Nociceptive innervation of the thoracolumbar fascia (TLF) has been investigated over decades, however these studies have not been compiled or collectively appraised. The purpose of this scoping review was to assess current knowledge regarding nociceptive innervation of the TLF to better inform future mechanistic and clinical TLF research targeting low back pain (LBP) treatment. PubMed, ScienceDirect, Cochrane and Embase databases were searched in January 2021 using relevant descriptors encompassing fascia and pain. Eligible studies were: (a) published in English; (b) preclinical and clinical (in vivo and ex vivo) studies; (c) original data; (d) included quantification of at least one TLF nociceptive component. Two-phase screening procedures were conducted by a pair of independent reviewers, data were extracted and summarized from eligible studies. The search resulted in 257 articles of which 10 met inclusion criteria. Studies showed histological evidence of nociceptive nerve fibers terminating in low back fascia, suggesting a TLF contribution to LBP. Noxious chemical injection or electrical stimulation into fascia resulted in longer pain duration and higher pain intensities than injections into subcutaneous tissue or muscle. Pre-clinical and clinical research provides histological and functional evidence of nociceptive innervation of TLF. Greater knowledge of fascial neurological components could impact LBP treatment.

Objective: This systematic review and meta-analysis compared the patient-reported outcomes of intra-articular facet joint injections of normal saline and selected active substances to identify a more effective agent for treating subacute and chronic low back pain (LBP). Methods: The PubMed, Embase, Scopus, Web of Science, and CENTRAL databases were searched for randomized controlled trials and observational studies published in English. A research quality assessment was performed using ROB2 and ROBINS-I. A meta-analysis was conducted using a random-effects model, and the mean differences (MD) with 95% confidence intervals (CI) in efficacy outcomes, including pain, numbness, disability, and quality of life, were assessed. Results: Of the 2,467 potential studies, three were included (247 patients). The active substances and normal saline had similar therapeutic effects on pain within 1 h, after 1-1.5 months, and after 3-6 months, with MD and 95% CI of 2.43 and -11.61 to 16.50, -0.63 and -7.97 to 6.72, and 1.90 and -16.03 to 19.83, respectively, as well as the quality of life after 1 and 6 months. Conclusion: The short- and long-term clinical effects of intra-articular facet joint injections of normal saline are comparable to those of other active substances in patients with LBP.

Field and numerical investigations at Happisburgh, East coast of England, UK, sought to characterize beach thickness and determine geologic framework controls on coastal change. After a major failure of coastal protection infrastructure, removal of about 1 km of coastal defense along the otherwise protected cliffed coastline of Happisburgh triggered a period of rapid erosion over 20 years of ca. 140 m. Previous sensitivity studies suggested that that beach thickness plays a major role in coastal recession. These studies were limited, however, by a lack of beach volume data. In this study, we have integrated the insights gained from our understanding of the Quaternary geology of the area, a novel non-intrusive passive seismic survey method, and a 3D novel representation of the subsurface source and transportable material into a coastal modelling environment to explore the role of beach thickness on the back wearing and down wearing of the cliffs and consolidated platform, respectively. Results show that beach thickness is non-homogeneous along the study site: we estimate that the contribution to nearshore sediment budget via platform down wearing is of a similar order of magnitude as sediment lost from the beach and therefore non-negligible. We have provided a range of evidence to support the idea that the Happisburgh beach is a relatively thin layer perched on a sediment rich platform of sand and gravel. This conceptualization differs from previous publications, which assumes that the platform was mostly till and fine material. This has direct implication on the regional sediment management of along this coastline. The present study contributes to our understanding of a poorly known aspect of coastal sediment budgeting and outlines a quantitative approach that allows for simple integration of geological understanding for coastline evolution assessments worldwide.

In airborne sensor networks (ASNs), the media access control (MAC) protocol is facing with serious unfairness problem due to the traditional protection mechanism of air-to-air communications among aircrafts. Actually by using the binary exponential back-off algorithm at high traffic loads to minimize collisions among users, the latest successful node can always benefit from this kind of MAC to obtain channel resources. Moreover, when taking the existence of the hidden nodes in ASNs into account, the inaccurate traffic load information will further aggravate the system’s unfairness. In this paper, a neighbor-channel-aware (NCA) protocol is proposed to improve the fairness of MAC protocol in ASNs. In the proposal, the NCA frame is firstly added and exchanged between neighbor nodes periodically, which helps to resolve the inaccurate traffic load information, so as to avoid reducing the probability of successful message transmission. Then a traffic-loading based back-off algorithm is involved to make the neighbor nodes cooperatively adjust the inter-frame space (IFS) interval to further reduce the unfairness. The simulation results show that, the proposed MAC protocol can guarantee the satisfied fairness, simultaneously avoiding heavy network overloads to protect key messages’ successful transmissions in ASNs.

