Global Head Research Articles

Evaluating the Intracranial Pressure Biofidelity and Response Repeatability of a Physical Head-Brain Model in Frontal Impacts.

Headforms are widely used in head injury research and headgear assessment. Common headforms are limited to replicating global head kinematics, although intracranial responses are crucial to understanding brain injuries. This study aimed to evaluate the biofidelity of intracranial pressure (ICP) and the repeatability of head kinematics and ICP of an advanced headform subjected to frontal impacts. Pendulum impacts were performed on the headform using various impact velocities (1-5m/s) and impactor surfaces (vinyl nitrile 600 foam, PCM746 urethane, and steel) to simulate a previous cadaveric experiment. Head linear accelerations and angular rates in three axes, cerebrospinal fluid ICP (CSFP), and intraparenchymal ICP (IPP) at the front, side, and back of the head were measured. The head kinematics, CSFP, and IPP demonstrated acceptable repeatability with coefficients of variation generally being less than 10%. The BIPED front CSFP peaks and back negative peaks were within the range of the scaled cadaver data(between the minimum and maximum values reported by Nahum et al.), while side CSFPs were 30.9-92.1% greater than the cadaver data. CORrelation and Analysis (CORA) ratings evaluating the closeness of two time histories demonstrated good biofidelity of the front CSFP (0.68-0.72), while the ratings for the side (0.44-0.70) and back CSFP (0.27-0.66) showed a large variation. The BIPED CSFP at each side was linearly related to head linear accelerations with coefficients of determination greater than 0.96. The slopes for the BIPED front and back CSFP-acceleration linear trendlines were not significantly different from cadaver data, whereas the slope for the side CSFP was significantly greater than cadaver data. This study informs future applications and improvements of a novel head surrogate.

Improved Speech Emotion Recognition Using Channel-wise Global Head Pooling (CwGHP)

Improved Speech Emotion Recognition Using Channel-wise Global Head Pooling (CwGHP)

Effect of field strength on RF power deposition near conductive leads: A simulation study of SAR in DBS lead models during MRI at 1.5 T-10.5 T.

Since the advent of magnetic resonance imaging (MRI) nearly four decades ago, there has been a quest for ever-higher magnetic field strengths. Strong incentives exist to do so, as increasing the magnetic field strength increases the signal-to-noise ratio of images. However, ensuring patient safety becomes more challenging at high and ultrahigh field MRI (i.e., ≥3 T) compared to lower fields. The problem is exacerbated for patients with conductive implants, such as those with deep brain stimulation (DBS) devices, as excessive local heating can occur around implanted lead tips. Despite extensive effort to assess radio frequency (RF) heating of implants during MRI at 1.5 T, a comparative study that systematically examines the effects of field strength and various exposure limits on RF heating is missing. This study aims to perform numerical simulations that systematically compare RF power deposition near DBS lead models during MRI at common clinical and ultra-high field strengths, namely 1.5, 3, 7, and 10.5 T. Furthermore, we assess the effects of different exposure constraints on RF power deposition by imposing limits on either the B1+ or global head specific absorption rate (SAR) as these two exposure limits commonly appear in MRI guidelines. We created 33 unique DBS lead models based on postoperative computed tomography (CT) images of patients with implanted DBS devices and performed electromagnetic simulations to evaluate the SAR of RF energy in the tissue surrounding lead tips during RF exposure at frequencies ranging from 64 MHz (1.5 T) to 447 MHz (10.5 T). The RF exposure was implemented via realistic MRI RF coil models created based on physical prototypes built in our institutions. We systematically examined the distribution of local SAR at different frequencies with the input coil power adjusted to either limit the B1+ or the global head SAR. The MRI RF coils at higher resonant frequencies generated lower SARs around the lead tips when the global head SAR was constrained. The trend was reversed when the constraint was imposed on B1+. At higher static fields, MRI is not necessarily more dangerous than at lower fields for patients with conductive leads. Specifically, when a conservative safety criterion, such as constraints on the global SAR, is imposed, coils at a higher resonant frequency tend to generate a lower local SAR around implanted leads due to the decreased B1+ and, by proxy, E field levels.

