Environmental Manipulations Research Articles

A Pilot Study Exploring Practices that Support the Longevity of Community Gardens Supported by Religious Organizations.

The online version contains supplementary material available at 10.1007/s42822-023-00124-7.

A STUDY OF RISK FACTORS OF DELIRIUM TREMENS IN PERSONS WITH ALCOHOL USE DISORDER IN A TERTIARY CARE HOSPITAL.

Introduction: Delirium tremens is the severe form of alcohol withdrawal state that carries a certain degree of mortality. It is important to understand various risk factors associated with delirium tremens and compare with persons in alcohol withdrawal without delirium tremens. Objectives of the Study is to identify various risk factors associated with delirium tremens and to compare and identify any differences in risk factors for withdrawal syndrome in persons with alcohol use disorder with and without delirium tremens. This cross-sectional study Methodology: was conducted in the Department of Psychiatry at Hamdard Institute of Medical Science and HAHC Hospital, New Delhi on the patients with alcohol use disorder in withdrawal attending Department of Psychiatry, during period from January 2022 to June 2022. 75 patients with alcohol use disorder were taken. They were further categorised into 3 groups of patients which included patients with alcohol use disorder experiencing uncomplicated withdrawal, complicated withdrawal with or without delirium tremens. Patients with age range 18-60 years of either sex with illness of at least 12 months were taken. Severity of withdrawal was assessed by CIWA-Ar (Clinical Institute for Withdrawal of Alcohol scale containing ten items). Data was analysed using computer-based software (SPSS v16). Mean scores were calculated for both study populations for all the scales applied. Chi square test was used to make in between group comparisons for categorical variables with P value less than 0.05 was considered statistically signicant at 95 % condence level. Among the 75 patients Results: admitted for detoxication treatment during the period of January 2022- June 2023; 9 of the participants were suffering from uncomplicated withdrawal, 13 participants were suffering from complicated withdrawal without delirium tremens and 53 participants was suffering from complicated withdrawal with delirium tremens The factors signicantly associated with delirium tremens were previous history of DT (p=0.004**), binge drinking pattern (p=0.000**), history of morning alcohol consumption (p=0.000*), and delay in hospitalization (p=0.004**), and increased CIWA- AR score (p=0.001**). Patient admitted Conclusion: for detoxication should be carefully evaluated for these risk factors; and the vulnerable subjects with the presence of these risk factors should be cautiously managed and carefully monitored by the nurses taking care of these patients to prevent the occurrence of the fatal complication associated with alcohol withdrawal syndrome. Environmental manipulation, close observation and monitoring of vital signs, front loading dose of benzodiazepines are essential for preventing the occurrence of Delirium tremens during detoxication period.

Review: Manipulation of follicle development to improve fertility of cattle in timed-artificial insemination programs.

The development of an ovulatory follicle is a fundamental premise for any reproductive management program that aims to optimize fertility in cattle. Controlling follicular development comprises the synchronized emergence of a new follicular wave, selection and growth of the dominant follicle, and synchronized ovulation of a high-quality oocyte. All these follicular events, primarily driven by gonadotropin secretion, occur under a very dynamic hormonal environment. In this sense, controlling follicular development demands essentially a precise manipulation of the hormonal environment to modulate gonadotropin secretion. Furthermore, the effectiveness of hormonal manipulation strategies in the management of follicular development depends on specific particularities of each situation, which can vary widely according to genetic groups (Bos taurus vs Bos indicus), nutritional, metabolic, and reproductive status. In this regard, the constant search for the refined synchrony between the hormonal treatments and reproductive events, considering these distinctions and particularities, have provided valuable information that contributed to the development of efficient reproductive programs. This manuscript discusses the physiological bases behind the development of fine-tuned timed-artificial insemination protocols for beef and dairy cattle that resulted in great improvements in reproductive efficiency of beef and dairy herds.