Rising sensitivity of the loads with respect to power quality has grown-up the consideration of power system study and power quality enhancement systems. The fluctuation of voltage outside the normal working range due to faults may lead to unsuitable interruption of wind turbines. This thesis present 1.5MW grid connected Adama Ⅰ Wind Farm in Ethiopia with the objectives to capture the optimal power from the wind and ensure voltage source for sensitive load. This paper deals with the effective voltage sag mitigation and Harmonic distortion effectively met IEEE 519-1992 standard under all Phase to ground fault compensation by using Dynamic Voltage Restorer (DVR), to regulate the terminal voltage of the wind farm and safe operation of sensitive load. The DVR utilizes a feed forward control-based algorithm to generate PWM. The simulation results are going to be carried out by MATLAB-Simulink to verify the operation and effectiveness of DVR during balanced voltage sag and swell conditions.

Decision tree algorithms have been among the most popular algorithms for interpretable (transparent) machine learning since the early 1980s. On the other hand, deep learning methods have boosted the capacity of machine learning algorithms and are now being used for non-trivial applications in various applied domains. But training a fully-connected deep feed-forward network by gradient-descent backpropagation is slow and requires arbitrary choices regarding the number of hidden units and layers. In this paper, we propose near-optimal neural regression trees, intending to make it much faster than deep feed-forward networks and for which it is not essential to specify the number of hidden units in the hidden layers of the neural network in advance. The key idea is to construct a decision tree and then simulate the decision tree with a neural network. This work aims to build a mathematical formulation of neural trees and gain the complementary benefits of both sparse optimal decision trees and neural trees. We propose near-optimal sparse neural trees (NSNT) that is shown to be asymptotically consistent and robust in nature. Additionally, the proposed NSNT model obtain a fast rate of convergence which is near-optimal up to some logarithmic factor. We comprehensively benchmark the proposed method on a sample of 80 datasets (40 classification datasets and 40 regression datasets) from the UCI machine learning repository. We establish that the proposed method is likely to outperform the current state-of-the-art methods (random forest, XGBoost, optimal classification tree, and near-optimal nonlinear trees) for the majority of the datasets.

The aim of this study was to evaluate the effect of dietary supplementation with Olea europaea L. extract on the animal welfare and milk quality of lactating Italian Holstein-Friesian dairy cows at different calving orders. Cows in mid lactation phase received, for 60 days, the natural olive extract Phenofeed Dry® (500 mg/cow/day) with high antioxidant power. Hormonal and metabolic parameters were determined through ELISA assays, the milk fatty acid profile through gas chromatography, chemical-nutritional and hygienic-sanitary parameters through ultrasonic analyses. The milk lysozyme content was measured through a specific ELISA assay. The administration of the enriched feed did not alter the hormonal balance. Primiparous cows were more sensitive to the treatment and showed a better general health status compared to other calving orders. The enriched feed resulted in a reduction of saturated fatty acids (SFAs) and an increase of monounsaturated fatty acids (MUFAs) and polyunsaturated fatty acids (PUFAs), ensuring an adequate nutritional content and, above all, a significantly higher content of the antibacterial protein, lysozyme. Overall, our study demonstrate that the inclusion of natural bioactive molecules such as Olea europaea L. polyphenols contributes to improving the welfare status of dairy cows and ensuring high nutritional and functional quality of animal productions.

Abstract: Sand-cement bound screed floor layers are at risk for work-related low back pain, lumbosacral radicular syndrome and knee osteoarthritis given their working technique of level-ling screed with their trunk bended and mainly supported by their hands and knees. To reduce the exposure of the physical demands of bending of the trunk and kneeling, a manually moved screed levelling machine was developed for floor layers in the Netherlands. The aim of this pa-per is to estimate the potential health gain of the manually moved screed levelling machine on the risk of low back pain (LBP), lumbosacral radicular syndrome (LRS) and knee osteoarthritis (KOA) compared to the traditional working technique. The potential health gain was assessed using the epidemiological population estimates of the Population Attributable Fraction (PAF) and the Potential Impact Fraction (PIF) combined with work-related risk estimates for these three disorders from systematic reviews. The percentage of workers exceeding these risk esti-mates was based on worksite observations among in total 28 floor layers. For LBP, 16/18 work-ers were at risk using the traditional working technique with PAF=38%, and for the manually moved screed levelling machine this was 6/10 with PIF=13%. For LRS, these data were 16/18 with PAF=55% and 14/18 with PIF=18% and for KOA, 8/10 with PAF=35% and 2/10 with PIF=26%. A manually moved screed levelling machine might have a significant impact on the prevention of LBP, LRS and KOA among floor layers in the Netherlands and a health impact assessment is a feasible approach to assess health gains in an efficient way.

