression was analyzed by immunohistochemistry and quantitative real-time polymerase chain reaction in the cardiac tissues of patients with ischemic cardiomyopathy and healthy control subjects.

Results:

We identified
Lgmn
as a gene specifically expressed by cardiac resident macrophages. Lgmn deficiency resulted in a considerable exacerbation in cardiac function, accompanied by the accumulation of apoptotic cardiomyocytes and a reduced index of in vivo efferocytosis in the border area. It also led to decreased cytosolic calcium attributable to defective intracellular calcium mobilization. Furthermore, the formation of LC3-II–dependent phagosome around secondary-encountered apoptotic cardiomyocytes was disabled. In addition, Lgmn deficiency increased infiltration of MHC-II
high
CCR2
+
macrophages and the enhanced recruitment of MHC-II
low
CCR2
+
monocytes with downregulation of the anti-inflammatory mediators, interleukin-10, and transforming growth factor-β and upregulationof the proinflammatory mediators interleukin-1β, tumor necrosis factor-α, interleukin-6, and interferon-γ.

Conclusions:

Our results directly link efferocytosis to wound healing in the heart and identify Lgmn as a significant link between acute inflammation resolution and organ function.
Temporal Trends in the Remaining Lifetime Risk of Cardiovascular Disease Among Middle-Aged Adults Across 6 Decades: The Framingham Study
Authors: Vasan Ramachandran S. , Enserro Danielle M. , Xanthakis Vanessa , Beiser Alexa S. , Seshadri Sudha
Published: April 2022

Background:

The remaining lifetime risk (RLR) is the probability of developing an outcome over the remainder of one’s lifespan at any given age. The RLR for atherosclerotic cardiovascular disease (ASCVD) in three 20-year periods were assessed using data from a single community-based cohort study of predominantly White participants.

Methods:

Longitudinal data from the Framingham study in 3 epochs (epoch 1, 1960–1979; epoch 2, 1980–1999; epoch 3, 2000–2018) were evaluated. The RLR of a first ASCVD event (myocardial infarction, coronary heart disease death, or stroke) from 45 years of age (adjusting for competing risk of death) in the 3 epochs were compared overall, and according to the following strata: sex, body mass index, blood pressure and cholesterol categories, diabetes, smoking, and Framingham risk score groups.

Results:

There were 317 849 person-years of observations during the 3 epochs (56% women; 94% White) and 4855 deaths occurred. Life expectancy rose by 10.1 years (men) to 11.9 years (women) across the 3 epochs. There were 1085 ASCVD events over the course of 91 330 person-years in epoch 1, 1330 ASCVD events over the course of 107 450 person-years in epoch 2, and 775 ASCVD events over the course of 119 069 person-years in epoch 3. The mean age at onset of first ASCVD event was greater in the third epoch by 8.1 years (men) to 10.3 years (women) compared with the first epoch. The RLR of ASCVD from 45 years of age declined from 43.7% in epoch 1 to 28.1% in epoch 3 (
P
<0.0001), a finding that was consistent in both sexes (RLR [epoch 1 versus epoch 3], 36.3% versus 26.5% [women]; 52.5% versus 30.1% [men];
P
<0.001 for both). The lower RLR of ASCVD in the last 2 epochs was observed consistently across body mass index, blood pressure, cholesterol, diabetes, smoking, and Framingham risk score strata (
P
<0.001 for all). The RLR of coronary heart disease events and stroke declined in both sexes (
P
<0.001).

