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The energy finance sector is characterized by its complexity and volatility, driven by fluctuating commodity prices, regulatory changes and evolving market dynamics. Energy companies face financial, regulatory and operational risks, relying on historical data and static risk assessment frameworks that may not accurately reflect real-time market changes. This research aims to develop an energy finance risk compliance early warning system, leveraging a machine learning approach to enhance the early detection of compliance risks, enabling proactive decision-making and improving organizational resilience. Initially, data were collected from various sources, including historical financial records, market trends and regulatory frameworks. These data are essential for developing an early warning system that aims to enhance compliance risk detection in the energy sector. The collected data are preprocessed using cleaning and normalization and prepared for analysis. Exploratory Data Analysis (EDA) was conducted using statistical methods such as correlation analysis and regression analysis to identify patterns and relationships between variables. The study proposes a novel Revenue Optimizer with a weighted Support Vector Machine (RO-WSVM) model to enhance risk detection and ensure regulatory compliance in energy finance. Optimizing revenue while adhering to compliance standards provides proactive insights for effective risk management and decision-making. The result demonstrates that the application of the proposed RO-WSVM model works successfully and this is because RO-WSVM has higher accuracy (90%), error value (0.1%) and less time taken to process the data than any other model (6s). The study highlights that the innovative approach RO-WSVM enhances the prediction model in the finance risk compliance early warning of energy finance.

APAC drug delivery devices market to reach $5.4 billion in 2023.

Mergermarket released Global Pharma, Medical & Biotech trend report for Q3 2017.

Global BioLife develops breakthrough modified sugar.

Breakthrough noodle formula with low-glycemic score of 38.

Aphria ships first medical cannabis oil to Australia’s Medlab for clinical trial.

Envirotainer doubles e-technology capacity across Asia.

Genesis CancerCare Queensland is first in Asia-Pacific to use Elekta’s Venezia Brachytherapy Applicator.

iX Biopharma secures European patent for WaferiX drug delivery technology.

Shingrix approved in the US for prevention of shingles in adults aged 50 and over.

First three-monthly long-acting treatment for schizophrenia patients in Singapore.

China, Brazil and Russia named by healthcare companies as riskiest markets for compliance and regulation.

New survey shows patients in Asia Pacific fail to recognize their fragility fracture is due to osteoporosis.

Healthcare community join forces to fight growing epidemic of fragility fractures caused by osteoporosis.

This paper involves developing financial utility function that considers compliance to a certain qualitative characteristic and studies the impact on market equilibrium prices, should this criterion be Sharia compliance, fair-trade, environmental, social and governance principles or other ethical aspect. The goal is to show that individual utility can depend on other parameters than wealth and risk aversion, that therefore influence equilibrium market prices. This has been done by examining a possible utility function that takes into account individual sensitivity to the criterion and the intrinsic quality of compliance of this parameter. In order to prove the effectiveness of the proposed utility function, a simulation is made using agent-based approach with NetLogo platform. Upon examination of the impact of these parameters, it becomes clear that compliance to a qualitative characteristic would impact individual utility, supply and demand and result in equilibrium prices. This research highlights the importance of ethical arguments on individual decision making and how markets behave to this.

A mechanical mock of the cardiovascular system was used to simulate different conditions of ventricular-arterial mechanical matching. Four ventricles and four aortas with different elastances were set up, and all possible connection combinations tested by sampling ventricular and aortic pressures and flows. The mechanical energy produced by the simulated ventricles and the amount transferred to the aorta in the different connection conditions were calculated. The results demonstrate a clear dependence between the mechanical work production of the ventricles and the ventricular elastance (slope of the end-systolic pressure–volume relation) (from 20.42 ± 0.02 mJ/beat to 12.10 ± 0.02 mJ/beat), and an efficiency of energy transfer to the aorta strongly dependent on ventricular-aortic mechanical matching (from 56% to 20.7%). These results show that, even in optimal simulated conditions, only 56% of the energy produced is transferred to the load; and highlight the important role of mechanical aspects in conditions of very limited cardiovascular performance (i.e. final stages of heart failure), where energy transfer efficiency may be as low as 20.7%. This evidence emphasizes that the mechanical aspects must also be entertained in the evolution of complex cardiovascular pathologies, evaluating the possibility of combining mechanical and pharmaceutical interventions.

The thrombus is the inappropriate activation of hemostasis in vascular system. In this paper, biomechanical factors affecting the behaviors of artery with intraluminal thrombus were studies. Results indicated that heart rate and blood viscosity had strong impact on the compliance of the stenosis artery and flow pattern. The alteration in blood viscosity had stronger influence than cardiac cycle on the volume change of the fluid region surrounded by thrombus. von Mises stress measured at the thinnest region of the plaque had the largest time-averaged value. The alteration of these parameters could potentially lead to stress redistribution at intraluminal thrombus.