This study presents three forms of interdisciplinary expertise in the healthcare design context to approach a particular multifaceted problem around the current healthcare for older adult patients with chronic low-back pain (LBP). Using an interdisciplinary co-design framework, first, our design approach performs the role of an initiator to define the problem by exploring the current context of healthcare. Second, it facilitates the experiences of experts and patients to reach the roots of the problem by functioning as a mediator. Third, our approach fulfills the primary role of healthcare design in producing new meanings considering the principles of patient-centeredness. These roles significantly contributed to the design of healthcare innovations. Our framework transformed the distributed disciplinary knowledge developed while tackling the multifaceted problem into new forms of expertise for collaboration in healthcare innovation.

Utilization of Bidirectional Reflectance Distribution Function (BRDF) model parameters obtained from the multi-angular remote sensing is one of the approaches for the retrieval of vegetation structural information. In this research, the potential of multi-angular vegetation indices, formulated by the combination of multi-spectral reflectance from different view angles, for the retrieval of forest above ground biomass was assessed. This research was implemented in the New England region with the availability of a high quality forest inventory database. The multi-angular vegetation indices were generated by the simulation of the Moderate Resolution Imaging Spectroradiometer (MODIS) BRDF/Albedo Model Parameters Product (MCD43A1 Version 6) based BRDF parameters. The effects of seasonal (spring, summer, autumn, and winter) composites of the multi-angular vegetation indices on above ground biomass, angular relationship of the spectral reflectance with above ground biomass, and the interrelationships between the multi-angular vegetation indices were analyzed. Among the existing multi-angular vegetation indices, only the Nadir BRDF-adjusted NDVI ( and Hot-spot incorporated NDVI ( showed significant relationship (more than 50%) with the above ground biomass. This research proposed two more sensitive vegetation structural indices, Fore-scattering Back-scattering NDVI and Vegetation Structure Index (VSI). The Fore-scattering Back-scattering NDVI showed higher sensitivity (R² = 0.62, RMSE = 52.46) towards the above ground biomass than existing multi-angular vegetation indices. Furthermore, the VSI performed in the most efficient way explaining 64% variation of the above ground biomass, suggesting that the right choice of the spectral channel and observation geometry should be considered for improving the estimates of the above ground biomass. In addition, the right choice of seasonal data (summer) was found to be important for estimating the forest biomass while other seasonal data were either insensitive or pointless. The promising results shown by the VSI suggest that it could be an appropriate candidate for monitoring vegetation structure from the multi-angular satellite remote sensing.

Artificial Intelligence is dominated by Artificial Neural Networks (ANNs). Currently, the Batch Gradient Descent (BGD) is the only solution to train ANN weights when dealing with large datasets. In this article, a modification to the BGD is proposed which significantly reduces the training time and improves the convergence. The modification, called Instance Eliminating Back Propagation (IEBP), eliminates correctly-predicted-instances from the Back Propagation. The speedup is due to the elimination of unnecessary matrix multiplication operations from the Back Propagation. The proposed modification does not add any training hyperparameter to the existing ones and reduces the memory consumption during the training.

In this study, a motion control problem for the vessels towed by tugboats or towing ships on the sea is considered. The towed vessels including barge ships are need to have assistance of tugboats. Combining two vessels, some work purposes in the sea or harbor area can be completed. In this study, the authors give newly developed mathematical model and control system strategy. Especially, the system model fully presenting the physical characteristics of two vessels are derived. For controlling the system effectively, it is considered that the towed vessel has no power propulsion system but the rudder is activated to improve the maneuverability. Considering the strong nonlinearities included in the vessel dynamics, the modelled system is presented by nonlinear system without linearization of nonlinear parameters. Thus, the control system for the towed vessel is designed based on the nonlinear control scheme. Exactly, the back-stepping control method is applied to its motion control. Also, the PID control method is applied for comparing with the proposed control strategy.

This paper proposes a single-stage asymmetrical half-bridge fly-back (AHBF) converter with resonant mode using dual-mode control. The presented converter has an integrated boost converter and asymmetrical half-bridge fly-back converter and operates in resonant mode. The boost-cell always operates in discontinuous conduction mode (DCM) to achieve high power factor. The presented converter operates simultaneously using a variable-frequency-controller (VFC) and pulse-width-modulation (PWM) controller. Unlike the conventional single-stage design, the intermediate bus voltage of this controller can be regulated depending on the main power switch duty ratio. The asymmetrical half-bridge fly-back converter utilizes a variable switching frequency controller to achieve the output voltage regulation. The asymmetrical half-bridge fly-back converter can achieve zero-voltage-switching (ZVS) operation and significantly reduce the switching losses. Detailed analysis and design of this single-stage asymmetrical half-bridge fly-back converter with resonant mode is described. A wide AC input voltage ranging from 90 to 264 Vrms and output 19 V/ 120 W prototype converter was built to verify the theoretical analysis and performance of the presented converter.