BOOK REVIEW: Goals-Based Portfolio Theory by Franklin Parker

1. Paul Bouchey 1. is global head of research at Parametric and co-editor of The Journal of Wealth Management in Seattle, WA. (pbouchey{at}paraport.com) Reviewed by: Paul Bouchey It took the investment industry a while to realize that individual investors need to be treated differently from

Self-Supervised Global–Local Contrastive Learning for Fine-Grained Change Detection in VHR Images

Self-supervised contrastive learning (CL) can learn high-quality feature representations that are beneficial to downstream tasks without labeled data. However, most CL methods are for image-level tasks. For the fine-grained change detection (FCD) tasks, such as change or change trend detection of some specific ground objects, it is usually necessary to perform pixel-level discriminative analysis. Therefore, feature representations learned by image-level CL may have limited effects on FCD. To address this problem, we propose a self-supervised global–local contrastive learning (GLCL) framework, which extends the instance discrimination task to the pixel level. GLCL follows the current mainstream CL paradigm and consists of four parts, including data augmentation to generate different views of the input, an encoder network for feature extraction, a global CL head, and a local CL head to perform image-level and pixel-level instance discrimination tasks, respectively. Through GLCL, features belonging to different perspectives of the same instance will be pulled closer, while features of different instances will be alienated, which can enhance the discriminativeness of feature representations from both global and local perspectives, thereby facilitating downstream FCD tasks. In addition, GLCL makes a targeted structural adaptation to FCD, i.e., the encoder network is undertaken by the common backbone networks of FCD, which can accelerate the deployment on downstream FCD tasks. Experimental results on several real datasets show that compared with other parameter initialization methods, the FCD models pretrained by GLCL can obtain better detection performance.

Global Wheat Head Detection Challenges: Winning Models and Application for Head Counting.

Data competitions have become a popular approach to crowdsource new data analysis methods for general and specialized data science problems. Data competitions have a rich history in plant phenotyping, and new outdoor field datasets have the potential to embrace solutions across research and commercial applications. We developed the Global Wheat Challenge as a generalization competition in 2020 and 2021 to find more robust solutions for wheat head detection using field images from different regions. We analyze the winning challenge solutions in terms of their robustness when applied to new datasets. We found that the design of the competition had an influence on the selection of winning solutions and provide recommendations for future competitions to encourage the selection of more robust solutions.

Global Asymptotic Position and Heading Tracking for Multirotors Using Tuning Function-Based Adaptive Hybrid Feedback

This letter considers the problem of global asymptotic position and heading tracking for multirotors. We propose a hybrid adaptive feedback control law that globally asymptotically tracks a position and heading reference in the presence of unknown constant disturbances in both the translational and rotational dynamics. By employing a tuning function-based backstepping approach, the number of parameter estimates are minimized. Moreover, we propose a novel control law for the translational subsystem, which leads to a simpler virtual control law when backstepping. Global asymptotic heading tracking is achieved through a novel construction of the desired rotation matrix. The theory is verified through experiments on a quadrotor.

YOLOv5-Based Model Integrating Separable Convolutions for Detection of Wheat Head Images

In the detection of global wheat heads, it is easy to give rise to difficulties due to different wheat varieties, planting densities and growth periods of wheat plants in different countries. In addition, the illumination conditions of the image collection and the complex background of field will also reduce the detection accuracy. It is also hard to accurately detect targets that are occluded and partially displayed in the image. To solve the above problems, in this paper, an improved YOLOv5 algorithm that integrates separable convolution and attention mechanisms is proposed. Firstly, the number of CSP modules of YOLOv5 is reduced to shrink memory consumption. Subsequently, vanilla convolutions in the CSP are replaced by separable convolutions which is also added to the fusion path and to reduce the redundant information of the feature map, so as to reduce the complexity of the model. In addition, the co-attention mechanism is added in backbone. Finally, the feature fusion module was adjusted to make the high-level features fuse more low-level information. Compared with the original algorithm, results show that the mAP of the improved algorithm reaches 93.8% which is 4.2% higher than that of the YOLOv5 algorithm, and the FPS is 27.4 which is 1.3 higher than YOLOv5. YOLOv7 is emphatically compared during model evaluation, other YOLO series and mainstream detection algorithms are also compared, and results show that our model has the best inference time and the best accuracy when dealing with high pixel images.

Prof. Thomas Girst (Global Head of Cultural Engagement, BMW Group): in conversation

Prof. Thomas Girst (Global Head of Cultural Engagement, BMW Group): in conversation

Hallyu And Multitrack Diplomacy Of South Korea By Sm Entertainment

For the past decade, the spotlight of Pop culture global sensation head to South Korea, Hallyu, Korean Wave, known as South Korea’s public diplomacy which promotes Korean culture, start to spread in the mid-1990s and got bigger in 2000 with the boom of Korean Pop (K-Pop). As a tool of public diplomacy, Hallyu not only depends on the South Korean Government's direction but also encourages the private sector to take a part in promoting Korea culture. SM Entertainment (SME) as one of the big entertainment management in Korea also take a part, not only through the entertainment industry activity which is the main business but also in promoting public diplomacy through cooperation with Non-Government Organization (NGO) and supporting Saudi Arabia goverment. SME promotes Hallyu not only through regular public diplomacy also by applying multitrack diplomacy. Using the qualitative methods by applying the Multitrack diplomacy concept, this paper will explain how SME activity does not only reflect public diplomacy but is also part of the Multitrack diplomacy of the South Korean Government.