Insights into biohydrogen production from algal biomass: Challenges, recent advancements and future directions

Detrimental greenhouse gases (GHGs) emissions producing conventional sources of energy are needed to be replaced with eco-friendly and renewable energy sources. Researchers have strongly highlighted biohydrogen is an alternate source of high-energy for alleviating the energy crisis due to its having energy content 2.75 times higher than that of fossil fuels. In addition, the fuel known for leaving no trails of harmful emissions by combustion and emits only water as a by-product. Algal biomass has emerged as a potential feedstock for biohydrogen production. The objectives of the present article is to illustrate the various ways of algal biohydrogen production along with mechanisms and challenges of biohydrogen production in which factors controlling the hydrogen production process and challenges in the economic aspect, technical aspect and storage are considered. Future road map of biohydrogen from algae is also delineated in view of decarbonization pathway and respective SWOT analysis pointing strength, weakness, opportunities and threats. Key strength of algal biohydrogen is identified as excellent carbon capture and waste valorization capability of algae to promote zero-waste circular bioeconomy. Along with these, some weaknesses of this biological approach include technological hinderances leading low biohydrogen yield and high initial cost investment. Implementing genetic/metabolic or environmental manipulations has shown promising opportunity to improve algal biohydrogen to ensure long-term sustainability. Cascading effects of technological immaturity followed by lack of credibility even after suggested alterations are few of threats that need to be superintended by optimizing operational parameters, metabolic engineering, etc.

Modulating chronic outcomes after pediatric traumatic brain injury: Distinct effects of social and environmental enrichment

Impairments in social and cognitive function are a common consequence of pediatric traumatic brain injury (TBI). Rehabilitation has the potential to promote optimal behavioral recovery. Here, we evaluated whether an enhanced social and/or cognitive environment could improve long-term outcomes in a preclinical model of pediatric TBI. Male C57Bl/6 J mice received a moderately-severe TBI or sham procedure at postnatal day 21. After one week, mice were randomized to different social conditions (minimal socialization, n = 2/cage; or social grouping, n = 6/cage), and housing conditions (standard cage, or environmental enrichment (EE), incorporating sensory, motor, and cognitive stimuli). After 8 weeks, neurobehavioral outcomes were assessed, followed by post-mortem neuropathology. We found that TBI mice exhibited hyperactivity, spatial memory deficits, reduced anxiety-like behavior, and reduced sensorimotor performance compared to age-matched sham controls. Pro-social and sociosexual behaviors were also reduced in TBI mice. EE increased sensorimotor performance, and the duration of sociosexual interactions. Conversely, social housing reduced hyperactivity and altered anxiety-like behavior in TBI mice, and reduced same-sex social investigation. TBI mice showed impaired spatial memory retention, except for TBI mice exposed to both EE and group housing. In the brain, while TBI led to significant regional tissue atrophy, social housing had modest neuroprotective effects on hippocampal volumes, neurogenesis, and oligodendrocyte progenitor numbers. In conclusion, manipulation of the post-injury environment has benefit for chronic behavioral outcomes, but the benefits are specific to the type of enrichment available. This study improves understanding of modifiable factors that may be harnessed to optimize long-term outcomes for survivors of early-life TBI.

NA-OR: A path optimization method for manipulators via node attraction and obstacle repulsion.

This paper is concerned with the issue of path optimization for manipulators in multi-obstacle environments. Aimed at overcoming the deficiencies of the sampling-based path planning algorithm with high path curvature and low safety margin, a path optimization method, named NA-OR, is proposed for manipulators, where the NA (node attraction) and OR (obstacle repulsion) functions are developed to refine the path by iterations. In the iterations of path optimization, the node attraction function is designed to pull the path nodes toward the center of their neighbor nodes, thereby reducing the path curvature and improving the smoothness. Also, the obstacle repulsion function is developed to push the path nodes out of the potentially unsafe region by generating a repulsive torque on the path nodes, thus improving the safety margin of the motion. By introducing the effect of NA-OR, the optimized path has a significant improvement in path curvature and safety margin compared with the initial path planned by Bi-RRT, which meaningfully enhances the operation ability of manipulators for the applications that give a strong emphasis on security. Experimental results on a 6-DOF manipulator in 4 scenarios demonstrate the effectiveness and superiority of the proposed method in terms of the path cost, safety margin, and path smoothness.

