Threshold Modulation Research Articles

Transfer learning: A new aerodynamic force identification network based on adaptive EMD and soft thresholding in hypersonic wind tunnel

The aerodynamic test in the pulse combustion wind tunnel is very important for the design, evaluation and optimization of aerodynamic characteristics of the hypersonic aircraft. The test accuracy even affects the success or failure of hypersonic aircraft development. In the aerodynamic test of pulse combustion wind tunnel, the aerodynamic signal is disturbed by the inertial force signal, which seriously affects the test accuracy of aerodynamic force. Aiming at the above problems, this paper innovatively proposes an aerodynamic intelligent identification method, that is the transfer learning network based on adaptive Empirical Modal Decomposition (EMD) and Soft Thresholding (TLN-AE&ST). Compared with the existing aerodynamic intelligent identification model based on deep learning technology, this study introduces the transfer learning idea into the aerodynamic intelligent identification model for the first time. The TLN-AE&ST effectively alleviates the problem of scarcity of training samples for intelligent models due to the high cost of wind tunnel tests, and provides a new idea for further implementation of deep learning technology in the field of wind tunnel aerodynamic testing. And this study designed residual attention block with soft threshold and dense block with adaptive EMD in TLN-AE&ST model. Residual attention block with soft threshold module can more effectively suppress the influence of instrument noise signal on model training effect. Dense block with adaptive EMD makes the deep learning model no longer a black box to a certain extent, and has certain physical significance. Finally, a series of wind tunnel tests were carried out in the Φ = 2.4 m pulse combustion wind tunnel of China Aerodynamic Research and Development Center to verify the effectiveness of TLN-AE&ST.

Effects of Orthopedic Manual Therapy on Pain Sensitization in Patients With Chronic Musculoskeletal Pain: An Umbrella Review With Meta-Meta-analysis.

The aim of this umbrella review with meta-meta-analysis was to assess the effectiveness of orthopedic manual therapy in isolation on pain sensitization in patients with chronic musculoskeletal pain. A systematic search was performed in different databases including systematic reviews with or without meta-analysis. The outcome measures included were pressure pain threshold, temporal summation, and conditioned pain modulation. The results of the different reviews were statistically synthesized through a random-effect meta-analysis, of all standardized mean differences and the corresponding 95% confidence interval reported by each study. For mechanical hyperalgesia, the meta-meta-analysis of three meta-analyses revealed a statistically significant small-moderate effect of orthopedic manual therapy, with no evidence of heterogeneity and moderate-quality evidence. In terms of temporal summation, one meta-analysis revealed a statistically significant small effect of orthopedic manual therapy intervention, with moderate heterogeneity and low quality of evidence. Finally, one review without meta-analysis found that orthopedic manual therapy improved endogenous analgesia with low-quality evidence. Orthopedic manual therapy in isolation improved mechanical hyperalgesia with moderate-quality evidence, as well as temporal summation and conditioned pain modulation with low-quality evidence. However, its effects are limited only to immediate and short-term.

A computational model to simulate spectral modulation and speech perception experiments of cochlear implant users.

Speech understanding in cochlear implant (CI) users presents large intersubject variability that may be related to different aspects of the peripheral auditory system, such as the electrode-nerve interface and neural health conditions. This variability makes it more challenging to proof differences in performance between different CI sound coding strategies in regular clinical studies, nevertheless, computational models can be helpful to assess the speech performance of CI users in an environment where all these physiological aspects can be controlled. In this study, differences in performance between three variants of the HiRes Fidelity 120 (F120) sound coding strategy are studied with a computational model. The computational model consists of (i) a processing stage with the sound coding strategy, (ii) a three-dimensional electrode-nerve interface that accounts for auditory nerve fiber (ANF) degeneration, (iii) a population of phenomenological ANF models, and (iv) a feature extractor algorithm to obtain the internal representation (IR) of the neural activity. As the back-end, the simulation framework for auditory discrimination experiments (FADE) was chosen. Two experiments relevant to speech understanding were performed: one related to spectral modulation threshold (SMT), and the other one related to speech reception threshold (SRT). These experiments included three different neural health conditions (healthy ANFs, and moderate and severe ANF degeneration). The F120 was configured to use sequential stimulation (F120-S), and simultaneous stimulation with two (F120-P) and three (F120-T) simultaneously active channels. Simultaneous stimulation causes electric interaction that smears the spectrotemporal information transmitted to the ANFs, and it has been hypothesized to lead to even worse information transmission in poor neural health conditions. In general, worse neural health conditions led to worse predicted performance; nevertheless, the detriment was small compared to clinical data. Results in SRT experiments indicated that performance with simultaneous stimulation, especially F120-T, were more affected by neural degeneration than with sequential stimulation. Results in SMT experiments showed no significant difference in performance. Although the proposed model in its current state is able to perform SMT and SRT experiments, it is not reliable to predict real CI users' performance yet. Nevertheless, improvements related to the ANF model, feature extraction, and predictor algorithm are discussed.