Acute low back pain (LBP) stands as a leading cause of activity limitation and work absenteeism, and its associated healthcare expenditures are expected to become substantial when acute LBP develops into a chronic and even refractory condition. Therefore, early intervention is crucial to prevent progression to chronic pain whose management is particularly challenging and for which the most effective pharmacological therapy is still controversial. Current guideline treatment recommendations vary and are mostly driven by expertise with opinion differing across different interventions. Thus, it is difficult to formulate evidence-based guidance when relatively few randomized clinical trials did explore the diagnosis and management of LBP while employing different selection criteria, statistical analyses, and outcome measurements. This narrative review aims to provide a critical appraisal of current acute LBP management by discussing the unmet needs and areas of improvement from bench-to-bedside and proposes multimodal analgesia as the way forward to attain an effective and prolonged pain relief and functional recovery in patients with acute LBP.

Low back pain (LBP) is a pandemic and costly musculoskeletal condition in the United States. Patients with LBP may endure surgery, injections, and expensive visits to emergency departments. Some suggest that using physical therapy or chiropractic in the earlier stage of LBP reduces the utilization of expensive health services and lowers the treatment costs. Nevertheless, there is no consistent evidence to declare which one of these methods is a cost-effective treatment within a short (less than a year) period of time. The purpose of this study was to investigate the cost-effectiveness of chiropractic versus physical therapy in the United States. A decision tree analytic model was used for estimating the economic outcomes. The findings showed that in the chiropractic group, the total average cost was $48.56 lower than the physical therapy group, and daily adjusted life years (DALY) was 0.0043 higher than the physical therapy group. Chiropractic care was shown to be a cost-effective alternative compared with physical therapy for adults with at least three weeks of low back pain over six months.

Eutrophication is a major environmental issue with many negative consequences, such as hypoxia and harmful cyanotoxins production. Monitoring coastal eutrophication is a crucial, especially for island countries like the Republic of Cyprus, which are economically dependent on the touristic sector. Additionally, the open-sea aquaculture industry in Cyprus has been exhibiting an increase in the last decades and environmental monitoring to identify possible signs of eutrophication is mandatory according to the legislation. Therefore, in this modelling study, two different types of Artificial Neural Networks (ANNs) are developed based on in situ-data collected from stations located in the coastal waters of Cyprus. Theses ANNs aim to model the eutrophication phenomenon based on two different data-driven modelling procedures. Firstly, the self-organizing map (SOM) ANN examines several water quality parameters (specifically water temperature, salinity, nitrogen species, ortho-phosphates, dissolved oxygen and electrical conductivity) interactions with the Chlorophyll-a parameter. The SOM model enables us to visualize the monitored parameters relationships and to comprehend complex biological mechanisms related to Chlorophyll-a production. A second feed-forward ANN model is also developed for predicting the Chlorophyll-a levels. Based on this ANN model, several scenarios associated to the eutrophication-related water quality parameters can be extracted. The combination of these two ANNs models is considered a holistic modelling approximation for the identification of eutrophication scenarios, since it enables not only the prediction of the Chlorophyll-a parameter levels, but also the “capturing” of hidden biological mechanisms associated with algal production.

This scoping review investigated how consumers perceive and interpret serving size information on food packages. A search of seven databases (2010 to September 2017) was followed by title and abstract screening, with relevant articles assessed for eligibility in full-text. Fourteen studies met inclusion criteria, with relevant data extracted by one reviewer and checked for consistency by a second reviewer. Five studies reported poor understanding of nutrition facts labelling and portion size, with information to ‘benchmark’ serving size against reported as helpful in two studies. Consumer attitudes towards serving size labelling were measured in six studies and identified that serving size information was interpreted as indicative of nutrient intake regardless of portion size recommendations. Increased labelled serving sizes resulted in increased portion sizes in three studies, with three studies reporting the opposite or neutral effect for discretionary food portion sizes. The influence of labelled serving size on consumer attitudes and consumption is complex and sometimes counterintuitive. As labelled serving size can impact on consumption, any changes may result in unintended public health consequences. The effects of labelled serving size format changes should be tested carefully within experimental and ecological contexts and accompanied by tailored, comprehensive and serving size-specific food literacy initiatives.