Vision-Based Impedance Control of an Aerial Manipulator Using a Nonlinear Observer

Contact-based aerial interaction control in unknown environments is a challenging issue. To solve this problem, this paper presents an image-based impedance control scheme for an aerial manipulator. Unlike points and image moments, the line features considered in this paper cannot uniquely determine the pose of the onboard camera. Therefore, a nonlinear observer is proposed to online provide supplementary 3D information of the system. After that, a hierarchical tracking controller, which is equipped with an image-space impedance filter, is designed to implement a trajectory tracking task with tunable compliance, while at the same time achieving a subtask that aims to determine the final pose of the aerial manipulator. By planning task-space trajectories, desired interaction behavior can be specified without relying on the global position of the system. Furthermore, the effectiveness criterion of the observer is derived, and the stability of the system is proven. Several experiments, including a push-and-slide task, robustness analysis, and a comparison with the state of the art have been conducted to demonstrate the feasibility of the method. Note to Practitioners—This article presents a method for controlling an aerial manipulator to interact with unknown environments without measuring the global position of both the environment and the aerial manipulator. Furthermore, unlike the existing methods, the proposed visual servoing method is based on line features, which are generally more robust than point features. Moreover, it would be intuitive for users to specify the approaching path and the interaction behavior of the aerial manipulator by just planning the image feature trajectories and the desired distance between the aerial manipulator and the environment. This distance is online estimated using the visual feedback of a monocular camera, instead of relying on any costly 3D-vision sensors or lidars, making it an economical solution for aerial manipulation in field environments.

Providing Dual Awareness using Multimodal Cues for Collaborative Manipulation in Virtual Environments

Virtual reality (VR) collaborative manipulation requires a proper understanding of the user’s self, other collaborators, and shared objects in the virtual environment. Users must be aware of the movements of themselves and others to coordinate their actions when they hand over an object or move it together. The awareness of collaboration plays an essential role in virtual environments. However, previous studies have focused on providing awareness only for cooperative manipulation. This study proposes a novel framework for dual awareness that comprehensively manages the state of interactions between multiple users and shared virtual objects and provides distinct sensory cues to distinguish themselves from collaborators. The experimental results showed that participants could easily and quickly collaborate on manipulation using our feedback, and they also answered positively in the subjective evaluation.

The effect of environment and canopy manipulation on the development of red flesh colour in apple

The effect of environment and canopy manipulation on the development of red flesh colour in apple

SK and Kv4 Channels Limit Spike Timing Perturbations in Pacemaking Dopamine Neurons.

Midbrain dopamine (DA) neurons are among the best characterized pacemaker neurons, having intrinsic, rhythmic firing activity even in the absence of synaptic input. However, the mechanisms of DA neuron pacemaking have not been systematically related to how these cells respond to synaptic input. The input-output properties of pacemaking neurons can be characterized by the phase-resetting curve (PRC), which describes the sensitivity of interspike interval (ISI) length to inputs arriving at different phases of the firing cycle. Here we determined PRCs of putative DA neurons in the substantia nigra pars compacta in brain slices from male and female mice using gramicidin-perforated current-clamp recordings with electrical noise stimuli applied through the patch pipette. On average, and compared with nearby putative GABA neurons, DA neurons showed a low, nearly constant level of sensitivity across most of the ISI, but individual cells had PRCs showing relatively greater sensitivity at early or late phases. Pharmacological experiments showed that DA neuron PRCs are shaped by small-conductance calcium-activated potassium and Kv4 channels, which limit input sensitivity across early and late phases of the ISI. Our results establish the PRC as a tractable experimental measurement of individual DA neuron input-output relationships and identify two of the major ionic conductances that limit perturbations to rhythmic firing. These findings have applications in modeling and for identifying biophysical changes in response to disease or environmental manipulations.