Conclusions:

Over the past 6 decades, mean life expectancy increased and the RLR of ASCVD decreased in the community-based, predominantly White Framingham study. The residual burden of ASCVD underscores the importance of continued and effective primary prevention efforts with better screening for risk factors and their effective treatment.
Percutaneous Transvalvular Microaxial Flow Pump Support in Cardiology
Authors: Lüsebrink Enzo , Kellnar Antonia , Krieg Kathrin , Binzenhöfer Leonhard , Scherer Clemens , Zimmer Sebastian , Schrage Benedikt , Fichtner Stephanie , Petzold Tobias , Braun Daniel , Peterss Sven , Brunner Stefan , Hagl Christian , Westermann Dirk , Hausleiter Jörg , Massberg Steffen , Thiele Holger , Schäfer Andreas , Orban Martin
Published: April 2022

The Impella device (Impella, Abiomed, Danvers, MA) is a percutaneous transvalvular microaxial flow pump that is currently used for (1) cardiogenic shock, (2) left ventricular unloading (combination of venoarterial extracorporeal membrane oxygenation and Impella concept), (3) high-risk percutaneous coronary interventions, (4) ablation of ventricular tachycardia, and (5) treatment of right ventricular failure. Impella-assisted forward blood flow increased mean arterial pressure and cardiac output, peripheral tissue perfusion, and coronary blood flow in observational studies and some randomized trials. However, because of the need for large-bore femoral access (14 F for the commonly used Impella CP device) and anticoagulation, the incidences of bleeding and ischemic complications are as much as 44% and 18%, respectively. Hemolysis is reported in as many as 32% of patients and stroke in as many as 13%. Despite the rapidly growing use of the Impella device, there are still insufficient data on its effect on outcome and complications on the basis of large, adequately powered randomized controlled trials. The only 2 small and also underpowered randomized controlled trials in cardiogenic shock comparing Impella versus intra-aortic balloon pump did not show improved mortality. Several larger randomized controlled trials are currently recruiting patients or are in preparation in cardiogenic shock (DanGer Shock [Danish-German Cardiogenic Shock Trial; NCT01633502]), left ventricular unloading (DTU-STEMI [Door-To-Unload in ST-Segment–Elevation Myocardial Infarction; NCT03947619], UNLOAD ECMO [Left Ventricular Unloading to Improve Outcome in Cardiogenic Shock Patients on VA-ECMO], and REVERSE [A Prospective Randomised Trial of Early LV Venting Using Impella CP for Recovery in Patients With Cardiogenic Shock Managed With VA ECMO; NCT03431467]) and high-risk percutaneous coronary intervention (PROTECT IV [Impella-Supported PCI in High-Risk Patients With Complex Coronary Artery Disease and Reduced Left Ventricular Function; NCT04763200]).
Management of Hypertension in Patients With Ventricular Assist Devices: A Scientific Statement From the American Heart Association
Authors: Eisen Howard J. , Flack John M. , Atluri Pavan , Bansal Neha , Breathett Khadijah , Brown Angela L. , Hankins Shelley R. , Khazanie Prateeti , Masri Carolina , Pirlamarla Preethi , Rowe Theresa ,   on behalf of the American Heart Association Heart Failure and Transplantation Committee of the Council on Clinical Cardiology; Council on Hypertension; and Council on Lifelong Congenital Heart Disease and Heart Health in the Young
Published: April 2022