BLOODPAC: Collaborating to chart a path towards blood-based screening for early cancer detection.

BLOODPAC: Collaborating to chart a path towards blood-based screening for early cancer detection.

Deep learning method to assess brain injury risk

Model-based brain injury criteria can present higher potential to predict injury than global head kinematic parameters. Numerical head injury prediction tools are time consuming and require Finite Element (FE) skilled users. To address these difficulties, a deep learning technique was applied to an existing previously developed brain FE model for which an injury risk curve has been proposed in terms of maximum Von Mises stress to predict moderate diffuse axonal injury. A total of 4492 experimental head impacts coming from experimental helmet testing were considered as input for the analysis. Each input was expressed in terms of three linear accelerations and three angular velocities versus time, when the target metric was the time history Von Mises Stress () curve computed within the brain via the FE analysis. The architecture used for the Deep Learning (DL) model is the U-Net and four models based on it were evaluated. The dataset was split into three datasets dedicated for learning and testing. The quality of the DL models were assessed via the Maximum Absolute Error between FE and DL models computed brain maximum Further, a regression analysis of brain response with both methods was conducted. The results demonstrated that deep learning methods can be applied in the context of brain response estimation when helmet assessment is considered without any FE computation, only by considering the 6 D head kinematic vs time demonstrating that the deep learning approach should be further developed for research and industrial applications.

Transfer Learning Method for Object Detection Model Using Genetic Algorithm

This paper proposes a transfer learning method for an object detection model using a genetic algorithm to solve the difficulty of the conventional transfer learning of deep learning-based object detection models. The genetic algorithm of the proposed method can select the re-learning layers automatically in the transfer learning process instead of a trial-and-error selection of the conventional method. Transfer learning was performed using the EfficientDet-d0 model pre-trained on the COCO dataset and the Global Wheat Head Detection (GWHD) dataset, and experiments were conducted to compare fine-tuning and the proposed method. Using the training data and the validation data of the GWHD, we compare the mean average precision (mAP) of the models trained by the conventional and the proposed methods, respectively, on the test data of the GWHD. It is confirmed that the model trained by the proposed method has higher performance than the model trained by the conventional method. The average of mAP of the proposed method, which automatically selects the re-learning layer (≈0.603), is higher than the average of mAP of the conventional method (≈0.594). Furthermore, the standard deviation of results obtained by the proposed method is smaller than that of the conventional method, and it shows the stable learning process of the proposed method.