Understanding alveolar mechanics is important for preventing the possible lung injuries during mechanical ventilation. Alveolar clusters with smaller size are found having lower compliance in two-dimensional studies. But the influence of alveolar shape on compliance is unclear. In order to investigate how alveolar morphology affects their behavior, we tracked subpleural alveoli of isolated mouse lungs during quasi-static ventilation using two- and three-dimensional imaging techniques. Results showed that alveolar clusters with smaller size and more spherical shape had lower compliance. There was a better correlation of sphericity rather than circularity with alveolar compliance. The compliance of clusters with great shape change was larger than that with relatively slight shape change. These findings suggest the contribution of lung heterogeneous expansion to lung injuries associated with mechanical ventilation.

Cardiovascular diseases like atherosclerosis, peripheral arterial disease, coronary heart disease, etc. are dangerous and hence early detection of such diseases is important in the field of medical sciences. The existing methods used for diagnosing diseases are time-consuming and highly expensive. On the other hand, experimentation with Cardiovascular System (CVS) for the analysis and decision making for treatment is unsafe and hence it is important to develop an accurate CVS model. It is observed from the existing integer order cardiovascular models that the viscoelastic property of four chambers is not taken into consideration. To accommodate these properties, this paper proposes a fractional order model by introducing fractionality to the dynamical equation of CVS. Further, an optimization method is presented to obtain the fractionality of different chambers by minimizing the integral square error between clinical data of healthy human and model output using Cuckoo search, Firefly and Accelerated particle swarm algorithms. The results indicate that fractional models are better than integer order CVS models and specifically, the Firefly algorithm provides a better fractional model than the models obtained from other algorithms. Further, the best model obtained using firefly algorithm is considered for simulating the diseases (i) increased arterial stiffness and (ii) atherosclerosis.

This paper contains an adjustment of the stiffness and control algorithm of an ankle joint to maintain the posture of a humanoid biped walking robot using an IMU (Inertial measurement Unit) in single support phase. One of the difficulties in maintaining the balance of a robot in single support phase involves the sole of the robot, which is easy to separate from the ground. This phenomenon is caused by an external disturbance or when the sole lands on uneven terrain. A method of adjusting the compliance in the ankle joint is introduced to reduce the tendency of this type of occurrence. In order to maintain the posture of a robot with a compliant ankle joint, a posture controller composed of a body balancing controller and a vibration reduction controller is adopted. A walking experiment is implemented using a compliant ankle joint and the posture controller. The proposed method is shown to enable rapid walking as well as walking on uneven terrain.

Biomechanics research shows that the ability of the human locomotor system depends on the functionality of a highly compliant motor system that enables a variety of different motions (such as walking and running) and control paradigms (such as flexible combination of feedforward and feedback controls strategies) and reliance on stabilizing properties of compliant gaits. As a new approach of transferring this knowledge into a humanoid robot, the design and implementation of the first of a planned series of biologically inspired, compliant, and musculoskeletal robots is presented in this paper. Its three-segmented legs are actuated by compliant mono- and biarticular structures, which mimic the main nine human leg muscle groups, by applying series elastic actuation consisting of cables and springs in combination with electrical actuators. By means of this platform, we aim to transfer versatile human locomotion abilities, namely running and later on walking, into one humanoid robot design. First experimental results for passive rebound, as well as push-off with active knee and ankle joints, and synchronous and alternate hopping are described and discussed. BioBiped1 will serve for further evaluation of the validity of biomechanical concepts for humanoid locomotion.

Enhancing energy efficiency of bipedal walking is an important research problem that has been approached by design of recently developed compliant bipedal robots such as CoMan. While compliance leads to energy efficiency, it also complicates the walking control system due to further under-actuated degrees of freedom (DoF) associated with the compliant actuators. This problem becomes more challenging as the constrained motion of the robot in double support is considered. In this paper this problem is approached from a multi-variable geometric control aspect to systematically account for the compliant actuators dynamics and constrained motion of the robot in double support phase using a detailed electro-mechanical model of CoMan. It is shown that the formulation of constraint subspace is non-trivial in the case of non-rigid robots. A step-wise numerical algorithm is provided and the effectiveness of the proposed method is illustrated via simulation, using a ten DoF model of CoMan.