Mechanical circulatory support with durable continuous-flow ventricular assist devices has become an important therapeutic management strategy for patients with advanced heart failure. As more patients have received these devices and the duration of support per patient has increased, the postimplantation complications have become more apparent, and the need for approaches to manage these complications has become more compelling. Continuous-flow ventricular assist devices, including axial-flow and centrifugal-flow pumps, are the most commonly used mechanical circulatory support devices. Continuous-flow ventricular assist devices and the native heart have a constant physiological interplay dependent on pump speed that affects pressure-flow relationships and patient hemodynamics. A major postimplantation complication is cerebrovascular vascular accidents. The causes of cerebrovascular vascular accidents in ventricular assist device recipients may be related to hypertension, thromboembolic events, bleeding from anticoagulation, or some combination of these. The most readily identifiable and preventable cause is hypertension. Hypertension management in these patients has been hampered by the fact that it is difficult to accurately measure blood pressure because these ventricular assist devices have continuous flow and are often not pulsatile. Mean arterial pressures have to be identified by Doppler or oscillometric cuff and treated. Although guidelines for hypertension management after ventricular assist device implantation are based largely on expert consensus and conventional wisdom, the mainstay of treatment for hypertension includes guideline-directed medical therapy for heart failure with reduced ejection fraction because this may reduce adverse effects associated with hypertension and increase the likelihood of favorable ventricular remodeling. The use of systemic anticoagulation in ventricular assist device recipients may at a given blood pressure increase the risk of stroke.
Tissue Sodium in Patients With Early Stage Hypertension: A Randomized Controlled Trial
Authors: Alsouqi Aseel , Deger Serpil Muge , Sahinoz Melis , Mambungu Cindy , Clagett Adrienne R. , Bian Aihua , Guide Andrew , Stewart Thomas G. , Pike Mindy , Robinson‐Cohen Cassianne , Crescenzi Rachelle , Madhur Meena S. , Harrison David G. , Ikizler Talat Alp
Published: April 2022

Background

Sodium (Na
+
) stored in skin and muscle tissue is associated with essential hypertension. Sodium magnetic resonance imaging is a validated method of quantifying tissue stores of Na
+
. In this study, we evaluated tissue Na
+
in patients with elevated blood pressure or stage I hypertension in response to diuretic therapy or low Na
+
diet.

Methods and Results

In a double‐blinded, placebo‐controlled trial, patients with systolic blood pressure 120 to 139 mm Hg were randomized to low sodium diet (<2 g of sodium), chlorthalidone, spironolactone, or placebo for 8 weeks. Muscle and skin Na
+
using sodium magnetic resonance imaging and pulse wave velocity were assessed at the beginning and end of the study. Ninety‐eight patients were enrolled to undergo baseline measurements and 54 completed randomization. Median baseline muscle and skin Na
+
in 98 patients were 16.4 mmol/L (14.9, 18.9) and 13.1 mmol/L (11.1, 16.1), respectively. After 8 weeks, muscle Na
+
increased in the diet and chlorthalidone arms compared with placebo. Skin sodium was decreased only in the diet arm compared with placebo. These associations remained significant after adjustment for age, sex, body mass index, systolic blood pressure, and urinary sodium. No changes were observed in pulse wave velocity among the different groups when compared with placebo.

Conclusions

Diuretic therapy for 8 weeks did not decrease muscle or skin sodium or improve pulse wave velocity in patients with elevated blood pressure or stage I hypertension.

Registration

URL:
https://www.clinicaltrials.gov
; Unique identifier: NCT02236520.
An Iatrogenic Injury? Anthony Eden and the Suez Crisis of 1956
Authors: Kernahan Peter J.
Published: April 2022

In 1953, Eden, then Britain’s Foreign Secretary, sustained a bile duct injury during a cholecystectomy. After reconstructive surgery at the Lahey Clinic, he continued to experience episodes of cholangitis, notably during the Suez Crisis of 1956. By then prime minister, the crisis ended in a humiliating retreat for Eden and for Britain. The role that his iatrogenic injury, its long term sequelae, and the cocktail of drugs he took to treat them played in his decision making has been an ongoing source of debate almost from the time of the crisis. This article reviews the Suez crisis, Eden's medical history, and the debate over Eden’s health.
Efficacy and Safety of Preoperative Radiotherapy Versus Chemoradiotherapy in Advanced Rectal Cancer: A Meta-analysis of Randomized Controlled Trials
Authors: Yu Miao , Wang Deng-Chao , Li Sheng , Huang Li-Yan , Wei Jian
Published: April 2022

Objective

This meta-analysis was conducted to evaluate the safety and efficacy of preoperative radiotherapy (RT) combined with surgery and preoperative chemoradiotherapy (CRT) combined with surgery for locally advanced rectal cancer.