High-damage vanadium pentoxide film saturable absorber for sub-nanosecond Nd:YAG lasers

Low-dimensional materials as saturable absorber (SA) for sub-nanosecond pulse laser have attracted extensive attention due to their excellent optoelectronic properties. However, high-quality low-dimensional materials’ nonlinear optical properties, such as larger damage threshold and higher modulation depth, are essential for generation of stable sub-nanosecond pulse laser. Herein, the large-area high-quality vanadium pentoxide (V2O5) films were prepared by magnetron sputtering deposition technology, and the usage of V2O5 films as a SA for sub-nanosecond pulse passively Q-switched Nd:YAG laser generation for the first time. It was found that V2O5-SA films exhibit excellent nonlinear optical characteristics, with a larger damage threshold of 509.8 mJ/cm2 and a higher modulation depth of 21.8 %, and the shortest pulse width of 59 ns. Our experimental results demonstrate that V2O5-SA films has the advantages of larger damage threshold and stable availability, which provides a promising solution for the development of high-quality low-dimensional SA devices in short pulse solid-state lasers.

Effect of monocular sensitivity on binocular summation of luminance-modulated flicker.

Binocular summation of luminance contrast signals in the spatial domain has been investigated in many studies, but less attention has been paid to the analogous interactions in the temporal domain. The present study determined the impact of monocular sensitivity on the binocular detection of luminance-modulated flickering stimuli. Binocular summation ratios (BSRs) were determined in 13 visually-normal adults for a range of monocular flicker modulation thresholds (FMTs), generated by changing stimulus size (7'- 60') and luminance (mesopic and photopic). Monocular and binocular FMTs were measured at the point of regard and in each of the four quadrants at 5° eccentricity for each target size and luminance using the Flicker-Plus test. Monocular and binocular FMT's increased with decreasing target size for all retinal locations (p<0.001), and were overall larger for mesopic than for photopic condition (p<0.001). BSRs for mesopic (mean±SD: 1.50±0.21) and photopic (1.60±0.24) stimuli were greater than unity (p<0.001), with the latter showing larger estimates than former (p<0.001). BSRs showed no significant trend across target sizes for both luminance conditions (p>0.12). The results demonstrate that the visual system successfully summates inputs from the two eyes to enhance flicker detection, independent of their absolute monocular detection thresholds. These findings may serve as a predictive baseline for further experiments designed to determine how other stimulus properties and interocular differences in monocular thresholds may affect the binocular perception of flicker.

Post-surgical contributors to persistent knee pain following knee replacement: The Multicenter Osteoarthritis Study (MOST)