Opioid use disorder has increased in the world in recent years and Iran ranks first in terms of opium smoking in the world. In fact, opium smoking by traditional methods, in addition to dependence on morphine, is a behavioral addiction in Iran. The body position during opium smoking is usually non-standard and non-ergonomic. Over time, changes in muscle tissue, tendons and ligaments, and the connective tissue go from elasticity to neuromuscular plasticity. This study aims to compare sway back posture and musculoskeletal problems between opium smokers and non-drug users. In this comparative and cross-sectional study, 80 opium smokers were compared with 74 non-drug users in terms of sway angle (sway back posture), and musculoskeletal complaints (NORDIC questionnaire) and the association of possible risk factors was investigated. Data were analyzed by Kolmogorov-Smirnov, Correlation Coefficient and paired-t tests using SPSS version 23. There were significant differences between two groups in terms of sway back posture (P=0.007), and neck (<0.001), upper back (<0.001) and lower back (0.006) musculoskeletal complaints. Homelessness, the lifetime duration of opium smoking (in months), and the duration of daily opium smoking (in minutes) had significant correlation with sway back posture and musculoskeletal complaints. Homelessness was the strongest predictor and had strongest correlation. Overall, an increase in the duration of sitting in non-ergonomic positions could lead to increase in sway angle and sway back posture and increase in musculoskeletal complaints of neck, upper back and lower back due to the non-neutral posture of opium smoking. It seems that plasticity and structural and functional adaptations of the posture occurs due to opium smoking and further studies are recommended.

The liver health of Gilthead sea bream and European sea bass fed fishmeal-free diets including various proportions of plant proteins, insect and poultry by-product meals, was investigated through biochemical and histological analyses using a new Liver Index (LI) formula. Four isoproteic (45% DM) and isolipidic (20% DM) diets were compared: a control, plant-based diet (CV) and other three test ones where 40% of a plant protein-rich ingredient mixture was replaced by Hermetia illucens (H40) or poultry by-product (P40) meals alone or in combination (H10P30). The trials lasted 12 and 18 weeks for sea bream and sea bass, respectively. The results so far ob-tained highlighted species-specific differences in the physiological response to dietary changes. In sea bream, the biochemical and histological responses suggest favorable physiological status and liver health, with higher serum cholesterol (CHO) and triglyceride (TAG) levels and moderate hepatocyte lipid accumulation with the H10P30 diet compared to CV (p<0.05). In sea bass, all diets resulted in elevated serum TAG levels and liver lipid accumulation particularly in fish fed the P40 one (p<0.05) which resulted in the highest LI, coupled with higher frequency of severe lipid accumulation, hypertrophy, cord loss, peripheral nuclei displacement and pyknosis. In conclusion sea bream well adapted to the test diets, while sea bass exhibited altered hepatic lipid metabolism leading to incipient liver steatosis, likely due to the high lipid content of the diets including the insect and poultry meals. The LI developed in this study proved to be a reliable tool for assessing the effects of dietary changes on liver health of sea bream and sea bass, consistent with biochemical and histological findings.

The seismic events of 2015 in Nepal exposed the challenges associated with constructing earthquake-resistant 2-story self-built stone masonry structures in high-elevation rural regions, especially post-disaster. The Department of Urban Development and Building Construction (DUDBC) provided designs that failed to preserve the local architectural landscape and craftsmanship while adding unfamiliar knowledge and technology. To address the challenges related to architecture, structure, and socio-economic concerns in designing and implementing post-earthquake houses, a need-based building development framework is required for standardized practice. This study presents a novel framework to assess, design, and implement a self-built house after a disaster, consisting of five stages: 1) post-disaster problem assessment, 2) need identification, 3) material selection, 4) design development, and 5) validation and implementation. Based on this framework, we proposed a novel gabions building construction technology for two-story stone masonry structures that effectively mitigate post-disaster challenges such as logistic, resilience, and socioeconomic aspects while improving disaster resiliency specifically in the high-elevation rural areas of Nepal. The proposed two-story gabion building preserves architectural values, enhances structural integrity, and provides cost-effectiveness when compared with its DUDBC peer models while providing much-needed relief to the vulnerable community. The proposed resilient house, G- 2.1, utilizes locally sourced materials and craftsmanship, and innovative gabion technology that ensures affordability and facilitates knowledge transfer. The contribution of this study includes a development framework and a two-story gabions house that is most suitable for self-built post-disaster reconstruction and resilient to local architecture and socio-economic conditions while providing structural integrity and safety.