An Efficiently Convergent Deep Reinforcement Learning-Based Trajectory Planning Method for Manipulators in Dynamic Environments

An Efficiently Convergent Deep Reinforcement Learning-Based Trajectory Planning Method for Manipulators in Dynamic Environments

Modular Soft Robot with Origami Skin for Versatile Applications.

Recent advances in soft robotics demonstrate the requirement of modular actuation to enable the rapid replacement of actuators for maintenance and functionality extension. There remain challenges to designing soft actuators capable of different motions with a consistent appearance for simplifying fabrication and modular connection. Origami structures reshaping along with their unique creases became a powerful tool to provide compact constraint layers for soft pneumatic actuators. Inspired by Waterbomb and Kresling origami, this article presents three types of vacuum-driven soft actuators with a cubic shape and different origami skins, featuring contraction, bending, and twisting-contraction combined motions, respectively. In addition, these modular actuators with diversified motion patterns can be directly fabricated by molding silicone shell and constraint layers together. Actuators with different geometrical parameters are characterized to optimize the structure and maximize output properties after establishing a theoretical model to predict the deformation. Owing to the shape consistency, our actuators can be further modularized to achieve modular actuation via mortise and tenon-based structures, promoting the possibility and efficiency of module connection for versatile tasks. Eventually, several types of modular soft robots are created to achieve fragile object manipulation and locomotion in various environments to show their potential applications.

On the normative advantages of dopamine and striatal opponency for learning and choice.

The basal ganglia (BG) contribute to reinforcement learning (RL) and decision-making, but unlike artificial RL agents, it relies on complex circuitry and dynamic dopamine modulation of opponent striatal pathways to do so. We develop the OpAL* model to assess the normative advantages of this circuitry. In OpAL*, learning induces opponent pathways to differentially emphasize the history of positive or negative outcomes for each action. Dynamic DA modulation then amplifies the pathway most tuned for the task environment. This efficient coding mechanism avoids a vexing explore-exploit tradeoff that plagues traditional RL models in sparse reward environments. OpAL* exhibits robust advantages over alternative models, particularly in environments with sparse reward and large action spaces. These advantages depend on opponent and nonlinear Hebbian plasticity mechanisms previously thought to be pathological. Finally, OpAL* captures risky choice patterns arising from DA and environmental manipulations across species, suggesting that they result from a normative biological mechanism.

An experimental study of animating-based facial image manipulation in online class environments

Recent advances in artificial intelligence technology have significantly improved facial image manipulation, which is known as Deepfake. Facial image manipulation synthesizes or replaces a region of the face in an image with that of another face. The techniques for facial image manipulation are classified into four categories: (1) entire face synthesis, (2) identity swap, (3) attribute manipulation, and (4) expression swap. Out of them, we focus on expression swap because it effectively manipulates only the expression of the face in the images or videos without creating or replacing the entire face, having advantages for the real-time application. In this study, we propose an evaluation framework of the expression swap models targeting the real-time online class environments. For this, we define three kinds of scenarios according to the portion of the face in the entire image considering actual online class situations: (1) attendance check (Scenario 1), (2) presentation (Scenario 2), and (3) examination (Scenario 3). Considering the manipulation on the online class environments, the framework receives a single source image and a target video and generates the video that manipulates a face of the target video to that in the source image. To this end, we select two models that satisfy the conditions required by the framework: (1) first order model and (2) GANimation. We implement these models in the framework and evaluate their performance for the defined scenarios. Through the quantitative and qualitative evaluation, we observe distinguishing properties of the used two models. Specifically, both models show acceptable results in Scenario 1, where the face occupies a large portion of the image. However, their performances are significantly degraded in Scenarios 2 and 3, where the face occupies less portion of the image; the first order model causes relatively less loss of image quality than GANimation in the result of the quantitative evaluation. In contrast, GANimation has the advantages of representing facial expression changes compared to the first order model. Finally, we devise an architecture for applying the expression swap model to the online video conferencing application in real-time. In particular, by applying the expression swap model to widely used online meeting platforms such as Zoom, Google Meet, and Microsoft Teams, we demonstrate its feasibility for real-time online classes.