ObjectivePain persistence following knee replacement (KR) occurs in ∼20–30% of patients. Although several studies have identified preoperative risk factors for persistent post-KR pain, few have focused on post-KR contributing factors. We sought to determine whether altered nociceptive signaling and other peripheral nociceptive drivers present post-operatively contribute to post-KR pain. DesignWe included participants from the Multicenter Osteoarthritis Study who were evaluated ∼12 months after KR. We evaluated the relation of measures of pain sensitivity [pressure pain threshold (PPT), temporal summation (TS), and conditioned pain modulation (CPM)] and the number of painful body sites to post-KR WOMAC knee pain, and of the number of painful sites to altered nociceptive signaling using linear or logistic regression models, as appropriate. Results171 participants (mean age 69 years, 62% female) were included. TS was associated with worse WOMAC pain post-KR (β ​= ​0.77 95% CI:0.19–1.35) and reduced odds of achieving patient acceptable symptom state (aOR ​= ​0.54 95%CI:0.34–0.88). Inefficient CPM was also associated with worse WOMAC pain post-KR (β ​= ​1.43 95% CI:0.15–2.71). In contrast, PPT was not associated with these outcomes. The number of painful body sites present post-KR was associated with TS (β ​= ​0.05, 95% CI:0.01, 0.05). ConclusionsPost-KR presence of central sensitization and inefficient descending pain modulation was associated with post-KR pain. We also noted that presence of other painful body sites contributes to altered nociceptive signaling, and this may thus also contribute to the experience of knee pain post-KR. Our findings provide novel insights into central pain mechanisms and other peripheral pain sources contributing to post-KR persistent knee pain.

Energy Efficiency Improvement with Reversible Substations for Electrified Transportation Systems

More and more often overall energy efficiency of an electrified transportation system appears as target of new constructions, sometimes with incomplete definitions of performance indexes to assess that target has been reached. A worked out example is based on the introduction of reversible substations. Reversible substations are a method to improve energy efficiency, whose application in an existing system can be progressive and does not require large traffic intensity to be effective. Their effectiveness depends on some system parameters (nominal catenary voltage in particular). A simulation model fed with experimental data from a line section of Metro de Madrid is used to demonstrate the operation and optimization of reversible substations. Background The ambitious reduction of CO2 greenhouse gas emission within 2050 declared by the European Commission also involves transportation systems. In this context an optimum recovery of the electric braking energy produced by railway vehicles is more and more relevant. Several strategies to completely recover the braking energy are being developed and applied. A methodology that allows the accurate determination of the amount of recovered energy in real operating conditions becomes then a valuable tool. Objective Reversible substations are one of the braking energy recovery methods that are widely applicable. Their effect is analyzed in a system perspective, considering them integrated in the transportation system with its dynamics and various operating points. The effectiveness and consequences of the operation of one or more reversible substations are evaluated by identifying relevant system conditions and scenarios. Methods An electric network model is provided, fed by measured timetable and traction current. Simulation results are analyzed and compared with some experimental results: simulation configurations will be selected to match those of the available experimental data. Results The selected substation no-load output voltage level has a significant effect on efficiency and performance of reversible substations. A reduction of 50 V, from 1700 V to 1650 V produces a decrease of the energy dissipated by the braking rheostat on-board trains of about 13%. The voltage increase caused during braking phases is kept under control better for track positions close to reversible substations: tests show that line voltage increase is 2.5% of nominal value with a reversible substation, and only 0.5% when it is operated. Trimming the thresholds that trigger the operation of the on-board braking chopper (intermingling regenerative and dissipative braking) has a dramatic effect on regenerability: a reduction of 50 V causes an improvement of 19%. Conclusion The paper presents a methodology that merges measurements and circuital model to investigate on the energy saving provided by reversible substations supplying railway system. The methodology has been applied to a real case. Preliminary results regarding the impact of supply voltage level, reversible module position and threshold levels of the braking chopper control system on the dissipated braking energy and power quality has been carried out.

Automatic Segmentation of Psoriasis Skin Images Using Adaptive Chimp Optimization Algorithm-Based CNN.

Psoriasis is a severe skin disease that is surveyed outwardly by dermatologists. In recent years, computer vision is the major solution for diagnosing the psoriasis skin disease by segmenting the infected skin images. Besides, many researchers had presented efficient machine learning techniques for segmenting the psoriasis skin images. Nevertheless, accuracy and time consumption of the model are further to be improved. Thus, in this work, we present adaptive chimp optimization algorithm (AChOA)-based convolutional neural network (CNN) which is introduced for automatic segmentation of psoriasis skin images. After pre-processing, the input images are segmented using AChOA-CNN model where weight and bias values of CNN are optimized with the AChOA. The search ability of ChOA is enhanced by adapting the chaotic sequence based on tent map. At final, from the segmented output images, artifacts are removed by applying the threshold module. From the simulation, we attain 97% of accuracy.