Methods

PubMed, EMBASE and Cochrane Library were searched to collect published randomized controlled trials of preoperative radiotherapy or preoperative CRT combined with surgery for the treatment of locally advanced rectal cancer. Studies were screened according to inclusion and exclusion criteria, and quality was evaluated; RevMan 5.3 software was used for meta-analysis.

Results

In total, 7 related studies involving 3100 patients with locally advanced rectal cancer were evaluated. The pathological complete response rate, negative lymph node rate, R0 resection rate, and incidence of grade III/IV adverse reactions were lower in the RT group than in the CRT group. In the absence of postoperative chemotherapy, the 5-year local recurrence rate of RT was higher than that of CRT, but there was no significant difference between the groups among those who underwent postoperative chemotherapy. Moreover, there was no significant difference between the groups with regard to the 5-year survival rate, anal-preserving rate, or incidence of anastomotic leakage.

Conclusion

Preoperative CRT is better than preoperative RT for the treatment of advanced rectal cancer, though the adverse reaction rate is higher.
An Analysis of Traumatic and Non-Traumatic Hemopericardium Using Autopsy Data From a County Medical Examiner
Authors: Klutts Garrett , Kalkwarf Kyle , Meyer David , Yang Yijiong , Wolf Dwayne A. , Bhavaraju Avi , Margolick Joseph , Marino Katy , Robertson Ron , Drake Stacy A.
Published: April 2022

The volume of hemopericardium requiring hemodynamic changes in the trauma patient is not well understood. We performed a study using autopsy data from trauma patients who died with hemopericardium (>20 mL). Of 1848 traumatic deaths, 54 had hemopericardium at autopsy. The median pericardial blood in this group was 150 mL, which is more than the previously assumed volume to be lethal in trauma patients. Therefore, it may be appropriate to redefine the estimated volume required to cause lethal hemopericardium in trauma patients.
Use of a Multi-Sensor Monitoring Device in an Early Post-operative Mobilization Program
Authors: Restrepo Alexis , Saha Amit K. , Khanna Ashish K. , Huang Emily , Clark Clancy J.
Published: April 2022

Background

The current study aimed to evaluate the validity and feasibility of using a multi-sensor device to monitor patient mobility in a large postoperative population.

Methods

In this IRB-approved study, postoperative patient posture was recorded using a multi-sensor monitoring device (ViSi Mobile®) and compared with direct observations of patient physical activity. Retrospective cohort analysis of postoperative patient posture data from January to December 2019 was then performed. Patterns of postoperative mobilization were evaluated.

Results

Multi-sensor real-time posture monitoring with the ViSi Mobile® system consistently differentiate between rest and upright posture (sensitivity and specificity, both 100%). During observation of ambulatory events, ViSi Mobile® system correctly recorded a patient’s position as upright at each validation time point in 72.7% (8 of 11) of walks. Clinical data from 562 postoperative patients were linked with posture monitoring data. Median duration of posture monitoring was 64 hours (IQR 52.5) and median number of posture positions recorded per patient was 15,370 (IQR 12,685). Median duration of upright position per day was 148.6 minutes (IQR 192.8). Duration in active upright position per day was not associated with risk of readmission ( P > .05).

Conclusion

Real-time posture data from a multi-sensor monitoring device (ViSi Mobile®) was shown to consistently differentiate rest and active upright position. This novel technology can provide useful insight into adherence and clinical benefit of early mobilization programs.
Cannabis Use, Use Motives and Cannabis Use Disorder Among Berlin College Students
Authors: Naegele Helene , Betzler Felix , Viohl Leonard , Koslowski Michael , Ernst Felicitas , Petzold Moritz Bruno
Published: April 2022