In this work, the author employs the quantum hydrodynamic formalism to achieve the geometrization of spacetime for describing the gravitational interaction within the framework of quantum theory. This approach allows for the development of an equation of gravity that is mathematically connected to the fermion and boson fields. This achievement is accomplished by incorporating two fundamental principles: covariance of the quantum field equations and the principle of least action. By considering these principles, a theory is established that enables the calculation of gravitational corrections to Quantum Electrodynamics, and potentially, to the standard model of particle physics as well. The theory also provides an explanation for two phenomena: the existence of a cosmological pressure density similar to quintessence, that is compatible with the small value of the observed cosmological constant, and the breaking of matter-antimatter symmetry at high energies offering insights into why there is an imbalance between the two in the early universe. In the cosmological modeling of the theory, there exists a proposal to account for the formation of supermassive black holes that are accompanied by their own surrounding galaxies, without relying on the process of mass accretion. The model, in accordance with recent observations conducted by the James Webb Space Telescope, supports the notion that galactic configurations were established relatively early in the history of the universe, shortly after the occurrence of the Big Bang.

Background: Low-level physical activity (PA) among Chronic Low Back Pain (cLBP) is associated with various biopsychosocial factors. This research aimed to study the predictors of PA behavior among cLBP patients. Methods: In the present study 300 eligible patients with cLBP who referred to comprehensive health service centers in the Shahid Beheshti University of Medical Sciences (SBUMS) in Tehran, Iran were random selected.To diagnose the predictors of PA behavior, all the Theory of Reasoned Action (TRA) constructs were examined as risk factors to see if they influence on the probability of PA behavior occurrence and were interpreted through odds ratio (OR). SPSS version 19 was used to analyze the data. Results: Totally 280 cLBP patients with mean age of 57.07 ±13.09 years old participated in the study. This study showed that motivation to comply significant predictor the cLBP patients for subjective norm OR (%95CI): 2.095(0.116-2.792), p-value<0.001), intention was significant predictor for perform the PA behavior OR (%95CI): 1.431(0.138-1.538), p-value <0.001), behavior beliefs could predictor for attitude OR (%95CI): 1.276(0.106-1.355), p-value= 0.002). attitude, normative beliefs, subjective norm ,and evaluation outcome behavior could predictors the cLBP patients for intention to perform the PA behavior OR (%95CI): 1.188(0.032-1.312), p-value<0.001)., OR (%95CI): 1.158(0.076-2.208), p-value=0.003) ., OR (%95CI): 1.104(0.076-1.128), p-value<0.001) ., OR (%95CI): 0.814(0.301-1.440), p-value=0.007). Conclusions: This study showed that the cLBP patients who were normative beliefs and evaluation regarding PA behavior could effect on the intention to engage in greater PA than those via other constructs (attitude and subjective norm). This study showed that the cLBP patients who were normative beliefs and evaluation regarding PA behavior could effect on the intention to engage in greater PA than those via other constructs (attitude and subjective norm). This study showed that the cLBP patients who were normative beliefs and evaluation regarding PA behavior could effect on the intention to engage in greater PA than those via other constructs (attitude and subjective norm).

This service improvement project was carried out at LEKMA Hospital, Ghana. Ghana has high levels of antimicrobial resistance (AMR). There is an urgent need to introduce models of care that optimize antibiotic prescribing. Methods Delayed / back-up prescribing is a strategy that could reduce antibiotic use in suspected upper respiratory tract infections. Four different models of delayed / back-up prescribing [no prescription; post-dated prescription (given to patient); post-dated prescription (forwarded to pharmacy); and follow-up appointment for reassessment after 3 days] were implemented in discussion between clinician and patient. Patients were contacted 10 days after their appointment to record compliance, check on their wellbeing, and rate their experience. Results Over a 3-month period (12/2019-02/2020), 142 patients were eligible for delayed / back-up prescribing. The most common clinical diagnoses were sore throat (102/140, 73%), common cold (22/140, 16%) and sinusitis (10/140, 7%). In total, 12 (9%) patients remained symptomatic at day 10, and only one individual in the entire cohort took antibiotics. Most patients (95%) rated their experience as good or very good. Conclusions Delayed / back-up prescribing models can lead to substantial reduction in antibiotic consumption amongst outpatient department patients with suspected upper respiratory tract infections. Delayed / back-up prescribing can be implemented safely in low and middle-income countries.

SDG target 12.3 calls for halving food waste at retail, food service, and household by 2030. The food waste index for this purpose includes parts attached to food that are usually removed intentionally ("unavoidable food waste") and allows counting the conversion to animal feed and utilisation as biomaterial as means of reduction. In Japan, the "Food Waste Recycling Law" which has been in effect since 2001, promotes the recycling of food waste generated from businesses, designating feed conversion as top priority. On the other hand, based on the more recent "Food Loss Reduction Promotion Act" of 2019, the government is currently promoting the reduction of avoidable food waste, as to meet the SDG target. Based on statistical sources and interviews with Ministry officers, this paper explains the history and achievements of Japan's 23-year policy based on the Food Recycling Law, as well as the tension between the two legislations.