Detection of Dim Small Ground Targets in SAR Remote Sensing Image based on Multi-level Feature Fusion

Detection of dim small ground targets in SAR remote sensing images suffers from deficient target information and significant irrelevant background noise. In order to solve this problem, we propose the CD-YOLO (Cross-DRSN YOLO) based on multi-level feature fusion. In CD-YOLO, the convolutional neural network is firstly used to extract features from the input SAR image step by step, thus the spatial pyramid of shallow and deep feature maps is obtained. Cross-level feature fusion is then performed on the spatial pyramid of feature maps, combined with the constructed soft thresholding module which adopts DRSN (Deep Residual Shrinkage Network), to enhance the spatial features of dim small targets and eliminate the noise-related features. Finally, end-to-end target detection is carried out on the two large parallel feature maps generated after soft thresholding. Detection results are output combined with multi-channel information. Due to lack of sufficient image data, a SAR dim small ground target dataset named SGDSTD (SAR Small Ground-based Dim Small Target Dataset) is constructed. Experimental results show that CD-YOLO achieves a real-time performance of 32.3 frames per second, and its AP0.5 and AP0.5: 0.95 on the SGDSTD dataset achieve 91.6% and 51.9%, respectively. Precision and recall of CD-YOLO on the SGDSTD dataset are 86.9% and 81.4%, respectively. The experiment results prove the effectiveness of the proposed method.

PFYOLOv4: An Improved Small Object Pedestrian Detection Algorithm

With the development of deep convolutional neural networks, the effect of pedestrian detection has been rapidly improved. However, there are still many problems in small target pedestrian detection, for example noise (such as light) interference, target occlusion, and low detection accuracy. In order to solve the above problems, based on YOLOv4 algorithm, this paper proposes an improved small target pedestrian detection algorithm named PF_YOLOv4. The algorithm is improved in three aspects on the basis of the YOLOv4 algorithm: firstly, a soft thresholding module is added to the residual structure of the backbone network to perform noise reduction process on interference factors, such as light to enhance the robustness of the algorithm; secondly, the depthwise separable convolution replaces the traditional convolution in the YOLOv4 residual structure, to reduce the number of network model parameters; finally, the Convolutional Block Attention Module (CBAM) is added after the output feature map of the backbone network to enhance of the network feature expression. Experimental results show that the PF_YOLOv4 algorithm outperforms most of the state-of-the-art algorithms in detecting small target pedestrians. The mean Average Precision (mAP) of the PF_YOLOv4 algorithm is 2.35% higher than that of the YOLOv4 algorithm and 9.67% higher than that of the YOLOv3 algorithm, while the detection speed is slightly higher than that of YOLOv4 algorithm.

EEG Signal Denoising Based on Deep Residual Shrinkage Network

In recent years, EEG signals are usually denoised by traditional algorithms, which suffer from large amounts of computation, a limited number of channels, or modal aliasing. To achieve better denoising, a deep residual contraction network is proposed to denoise EEG signals. At the same time, on the basis of the original residual shrinkage building units, a new soft threshold module is used to replace the ReLU function to construct a new network model. Through different groups of denoising experiments, the effectiveness of this denoising algorithm is verified.

Firing behavior of single motor units of the tibialis anterior in human walking as non-invasively revealed by HDsEMG decomposition

Objective. Investigation of the firing behavior of motor units (MUs) provides essential neuromuscular control information because MUs are the smallest organizational component of the neuromuscular system. The MUs activated during human infants’ leg movements and rodent locomotion, mainly controlled by the spinal central pattern generator (CPG), show highly synchronous firing. In addition to spinal CPGs, the cerebral cortex is involved in neuromuscular control during walking in human adults. Based on the difference in the neural control mechanisms of locomotion between rodent, human infants and adults, MU firing behavior during adult walking probably has some different features from the other populations. However, so far, the firing activity of MUs in human adult walking has been largely unknown due to technical issues. Approach. Recent technical advances allow noninvasive investigation of MU firing by high-density surface electromyogram (HDsEMG) decomposition. We investigated the MU firing behavior of the tibialis anterior (TA) muscle during walking at a slow speed by HDsEMG decomposition. Main results. We found recruitment threshold modulation of MU between walking and steady isometric contractions. Doublet firings, and gait phase-specific firings were also observed during walking. We also found high MU synchronization during walking over a wide range of frequencies, probably including cortical and spinal CPG-related components. The amount of MU synchronization was modulated between the gait phases and motor tasks. These results suggest that the central nervous system flexibly controls MU firing to generate appropriate force of TA during human walking. Significance. This study revealed the MU behavior during walking at a slow speed and demonstrated the feasibility of noninvasive investigation of MUs during dynamic locomotor tasks, which will open new frontiers for the study of neuromuscular systems in the fields of neuroscience and biomedical engineering.