Manufacturing considerations underpinning viral and non-viral platform selection

With an ever-increasing range of viral and non-viral technologies available to advanced biotherapeutics developers, manufacturing considerations must play a key role in the decision-making process behind platform selection. These considerations include the current level of innovation in the bioprocessing toolkit and its corresponding capability to address the specific challenges facing individual technology areas.In this article a panel of experts spanning the lentiviral vector (LVV), exosome, and oncolytic virus fields discuss the impact of manufacturing considerations on their respective platform selection and ongoing product/process development strategies, comparing the state of the art in enabling technology in each application area, and discussing related challenges, needs, and opportunities.Allison Hagerman, P.Eng., PMP, MBTVice President, Product Development, Oncolytics BiotechA Professional Engineer focused on biotechnology, Ms. Hagerman joined Oncolytics in 2010 and has been integral to the progress of its product development program ever since. Prior to being appointed as Vice President of Product Development, Ms. Hagerman was the Director, Manufacturing and Engineering from 2013-2017 and Project Manager from 2010-2013, during which time she led the process performance qualification for pelareorep drug substance. Ms. Hagerman is a Professional Engineer (P.Eng., APEGA) and Project Management Professional (PMP, PMI). She holds a Master of Biomedical Technology (MBT) degree from the University of Calgary, and B.Sc. degrees in both Chemical Engineering and Biological Sciences. She is an accomplished equestrian and spends her spare time on horseback.Aaron NoyesVice President of Development, Codiak BiosciencesAaron is a Vice President of Integrated Drug Substance Development at Codiak BioSciences where he leads a team focused on developing scalable production processes for exosomes and robust technology to load varied payloads into exosomes. At the start of his industrial career, Aaron worked at Millipore before joining Wyeth Biopharma/Pfizer Biotech for 12 years where he developed purification processes and focused on scale-up of biologics, including mAbs, recombinant proteins, ADCs, vaccines, cell therapies, and viral vectors. Aaron received a B.S in Biochemistry from the University of Massachusetts at Amherst, a M.E in Biotechnology Engineering from Tufts University and an Engineering Doctorate in Biochemical Engineering at University College London.Laurens SierkstraSenior Director, Business Leader, Purification Thermo Fisher ScientificLaurens received his PhD in biotechnology in 1994 from the University of Utrecht after studying biology at the University of Leiden. He then joined Unilever as Project Manager and Unit Leader. In 2005, after the spinout of BAC BV from Unilever, he became CEO of BAC BV and set up the business in using single- domain antibodies for affinity purification, called CaptureSelect, which was sold in 2013 to Life Technologies. Since the acquisition by Thermo Fisher Scientific, he has been the business leader for the affinity purification business within the Bioproduction Division.Dr. Vladimir SlepushkinGlobal Head of Manufacturing, MedTherapy BiotechnologyDr. Vladimir Slepushkin is Global Head of Manufacturing at MedTherapy Biotechnology. He is leading all functions associated with manufacturing of CAR-T cells and viral vectors. Previously he was Executive Director of Vector Technology at Autolus Therapeutics, leading process development for manufacturing of lentivirus vectors in suspension cell culture, guiding assay development to support process de¬velopment for lentiviral vectors, managing CMO for GMP vector production and T-cell processing. Before that, Dr. Slepushkin was directing research vector core, and providing lentiviral, retroviral and AAV vectors for Kite Pharma. Vladimir proved successful in developing novel high-quality products by managing diverse technical groups and cross-functional teams, developing first-in-class clinical product from scratch, including facilities, equipment, manufacturing process, quality systems, regulatory CMC submissions and clinical trials design. He has proven expertise in technically understanding and leading the development and improvement of cell culture and purification processes, and operations and analytical methods, adhering to customer, regulatory, safety and environmental requirements and guidelines. Vladi¬mir is experienced in identifying and resolving regulatory and manufacturing technical problems, as well as intellectual property assessment and licensing. He has authored 61 scientific papers in peer-reviewed journals and he’s an author on 14 patents and patent applications.

Use of Brain Biomechanical Models for Monitoring Impact Exposure in Contact Sports

Head acceleration measurement sensors are now widely deployed in the field to monitor head kinematic exposure in contact sports. The wealth of impact kinematics data provides valuable, yet challenging, opportunities to study the biomechanical basis of mild traumatic brain injury (mTBI) and subconcussive kinematic exposure. Head impact kinematics are translated into brain mechanical responses through physics-based computational simulations using validated brain models to study the mechanisms of injury. First, this article reviews representative legacy and contemporary brain biomechanical models primarily used for blunt impact simulation. Then, it summarizes perspectives regarding the development and validation of these models, and discusses how simulation results can be interpreted to facilitate injury risk assessment and head acceleration exposure monitoring in the context of contact sports. Recommendations and consensus statements are presented on the use of validated brain models in conjunction with kinematic sensor data to understand the biomechanics of mTBI and subconcussion. Mainly, there is general consensus that validated brain models have strong potential to improve injury prediction and interpretation of subconcussive kinematic exposure over global head kinematics alone. Nevertheless, a major roadblock to this capability is the lack of sufficient data encompassing different sports, sex, age and other factors. The authors recommend further integration of sensor data and simulations with modern data science techniques to generate large datasets of exposures and predicted brain responses along with associated clinical findings. These efforts are anticipated to help better understand the biomechanical basis of mTBI and improve the effectiveness in monitoring kinematic exposure in contact sports for risk and injury mitigation purposes.

Modulation transfer functions for audiovisual speech.

Temporal synchrony between facial motion and acoustic modulations is a hallmark feature of audiovisual speech. The moving face and mouth during natural speech is known to be correlated with low-frequency acoustic envelope fluctuations (below 10 Hz), but the precise rates at which envelope information is synchronized with motion in different parts of the face are less clear. Here, we used regularized canonical correlation analysis (rCCA) to learn speech envelope filters whose outputs correlate with motion in different parts of the speakers face. We leveraged recent advances in video-based 3D facial landmark estimation allowing us to examine statistical envelope-face correlations across a large number of speakers (∼4000). Specifically, rCCA was used to learn modulation transfer functions (MTFs) for the speech envelope that significantly predict correlation with facial motion across different speakers. The AV analysis revealed bandpass speech envelope filters at distinct temporal scales. A first set of MTFs showed peaks around 3-4 Hz and were correlated with mouth movements. A second set of MTFs captured envelope fluctuations in the 1-2 Hz range correlated with more global face and head motion. These two distinctive timescales emerged only as a property of natural AV speech statistics across many speakers. A similar analysis of fewer speakers performing a controlled speech task highlighted only the well-known temporal modulations around 4 Hz correlated with orofacial motion. The different bandpass ranges of AV correlation align notably with the average rates at which syllables (3-4 Hz) and phrases (1-2 Hz) are produced in natural speech. Whereas periodicities at the syllable rate are evident in the envelope spectrum of the speech signal itself, slower 1-2 Hz regularities thus only become prominent when considering crossmodal signal statistics. This may indicate a motor origin of temporal regularities at the timescales of syllables and phrases in natural speech.