Cooperative non-orthogonal multi access communication is a promising paradigm for the future wireless networks because of its advantages in terms of energy efficiency, wider coverage and interference mitigating. In this paper, we study the secrecy performance of a downlink cooperative non-orthogonal multi access (NOMA) communication system under the presence of an eavesdropper node. Smart node selection based on feed forward neural networks (FFNN) is proposed in order to improve the physical layer security (PLS) of a cooperative NOMA network. The selected cooperative relay node is employed to enhance the channel capacity of the legal users, where the selected cooperative jammer is employed to degrade the capacity of the wiretapped channel. Simulations of the secrecy performance metric namely the secrecy capacity ($C_S$) are presented and compared with the conventional technique based on fuzzy logic node selection technique. Based on our simulations and discussions the proposed technique outperforms the existing technique in term the of secrecy performance.

The abundant mechanical vibration energy in bridge road environment can be converted into electric energy by using the piezoelectric energy harvest technology, which could be an efficient way to provide energy required by the wireless sensor network in the bridge condition monitoring system. An autonomous energy harvesting system has been designed based on cantilever beams for sensing and acquiring the bridge vibration energy. After the analysis of the dynamic properties of the piezoelectric cantilever beam in the energy conversion, three kinds of interface circuits were compared through simulation and experimental results. It was shown that the VD interface circuit has less power loss. Furthermore, the proposed closed loop control method based on the VD circuit was simple, adaptive, and self-powered, which is suitable for the road energy harvesting application. Finally, the energy harvesting system based on VD circuit was realized with harvested power of around 0.8mW.

Electricity demand forecasting plays a significant role in energy markets. Accurate prediction of electricity demand is the key factor to optimize power generation, consumption, saving energy resources, and determining the energy prices. However, integrating energy mix scenarios, including solar and wind power which are highly non-linear and seasonal, into an existing grid increases uncertainty in generation, adds the challenges for precise forecast. To tackle these challenges, state-of-the-art methods and algorithms have been implemented in literature. We have developed Artificial Intelligence (AI) based deep learning models that can effectively handle the information of long time-series data. Based on the pattern of dataset, four different scenarios were developed and two best scenarios were selected for prediction. Dozens of models were developed and tested in deep AI networks. In the first scenario (Scenario1), data for weekdays excluding holidays was taken and in the second scenario (Scenario2) all the data in the basket was taken. Remaining two scenarios, weekends and holidays were tested and neglected because of their high prediction error. To find the optimal configuration, models were trained and tested within a large space of alternatives called hyper-parameters. In this study, an Aritificial Neural Network (ANN) based Feed-forward Neural Network (FNN) showed the minimum prediction error for Scenario1 while a Recurrent Neural Network (RNN) based Gated Recurrent Network (GRU) showed the minimum prediction error for Scenario2. While comparing the accuracy, the lowest MAPE of 2.47% was obtained from FNN for Scenario1. When evaluating the same testing dataset (non-holidays) of Scenario2, the RNN-GRU model achieved the lowest MAPE of 2.71%. Therefore, we can conclude that grouping of weekdays as Senario1 prepared by excluding the holidays provides better forecasting accuracy compared to the single group approach used in Scenario2, where all the dataset is considered together. However, Scenario2 is equally important to predict the demand for weekends and holidays.

Historically, the evaluation and assessment of the clinical response to treatment for canine back pain is subjective and relies on owner and clinician assessment of pain. This study evaluated the use of sequential infrared thermal images as a measure of the response of canine patients with back pain to a prescribed series of photobiomodulation therapy (PBMT) treatments. Qualifying participants had histories of pain and dysfunction associated with spinal osteoarthritis or intervertebral disk disease, or of non-specific uni- or bilateral back pain along the paravertebral epaxial muscles. Each patient was initially thermally imaged prior to PBMT treatment and then received multiple PBMT treatments delivered to the appropriate spinal area on days 1, 2, 3, and 4. Participants were reimaged on day 7. Thermal images provided an objective measure of superficial temperature changes over the area of PBMT treatment of each patient after the PBMT regimen. The temperature correlated with statistically significant changes in Colorado State University Canine Chronic Pain Scale scoring (CPS) and owner assessment using the Canine Brief Pain Inventory (CBPI), which includes a Pain Severity Score (PSS) and Pain Interference Score (PIS). The correlation of objective thermal imaging data with more subjective outcome measures suggests thermal imaging may be a valuable additional tool in monitoring therapy outcome.