Altered central pain processing assessed by quantitative sensory testing in patients with failed back surgery syndrome

ObjectiveTo investigate the presence of altered central pain processing in patients with failed back surgery syndrome (FBSS) using quantitative sensory testing (QST). MethodsThis study included 34 patients with FBSS, 102 patients post-lumbar surgery without low back pain (LBP), and 102 healthy subjects. All subjects underwent both pressure pain threshold (PPT) and conditioned pain modulation (CPM) in both local and remote pain-free areas, as well as temporal summation (TS) in a remote pain-free area. All patient subjects were assessed using the Pain Catastrophizing Scale (PCS), Beck Anxiety Inventory (BAI), Beck Depression Index (BDI), Numeric rating pain scale (NRS) and Oswestry Disability Index (ODI). ResultsCompared with both control groups, FBSS patients showed a reduction in both PPT and CPM in both tested areas, along with increased TS in a pain-free area (P < 0.05). Furthermore, the patients with FBSS had a significantly higher prevalence of anxiety, depression and pain catastrophizing thoughts than the patient controls (P < 0.05). In the FBSS patients, there was a significant correlation between LBP at rest and both CPM and TS in the pain-free areas, and QST measurements were also associated with the ODI, PCS and BAI (P < 0.05). ConclusionThese findings support the existence of augmented central pain processing in patients with FBSS, which may be caused by dysfunction of endogenous pain facilitation and inhibition. This central amplification of pain may contribute to both LBP intensity and disability in FBSS patients. Therefore, treatment efforts should take into account functional alterations in the central nervous system of FBSS patients.

Robust detection of farmed fish by fusing YOLOv5 with DCM and ATM

Accurate object detection of farmed fish is vital for fish counting and measuring. However, the blurring, occlusion, and varying density of underwater fish images from aquaculture ponds result in low precision and poor robustness. This paper proposes a robust detection model called DCM-ATM-YOLOv5, in which the deformable convolution module (DCM) and adaptive threshold module (ATM) are integrated into YOLOv5. The farmed fish detection model is based on YOLOv5, considering its high precision and real-time capabilities. To achieve higher precision on blurred targets, the DCM is applied to offset the sampling locations and to focus more on fish so that the features of blurry fish are enhanced and the background is suppressed. The ATM is introduced to alleviate missed detections resulting from fixed thresholds by generating appropriate thresholds for different densities and predicting the thresholds dynamically, improving the robustness of the proposed model. Two experiments based on data from aquaculture ponds were designed to test the performance of the proposed model. The average precision and recall of DCM-ATM-YOLOv5 were 97.53% and 98.09%, respectively. Compared with the average precision and recall of YOLOv5, those of DCM-ATM-YOLOv5 were improved by 1.92% and 1.97%, respectively. The robustness of the proposed model was evaluated based on data with different densities and settings. The detection results obtained from datasets of varying densities and settings demonstrated that the detection performance of DCM-ATM-YOLOv5 was still superior to that of YOLOv5, indicating that the proposed model has significant stability and robustness. The experimental results showed that DCM-ATM-YOLOv5 has high precision and strong robustness in genuine aquaculture settings and can provide a feasible solution for the detection of farmed fish.