Compliance control is highly relevant to human safety in human–robot interaction (HRI). This paper presents a review of various compliance control techniques. The paper is aimed to provide a good background knowledge for new researchers and highlight the current hot issues in compliance control research. Active compliance, passive compliance, adaptive and reinforcement learning-based compliance control techniques are discussed. This paper provides a comprehensive literature survey of compliance control keeping in view physical human robot interaction (pHRI) e.g., passing an object, such as a cup, between a human and a robot. Compliance control may eventually provide an immediate and effective layer of safety by avoiding pushing, pulling or clamping in pHRI. Emerging areas such as soft robotics, which exploit the deformability of biomaterial as well as hybrid approaches which combine active and passive compliance are also highlighted.

Compliance control is highly relevant to human safety in human–robot interaction (HRI). This paper presents multi-dimensional compliance control of a humanoid robot arm. A dynamic model-free adaptive controller with an anti-windup compensator is implemented on four degrees of freedom (DOF) of a humanoid robot arm. The paper is aimed to compliment the associated review paper on compliance control. This is a model reference adaptive compliance scheme which employs end-effector forces (measured via joint torque sensors) as a feedback. The robot's body-own torques are separated from external torques via a simple but effective algorithm. In addition, an experiment of physical human robot interaction is conducted employing the above mentioned adaptive compliance control along with a speech interface. The experiment is focused on passing an object (a cup) between a human and a robot. Compliance is providing an immediate layer of safety for this HRI scenario by avoiding pushing, pulling or clamping and minimizing the effect of collisions with the environment.

Most robots are today controlled as being entirely rigid. But often, as for HRP-2 robot, there are flexible parts, intended for example to absorb impacts. The deformation of this flexibility modifies the orientation of the robot and endangers balance. Nevertheless, robots have usually inertial sensors inertial measurement units (IMUs) to reconstruct their orientation based on gravity and inertial effects. Moreover, humanoids have usually to ensure a firm contact with the ground, which provides reliable information on surrounding environment. We show in this study how important it is to take into account these information to improve IMU-based position/orientation reconstruction. We use an extended Kalman filter to rebuild the deformation, making the fusion between IMU and contact information, and without making any assumption on the dynamics of the flexibility. We show how, with this simple setting, we are able to compensate for perturbations and to stabilize the end-effector's position/orientation in the world reference frame. We show also that this estimation is reliable enough to enable a closed-loop stabilization of the flexibility and control of the center of mass (CoM) position with the simplest possible model.

When executing tasks, robots are required to demonstrate compliance to unexpected external disturbances or human–robot interactions, and return to the demanded posture when the disturbances or contacts are removed. Traditional Virtual Model Control (VMC) requires precise gravitational compensation to accurately control the posture of a robot. Hence, load variations or other uncertain unmodeled factors in the robot will result in offsets to its balance posture, which makes the robot deviate from the demanded posture when it is in a static state. To reject this offset without sacrificing the compliance of the robot, an adaptive controller is proposed in this paper to implement adaptive compliance on the robot, which makes the robot robust to the variations in gravitational loads in the double leg support phase. The adaptive controller is a combination of the VMC controller and an online gravitational loads estimator, in which the estimator is derived in the double leg support phase to estimate the values of these parameters and obtains an online updating law based on a Kalman optimal estimator. Then, a Lyapunov function is designed to modify and combine the controller and the online gravitational loads estimator. The experiments are conducted on a 4 DoF bipedal robot in the sagittal plane to validate the effectiveness of the controller and show that, by estimating the gravitational loads of the robot, the effects of load variations on balance posture are rejected without sacrificing compliance.

Joints’ backdrivability is desired for robots that perform tasks contacting the environment, in addition to the high torque and fast response property. The electro-hydrostatic actuator (EHA) is an approach to realize force-sensitive robots. To experimentally confirm the performance of a biped robot driven by EHAs, we developed the fully electro-hydrostatically driven humanoid robot Hydra. In this paper, we evaluate the whole-body control performance realized by integrating encoders, pressure sensors, and IMU through a high-speed communication bus to the distributed whole-body control system. We report the first example of bipedal locomotion by an EHA-driven robot in both position-controlled and torque-controlled approaches. The robot could keep the balance even when the ground condition was changing impulsively and utilize its high joint backdrivability to absorb a disturbance by the null space compliance. We also report practical challenges in implementing compliant control in real hardware with limitations in parameter accuracy, torque, and response. We experimentally confirmed that the resolved viscoelasticity control (RVC), which has indirect feedback of operational space tasks by projecting the operational space feedback gain to the joint space one, was effective to tune a proper gain to stabilize the center-of-mass motion while avoiding joint-level oscillation invoked by the control bandwidth limitation. The attached multimedia file includes the video of all experiments presented in the paper.