In the paper we show that the general relativity in recent Einstein-Palatini formulation is equivalent to a gauge field. We begin with a bit of information of the Einstein-Palatini formulation and derive Einstein field equations from it. In the next section, we consider general relativity with a positive cosmological constant in terms of the corrected curvature. We show that in terms of the corrected curvature general relativity takes the form typical for a gauge field. Finally, we give a geometrical interpretation of the corrected curvature.

With reference to Planck scale Hubble parameter, super luminal expansion speeds, super luminal rotation speeds, Mach’s principle and Holographic principle, we review the current cosmological observations with eight simple assumptions. By understanding Yuri N. Obukhov and V.A. Korotky proposed cosmic rotational effects of polarization of radiation due to massive bodies, to some extent cosmic rotation can be deep-rooted in an observational approach and the ratio of current angular velocity and Hubble parameter can be estimated. It is possible to show that, at H₀ =70 km/sec/Mpc, current cosmic temperature, age, radius, mass, mass density are 2.721 K, 4.41x10¹⁷ sec, 90 billion light years, 1.14654x10⁵⁴ kg, 0.0482 times the current critical density respectively. Clearly speaking, current universe seems to constitute 267 Hubble spheres. Important point to be noted is that, current rotational kinetic energy is 0.6667 times the current critical energy. Based on the estimated current mass density and current rotational kinetic energy, current cosmic dark matter density can be shown to be 0.2851 times the current critical density. These numerical coincidences cast serious doubt on the on the real existence of currently believed ‘dark energy’. Initial and current expansion speeds are 3x10⁸ m/sec and 3.56x10⁹ m/sec respectively. With increasing cosmic age and increasing cosmic expansion speed, current universe is expanding with a speed of 11.885c. By knowing the time to time future cosmic temperatures, future Hubble parameters and corresponding future cosmic expansion speeds can be estimated and thus future expansion speed can be understood. Starting from ‘speed of light’, our model assumes a continuous increase in expansion speed and attains a current radius of 90 billion light years (without inflationary concepts) and casts a serious doubt on the actuality of currently believed ‘inflation’.

The multidimensionality of chronic pain forces us to look beyond isolated pain assessment such as pain intensity, which does not consider multiple key parameters, particularly in patients suffering from post-operative Persistent Spinal Pain Syndrome (PSPS-T2). Our ambition was to provide a novel Multi-dimensional Clinical Response Index (MCRI), including not only pain intensity but also functional capacity, anxiety-depression, quality of life and objective quantitative pain mapping assessments, the objective being to capture patient condition instantaneously, using machine learning techniques. Two hundred PSPS-T2 patients were enrolled in a real-life observational prospective PREDIBACK study with 12-month follow-up and received various treatments. From a multitude of questionnaires/scores, specific items were combined using exploratory factor analyses to create an optimally accurate MCRI; as a single composite index, using pairwise correlations between measurements, it appeared to better represent all pain dimensions than any other classical score. It appeared to be the best compromise among all existing indexes, showing the highest sensitivity/specificity related to Patient Global Impression of Change (PGIC). Novel composite indexes could help to refine pain assessment by changing the physician’s perception of patient condition on the basis of objective and holistic metrics, and by providing new insights to therapy efficacy/patient outcome assessments, before ultimately being adapted to other pathologies.

While Spinal Cord Stimulation (SCS) provides satisfaction to almost 2/3 of Persistent Spinal Pain Syndrome-Type 2 (PSPS-T2) patients implanted for refractory chronic back and/or leg pain when not adequately addressed the back pain component, leaves patients in a therapeutic cul-de-sac. Peripheral Nerve field Stimulation (PNfS) has shown interesting results addressing back pain in the same population. Far from placing these two techniques in opposition, we suggest that these approaches could be combined to better treat PSPS-T2 patients. We designed a RCT (CUMPNS), with a 12-month follow-up, to assess the potential added value of PNfS, as a salvage therapy, in PSPS-T2 patients experiencing a “Failed SCS Syndrome” in the back pain component. Fourteen patients were included in this study and randomized into 2 groups (“SCS + PNfS” group/n=6 vs “SCS only” group/n=8). The primary objective of the study was to compare the percentage of back pain surface decrease after 3 months, using a computerized interface to obtain quantitative pain mappings, combined with multi-dimensional SCS outcomes. Back pain surface decreased significantly greater for the ”SCS+PNfS” group (80.2% ± 21.3%) compared to the “SCS only” group (13.2% ± 94.8%) (p=0.012), highlighting the clinical interest of SCS+PNfS, in cases where SCS fails to address back pain.