Compressive-Strain-Facilitated Fast Oxygen Migration with Reversible Topotactic Transformation in La0.5Sr0.5CoOx via All-Solid-State Electrolyte Gating

Modifying the crystal structure and corresponding functional properties of complex oxides by regulating their oxygen content has promising applications in energy conversion and chemical looping, where controlling oxygen migration plays an important role. Therefore, finding an efficacious and feasible method to facilitate oxygen migration has become a critical requirement for practical applications. Here, we report a compressive-strain-facilitated oxygen migration with reversible topotactic phase transformation (RTPT) in La0.5Sr0.5CoOx films based on all-solid-state electrolyte gating modulation. With the lattice strain changing from tensile to compressive strain, significant reductions in modulation duration (∼72%) and threshold voltage (∼70%) for the RTPT were observed, indicating great promotion of RTPT by compressive strain. Density functional theory calculations verify that such compressive-strain-facilitated efficient RTPT comes from significant reduction of the oxygen migration barrier in compressive-strained films. Further, ac-STEM, EELS, and sXAS investigations reveal that varying strain from tensile to compressive enhances the Co 3d band filling, thereby suppressing the Co-O hybrid bond in oxygen vacancy channels, elucidating the micro-origin of such compressive-strain-facilitated oxygen migration. Our work suggests that controlling electronic orbital occupation of Co ions in oxygen vacancy channels may help facilitate oxygen migration, providing valuable insights and practical guidance for achieving highly efficient oxygen-migration-related chemical looping and energy conversion with complex oxides.

Thermal pain and detection threshold modulation in augmented reality

Augmented Reality (AR) overlays computer-generated visual, auditory or other sensory information onto the real world. Due to recent technological advancement in the field, it can become increasingly difficult for the user to differentiate between sensory information coming from real and virtual objects, leading to interesting perceptual phenomena. For example, an AR experience in which users can experience their own hands in flames has been shown to elicit heat illusions on the affected hands. In this study, we investigate the potential that AR has for top-down modulation of pain and thermal perception. We assessed thermal pain and detection thresholds on the participant’s right hand while covering it with realistic virtual flames. We compared this experience to a baseline condition with no additional stimuli. We also report on a condition in which the hand is covered by a blue fluid not instantly associated with fire. We found that experiencing a virtual burning hand induces analgesic as well hyperalgesic effects as participants begin to feel heat related pain at lower temperatures and cold related pain at higher temperatures. The experience also impacts significantly on the lowest temperature at which participants starts perceiving warmth. The blue fluid do not affect the thresholds corresponding to the baseline condition. Our research thus confirms previous experiments showing that pain and thermal perception can be manipulated by by AR, while providing quantitative results on the magnitude of this effect.

Neuroendocrine effects of a single bout of functional and core stabilization training in women with chronic nonspecific low back pain: A crossover study.

Exercise‐induced hypoalgesia (EIH) is characterized as the pain reduction after an exercise session and it seems to be related to the release of plasma β‐endorphin. In this sense, the core stabilization training (CT) has been suggested for patients with chronic nonspecific low back pain (CNSLBP), but it is unclear whether it induces EIH. Patients with CNSLBP have neuromotor dysfunctions that can affect the performance of functional tasks, thus, performing functional training (FT) could improve motor control and promote EIH, since functional training uses multi‐joint exercises that aim to improve the functionality of actions performed in daily life. EIH is usually assessed using quantitative sensory tests (QST) such as conditioned pain modulation, pressure pain threshold, and temporal summation. Thus, the sum of parameters from quantitative sensory tests and plasma β‐endorphin would make it possible to understand what the neuroendocrine effects of FT and CT session are. Our study compared the acute effect of CT and FT on the EIH and plasma β‐endorphin release, and correlated plasma β‐endorphin with quantitative sensory testing in patients with CNSLBP. Eighteen women performed two training sessions (CT and FT) with an interval of 48 h between sessions. EIH was assessed by QST and plasma β‐endorphin levels. Results showed that only FT significantly increased plasma β‐endorphin (FT p < 0.01; CT p = 0.45), which correlated with pain pressure threshold (PPT) and conditioned pain modulation (CPM). However, QST values were not different in women with CNSLBP after CT or FT protocols. Plasma β‐endorphin correlated with PPT and CPM, however, the same did not occur with a temporal summation.