This study described cannabis use behavior among college students in Berlin, in particular, differences in use motives between subjects with frequent use and those with signs of cannabis use disorder (CUD). Cross-sectional data were collected via an online survey among Berlin college students ( N=9350; 50.7% women; Mage=24.4). Motivation scales were computed based on an exploratory factor analysis. Effects of these motive scales were compared using multivariate regression models, where the dependent variable was use intensity (ordinal), frequent use (twice or more per week, binary) or a positive substance use disorder screening test (binary). Cannabis use is known to be particularly prevalent among Berlin college students, which was confirmed by our data. The most frequent use motive was enhancement, which, however, was not associated with frequent use or CUD. The motives predicting frequent use (sociability) are different from motives predicting CUD (coping), even when controlling for a wide array of covariates.
Personality disorders and forensic assessments: The benefits of ICD-11
Authors: Carroll Andrew , Walvisch Jamie , Marsh Tim
Published: April 2022

A recent landmark case in the Australian state of Victoria clariﬁed the ways in which personality disorders may be taken into account when the courts are sentencing convicted offenders. The ruling especially emphasised: the need for evidence to be ‘cogent’; the need to determine ‘severity’ of the personality disorder; the need to consider whether there is a ‘connection to the offending’; the need for caution when diagnoses are based solely on behaviour; and the need to consider rehabilitative prospects and community protection. The ruling has significant implications for how forensic experts in all jurisdictions might most effectively assist the courts with the task of sentencing offenders with personality disorders. In this paper we argue that the approach to diagnosis taken in the newly published ICD-11 manual, that eschews ‘categories’ of personality disorder, in favour of a dimensional model supported by trait theory, is of much greater utility to forensic mental health experts striving to address these issues, compared to traditional ‘categorical’ approaches.
The Use of Caregivers’ Smartphones to Assist Infants’ Circadian Sleep–Wake Cycles
Authors: Tange Akiko , Hayashi Mitsuo
Published: April 2022

Parents and caregivers lack knowledge regarding young children’s sleep routines due to an absence of general guidelines about sleep development, and this knowledge gap has been associated with infants’ sleep problems. Approximately 30% of infants develop sleep problems, including difficulty with falling asleep and night-waking. In this study, we sought to develop a new indicator of regularity in infants’ circadian sleep–wake patterns. Our participants were healthy Japanese mothers and their infants ( n = 172 infants; Mage = 4.9, SD = 3.5 months). Mothers used their smartphones to record the time when their infants fell asleep and woke up in their natural home environments over 7 days. We conducted least-squares spectrum analysis, a time-series analysis often used in chronobiology, to calculate the percentage variance (PVA) of the best-fitted cosine waves with a 24-hr periodicity in the infants’ sleep records. We found that the PVA of the 24-hr cycles in the infants’ sleep records were significantly correlated with the infants’ age in months ( r = 0.554, p < 0.001), variations in their waking-up ( r = −0.316, p < 0.001) and falling asleep times ( r = −0.430, p < 0.001), and sleep duration ( r = −0.343, p < 0.001). Apart from these normative data, which are of potential comparative use by other investigators, we showed in this study that PVA data can be collected by infants’ parents and caretakers through smartphones to provide parents an indicator of the regularity of an infant’s 24-hr periodicity.
Tourism and Mental Health: Foundations, Frameworks, and Futures
Authors: Buckley Ralf
Published: April 2022

Tourism contributes to mental health. We could: recognize, measure, value, and market those contributions; analyze components and design products to maximize mental health benefits; and use mental health benefits in tourism industry marketing and lobbying. If we measure benefits to health-research standards, then tourism could also gain commercial opportunities within the health sector. Currently, there are widely differing bodies of evidence within different tourism subsectors, reflecting historical research emphases. Music, museums, and shopping malls have been identified as therapeutic for some. Nature tourism therapies have been tested extensively, with a higher standard of evidence. Adventure tourism has been analyzed principally from a phenomenological perspective, indicating powerful psychological effects. Many mental health therapies require continuing behavioral change. Tourism research could contribute to these therapies, since it includes detailed data on the effects of program design and guiding, and individual personalities, interests, capabilities, motivations, experiences, emotions, and satisfaction.