Quantum transport efficiency in noisy random-removal and small-world networks

We report the results of an in-depth study of the role of graph topology on quantum transport efficiency in random removal and Watts–Strogatz networks. By using four different environmental models—noiseless, driven by classical random telegraph noise (RTN), thermal quantum bath, and bath + RTN—we compare the role of the environment and of the change in network topology in determining the quantum transport efficiency. We find that small and specific changes in network topology is more effective in causing large change in efficiency compared to that achievable by environmental manipulations for both network classes. Furthermore, we have found that noise dependence of transport efficiency in Watts–Strogatz networks can be categorized into six classes. In general, our results highlight the interplay that network topology and environment models play in quantum transport, and pave the way for transport studies for networks of increasing size and complexity—when going beyond so far often used few-site transport systems.

Vibration suppression method for flexible link underwater manipulator considering torsional flexibility based on adaptive PI controller with nonlinear disturbance observer

Achieving stable and high-precision control of underwater manipulators in complex ocean environments is one of the biggest challenges faced by the research of marine robotics at present. Flexible link manipulators can be installed on unmanned underwater vehicles to realize underwater operations such as underwater cable inspection, deep sea rescue, and marine organizational collections. The flexible link underwater manipulator will vibrate due to the influence of torsional flexibility and water flow disturbance during rotation, which will seriously affect the motion accuracy of the end actuator. In this paper, a control strategy combining the adaptive proportional-integral (PI) controller and the nonlinear disturbance observer is proposed, which indirectly suppresses vibration by improving the speed control accuracy. Firstly, according to the assumed mode method, a dynamic model of the flexible link underwater manipulator considering torsional flexibility and external disturbance is established. Next, the overload compensation control law is proposed to meet the closed-loop stability of the flexible link underwater manipulator. In addition, the PI controller's adaptive law is designed according to the Lyapunov theorem. Finally, the effectiveness of the adaptive PI controller with a nonlinear disturbance observer is proved by the simulation and control experiments of different control strategies. The results show that the proposed controller can achieve stable speed tracking and has a better vibration suppression effect.

The social environment alters neural responses to a lipopolysaccharide challenge

Sick animals display drastic changes in their behavioral patterns, including decreased activity, decreased food and water intake, and decreased interest in social interactions. These behaviors, collectively called “sickness behaviors”, can be socially modulated. For example, when provided with mating opportunities, males of several species show reduced sickness behaviors. While the behavior is known to change, how the social environment affects neural molecular responses to sickness is not known. Here, we used a species, the zebra finch, Taeniopygia guttata, where males have been shown to decrease sickness behaviors when presented with novel females. Using this paradigm, we obtained samples from three brain regions (the hypothalamus, the bed nucleus of the stria terminalis, and the nucleus taeniae) from lipopolysaccharide (LPS) or control treated males housed under four different social environments. Manipulation of the social environment rapidly changed the strength and co-expression patterns of the neural molecular responses to the immune challenge in all brain regions tested, therefore suggesting that the social environment plays a significant role in determining the neural responses to an infection. In particular, brains of males paired with a novel female showed muted immune responses to LPS, as well as altered synaptic signaling. Neural metabolic activity in response to the LPS challenge was also affected by the social environment. Our results provide new insights into the effects of the social environment on brain responses to an infection, thereby improving our understanding of how the social environment can affect health.