Background: Improvements for knee osteoarthritis (OA) care models are carried out widely. Yet, patient attendance behaviours in present care models are not fully understood, without the readily available localised evidence.

Objective: Hence, we examined the relationships of patient-specific factors with the physiotherapy attendance for patients with knee OA.

Methods: A retrospective, cohort study was conducted. Primary data from a randomised controlled trial of a community-based, individualised, multidisciplinary programme for patients with knee OA was analysed. Patient-specific factors like demographics, medical factors, self-reported knee function, physical function testing, activity levels and psychological factors were considered. We ran multiple ordered logistic models to examine the relationships between these factors and patients’ physiotherapy attendance.

Results: We found that factors like gender, BMI, pain during physical function, previous knee injections and psychological symptoms were associated with the physiotherapy attendances of patients with knee OA.

Conclusion: There’s evidence to suggest that patient-specific factors are associated with different levels of physiotherapy attendance among the patients with knee OA. Our results further the understanding of physiotherapy attendance patterns of patients with knee OA, and reinforces the need to consider these factors when developing informed treatment strategies that optimises the physiotherapy attendance of these patients.

An unregulated Environmental Control Officer (ECO) industry is currently validating compliance to sustainability commitments made during the Environmental Impact Assessment (EIA) process of projects across South Africa. This paper follows an action research routine and explores the need and drivers for regulating professionalism of this industry. A self-administered survey questionnaire and interviews were used to generate empirical data from environmental practitioners. A total of 171 survey questionnaires were completed, and four interviews were conducted with key stakeholders. The data gathered were analysed and categorised in relation to theoretical perspectives on drivers for regulating verification professions within the context of attributes (or criteria) of a profession. To achieve the transition from an occupation to a profession, a six-step process is laid out tailored to meet the needs of the industry. This paper provides international environmental practitioners with insight to the need for regulating environmental verification industries such as ECOs.

A major challenge for many countries is the implementation of environmental regulations developed to reduce or eliminate air, water, and other pollutants. Recent efforts to ensure value for money in environmental protection, examine how to improve regulatory design, compliance promoting, and regulatory enforcement to deter and prevent regulatory violation. Work in accountability mechanisms such as performance audits have helped identify regulatory implementation issues. Opportunity exits to supplement traditional compliance promotion with new environmental data sources, including from citizen science.

Using unique data on chemical manufacturing facilities regulated under the Clean Water Act (CWA), this paper analyzes the effect of one particular environmental management practice — internal monitoring — on regulated facilities’ compliance with wastewater discharge limits. To deepen our understanding of the role played by internal monitoring, we extend our analysis by exploring the interaction between internal monitoring and self-audits, which should share a similar purpose to internal monitoring by providing systematic information to regulated facilities on their pollution abatement efforts. Baseline empirical results robustly demonstrate that increases in the extent of internal monitoring significantly improve facilities’ environmental compliance. The extended empirical results offer moderate evidence that audits complement internal monitoring (and vice versa): as facilities audit more frequently, the productive effect of increased internal monitoring grows.

The Group of Twenty (G20) was created first at the ministerial level and later upgraded to the summit level as a response to the global financial crises that first erupted from Asia in 1997, and then from the US in 2008 and Europe in 2010. These crises called into question the core principles and practices of the liberal order based on the economic, social and political openness that had been progressively internationally institutionalized since 1944. The G20 was designed with a dual distinctive foundational mission to promote financial stability and to make globalization work for all. It combined all established and emerging economies with high capability and connectivity, to operate as equals, to protect all within their borders and those beyond. It increasingly did so since its first summit in 2008. Its performance spiked at the summit in Hangzhou, China, on 3–4 September, 2016, and again at Hamburg, Germany, on 7–8 July, 2017. The latter coped with the new populist, protectionist US president and UK prime minister, whose countries had hosted the first three summits. G20-supported initiatives and agreements for full free trade have advanced since the first summit in 2008. No other center of global summit governance has emerged to guide an increasingly globalized world. The G20 has also steadily become an effective governor of global security. As the forces that propelled this rise will intensify, the Argentinian-hosted G20 summit on 30 November–1 December, 2018, promises to proceed along this path. It is guided by a country again afflicted by a financial crisis but now dedicated to following the core liberal order and making it work better for all. The real test will arrive in 2019, when Japan as host must co-operate with Korea and China, its neighbouring Asian powers and previous G20 hosts, to provide a new center of inclusive, progressive, liberal global governance that the world badly needs.