Milestone of the most used maximum power point tracking in solar harvesting system

Solar harvesting system with photovoltaic (PV) is one of the most desirable renewable energy sources because of its prominent advantages. However, low efficiency due to fluctuating output power is a major problem for PV systems. A technique used to maximize power extraction known as maximum power point tracking (MPPT) has been proposed by various literature to deal with this problem. One of the most widely developed MPPT methods due to its ease of implementation is perturb and observe (P&amp;amp;O). Since the initial discovery of the principle, the P&amp;amp;O method has been extensively modified including the fixed step-size: step-size variables, partial shading, threshold module current, three-point-comparison, maximization of dynamic performance, minimization of dynamic performance, bandwidth of 𝑃 − 𝑉 curve, decoupling, observation of 𝑑𝑉, 𝑑𝐼, and 𝑑𝑃, datasheet parameters, curve fitting, voltage hold P&amp;amp;O, and observation of 𝑑𝑉 and 𝑑𝑃. This paper presents the development of the P&amp;amp;O method from the initial principle to the end as a reference source for readers. The hope is that a new easy and robust P&amp;amp;O method as a complement to the implementation of the MPPT technique is developed in the solar harvesting system.

Sex effects in the interaction of acute stress and pain perception.

A reciprocity between the stress and the pain system is recognized; however, the manner by which sex affects this reciprocity is unclear. Understanding the interactions of stress, pain, and sex may shed light on the apparent women's vulnerability to chronic pain, which often coexists with increased distress, and to affective disorders, which often coexist with chronic pain. The study's aim was to examine the effect of acute, validated, psychosocial stress on pain perception and modulation of women and men in a controlled manner. Participants were 82 women and 66 men. Heat-pain threshold, heat-pain tolerance, and pain modulation by temporal summation of pain (TSP), and pain adaptation were measured before and after exposure to the Montreal Imaging Stress Task (MIST) or to a sham task. The stress response was verified by perceived ratings of stress and anxiety, autonomic variables, and salivary cortisol. A significant stress response was obtained by the MIST among both sexes; however, women displayed a greater increase in perceived distress, and men displayed a greater increase in cortisol. Among women, TSP decreased and pain adaptation increased following the MIST, responses that were predicted by perceived distress levels. Among men, TSP increased following the MIST but was not predicted by the stress variables. In conclusion, acute stress manipulation seems to differentially affect both stress and pain responses of women and men: women exhibited stress-induced antinociception and men exhibited stress-induced pronociception. Higher perceived stress levels among women may trigger a temporary increase in pain inhibition mechanisms to serve evolutionary purposes.

Is low intensity exercise sufficient to induce exercise-induced pain threshold modulation in people with persistent pain?

ObjectivesWe investigated whether a 12-min walk test (12MWT) yielded exercise-induced pain threshold modulation (EIPM) within people with persistent pain and whether baseline self-report and pain sensitivity measures differed according to these responses. DesignCross-sectional study. MethodsTwo cohorts (tertiary/community) (n = 88) with persistent pain underwent pressure pain threshold (PPT) testing before and after a 12MWT to determine exercise-induced pain threshold modulation responses. Baseline self-report (pain severity, pain distribution, psychological distress, sleep) and baseline widespread pain sensitivity (WPS) (high/low) were recorded. Within and between-group differences were analysed using paired t-tests and repeated measure analyses of covariance. Individual EIPM responses were categorised as hyperalgesic, no change and hypoalgesic responses. Differences in baseline self-report and pain sensitivity measures between EIPM categories were investigated. ResultsNo significant within- or between-group differences in PPT following the 12MWT were detected (p > 0.05). Individual responses showed that up to 30% of the community and 44% of the tertiary cohort demonstrated >20% change in PPT (in either direction). Significant differences were shown in pain distribution (p = 0.002) and baseline WPS (p = 0.001) between people with hyperalgesic, no change, hypoalgesic responses. People with 4–5 pain regions were more likely hyperalgesic (χ2 = 9.0, p = 0.003); people with low baseline WPS were more likely to demonstrate no change (p = 0.002). ConclusionLow or self-selected intensity exercise was insufficient to induce exercise-induced pain modulation at group level. Individual responses were variable with pain distribution and baseline WPS differing between responses. Future research could evaluate responses and associated factors in larger samples with high baseline pain sensitivity specifically.