Priority-based state machine synthesis that relaxes behavior design of multi-arm manipulators in dynamic environments

This paper presents a framework governing multiple state machines (SMs) to generate behaviors for kinematically-coupled multi-arm robots. A SM is one of the most used tools to switch controllers in robotics, however, it represents only one motion at a certain time. Such a limit of representation not only restricts the potential of the kinematical redundancy but also significantly increases the number of situations we have to consider in behavior design. To relax the problem, this paper provides a distributed design scheme and an online synthesis method for SMs. The base of the framework is a task-priority-based control method for redundant robots. We expand it by introducing an abstract data structure specialized in robotic behaviors. The abstract reformulation naturally connects with SMs so that the framework realizes parallelism of sequential logic. A priority queue constructed in each control loop integrates SMs designed for each effector, and the framework automatically generates whole-body behaviors online. In dynamic simulations, the framework governs four SMs and achieves reaching tasks with a dual-arm manipulator at 1 kHz. It is shown that the loose coupling of the SMs yields reactive and flexible decisions in a dynamic environment.

Environmental manipulation and stimulation of atypical children trough art therapy

IntroductionThe accumulated experience, both with typical and atypical children, led to the desire for an easier integration into the collective.Detecting and encouraging the skills of the atypical child, with the help of combined arts techniques and environmental stimulation, supports their’s integration into the comunity.ObjectivesBeneficiaries-Centered Art therapy, with the aim of identifying and developing outstanding skills, trough environmental manipulation and combined arts techniquesMethods The environmental manipulation method is used in the art therapy session trough artistic installations and colorful fabrics. Trough chromatics and textures are generated different contexts and atmospheres sense, through which the atypical child comes to accept and discover that environment. Through the manipulation of artistic installations, gross motor skills are also required, having to produce large movements with the whole body, in order to shape the elements in the environment.Costume making as a transitional phase in the adaptation of the beneficiary to the previously created environment independently or together with the art therapist, consists in harmonizing the beneficiary with the environment. These stages are achieved through mixed techniques of artistic work, painting, decorating, modeling, collage, weaving and binding techniques.Results By practicing these methods during the art therapy sessions, the beneficiaries increased their self-esteem through the achievements they had and discovered and improved their outstanding skills: fine and gross motor skills, color sense, visual thinking, hand-eye coordination; improved and developed both verbal and non-verbal communication between beneficiary - art therapist and beneficiary - beneficiary, in the case of group sessionsImage:Image 2:Image 3:ConclusionsThe role of the artist/Art-therapist can be to identify and encourage the creative potential of the beneficiaries by making both individual and team artworks; to support social integration through art and to value the outstanding skills of the beneficiaries.Disclosure of InterestNone Declared

Open-Set Object Detection Using Classification-Free Object Proposal and Instance-Level Contrastive Learning

Detecting both known and unknown objects is a fundamental skill for robot manipulation in unstructured environments. Open-set object detection (OSOD) is a promising direction to handle the problem consisting of two subtasks: objects and background separation, and open-set object classification. In this letter, we present Openset RCNN to address the challenging OSOD. To disambiguate unknown objects and background in the first subtask, we propose to use classification-free region proposal network (CF-RPN) which estimates the objectness score of each region purely using cues from object's location and shape preventing overfitting to the training categories. To identify unknown objects in the second subtask, we propose to represent them using the complementary region of known categories in a latent space which is accomplished by a prototype learning network (PLN). PLN performs instance-level contrastive learning to encode proposals to a latent space and builds a compact region centering with a prototype for each known category. Further, we note that the detection performance of unknown objects can not be unbiasedly evaluated on the situation that commonly used object detection datasets are not fully annotated. Thus, a new benchmark is introduced by reorganizing GraspNet-1billion, a robotic grasp pose detection dataset with complete annotation. Extensive experiments demonstrate the merits of our method. We finally show that our Openset RCNN can endow the robot with an open-set perception ability to support robotic rearrangement tasks in cluttered environments.