Disadvantaged Subgroups Within the Global Head and Neck Cancer Population: How Can We Optimize Care?

Within the global head and neck cancer population, there are subgroups of patients with poorer cancer outcomes independent from tumor characteristics. In this article, we review three such groups. The first group comprises patients with nasopharyngeal cancer in low- and middle-income countries where access to high-volume, well-resourced radiotherapy centers is limited. We discuss a recent study that is aiming to improve outcomes through the instigation of a comprehensive radiotherapy quality assurance program. The second group comprises patients with low socioeconomic status in a high-income country who experience substantial financial toxicity, defined as financial hardship for patients due to health care costs. We review causes and consequences of financial toxicity and discuss how it can be mitigated. The third group comprises older patients who may poorly tolerate and not benefit from intensive standard-of-care treatment. We discuss the role of geriatric assessment, particularly in relation to the use of chemotherapy. Through better recognition and understanding of disadvantaged groups within the global head and neck cancer population, we will be better placed to instigate the necessary changes to improve outcomes and quality of life for patients with head and neck cancer.

Can emergency avoidance behavior reduce injuries to electric two-wheeler riders in vehicle collisions?

Objectives The aim of this study was to examine the effects of emergency avoidance behaviors on the kinematics and injuries of electric two-wheeler (ETW) riders. Methods Four typical riding postures of ETW riders before collisions, including one normal posture and three avoidance postures, were identified through analysis of 298 videos of vehicle to ETW accidents. Crash simulations were then performed using the Total Human Model of Safety (THUMS) occupant model, ETW and a sedan finite element (FE) model, and the kinematics of ETW riders were compared. The risk of head injury and lower extremity injury was also investigated. Results When the struck foot position of the ETW rider was lower than the ETW pedal, the lower extremity was struck by the sedan bumper and ETW frame from the right and left side respectively, and the upper body of the rider rotated around the hood leading edge. At a car velocity of 40 km/h, the rider was at high risk of head injury and the tibia was fractured. The medial cruciate ligament (MCL) was ruptured in both the 20 km/h and 40 km/h collisions. When the struck foot position of the ETW rider was higher than the pedal, the lower extremity was hit by the bumper and then rebounded. In this situation, the bending moments of the femur and tibia, as well as the bending angle and shear displacement of the knee joint were less than the injury threshold in all crash simulations. Furthermore, when the head was turned toward the colliding car, the risk of head injury varied with the emergency avoidance posture. Conclusions The height of the struck foot relative to the ETW pedal influenced the rider’s global kinematics, and head and lower extremity injuries risk. In the struck side foot landing and both feet landing postures, the lower extremity was restrained and compressed by the ETW frame, resulting in a high risk of tibia fracture and MCL rupture. Reducing the impact velocities could effectively mitigate the injury risk of the ETW riders; however, loading patterns remain an important factor influencing the risk of lower extremity injury.

The Pandemic Supercharged Decentralized Trials, Now What?

The Pandemic Supercharged Decentralized Trials, Now What?

Improving the Resolution of International Tax Disputes

The dramatic increase in international trade and investments and related phenomena under the general heading of Globalization have multiplied the situations in which international tax disputes can arise, both between taxpayers and governments but also, and in some ways, more importantly, between governments themselves. These disputes may involve transfer pricing issues, differing income characterization rules, disagreement about the existence of a permanent establishment, or more generally, diverging views on the appropriate exercise of potential taxing rights by the source country jurisdiction and the corresponding obligation of the residence country to provide double tax relief.In the current circumstances, it seems inevitable that the frequency and complexity of international tax disputes will increase and, likewise, the need for some mechanism to solve them is increasingly important. This paper will review briefly the existing mechanisms for dealing with such disputes, looking at their structure and application, and then consider some of the current proposals to modify and improve the procedures, focusing principally on the work at the OECD.