The peg-in-hole task with object feature uncertain is a typical case of robotic operation in the real-world unstructured environment. It is nontrivial to realize object perception and operational decisions autonomously, under the usual visual occlusion and real-time constraints of such tasks. In this paper, a Bayesian networks-based strategy is presented in order to seamlessly combine multiple heterogeneous senses data like humans. In the proposed strategy, an interactive exploration method implemented by hybrid Monte Carlo sampling algorithms and particle filtering is designed to identify the features’ estimated starting value, and the memory adjustment method and the inertial thinking method are introduced to correct the target position and shape features of the object respectively. Based on the Dempster–Shafer evidence theory (D-S theory), a fusion decision strategy is designed using probabilistic models of forces and positions, which guided the robot motion after each acquisition of the estimated features of the object. It also enables the robot to judge whether the desired operation target is achieved or the feature estimate needs to be updated. Meanwhile, the pliability model is introduced into repeatedly perform exploration, planning and execution steps to reduce interaction forces, the number of exploration. The effectiveness of the strategy is validated in simulations and in a physical robot task. Several recent studies have demonstrated that robotic operations may no longer be targeted at specific objects and structured tasks. For example, in the medical field, robots autonomously perform large-scale pharyngeal swab sampling to reduce the risk of COVID-19 (Coronavirus Disease 2019) in health care workers [Visual sensors are considered to be the most common and direct method, which are used to perceive important features of the uncertain object. In ,4 they pSome methods based on various learning algorithms that fuse visual and tactile information are proposed, for example, in-depth researches on grasping stability prediction ,14 and sCompared to the above methods, the approach based on Bayesian probabilistic techniques has a clear advantage that a large amount of training data is not required in fusing multi-sensor information. The results in  also demTo achieve robotic autonomy operation without human intervention and without making any provisions for an uncertain object, the designed solution scheme in this paper is shown in To achieve the function of the robot deciding the next operation by relying on its own judgement, a fusion decision strategy (FD) is designed which is adapted to fine-grained operations with multiple requirements, such as operating accuracy and preload. The purpose of this is to avoid the errors that can arise from single-evidence decisions, for example, when evidenced by position only, substandard quality of operation may occur . When evidence by contact force only, it can be incorrectly judged as satisfying the task requirements, because an interaction during operation creates a contact force similar to the expected one. The fusion decision strategy is used after each exploration of operating object features. Unlike existed research works that only used position accuracy as an indicator, the designed fusion decision strategy fuses both position and force evidence information in the D-S theoretical framework and includes their uncertainties to guide the subsequent operations.Finally, command information, such as the features of the uncertain object and the evaluation results of the operation, from the MSP is sent to the robot to guide the operation. As shown in the pink box in This paper includes the following contents. In (1)how to perceive the features of the uncertain operating object, (2)how to achieve make an automatic decision for the robotic operation,(3)how to achieve safety interaction between the robot and the uncertain operating object.Based on the above analysis, the following issues will be investigated in this paper:For the critical step of the pen-in-hole task, a mathematical description of the above problem was presented. As shown in Besides visual error and occlusion, the operating object may generate continuous dynamic effects due to the interaction process, which can increase uncertainty. The uncertainty can be expressed as Moreover, in practical application, the operation task performed by the robot is usually composed of several continuous nail hole operations. Each contact behavior induces dynamic interactions at the operational object connections, resulting in coupling effects of robot operational errors and system stability. This coupling effect accumulates and increases over the course of the task. From the above description and analysis, it is clear that for each peg-in-hole operation, the robot must perform with high operational accuracy and apply appropriate forces to the operational object during continuous and large task volumes. That is, the contact force needs to satisfy:reliable .If the robot can make timely autonomy decisions based on the collected limited information to guide the subsequent movements, the number of contacts can be effectively reduced and thus the dynamic effects are reduced. In addition, it also reduces human involvement, which effectively avoids human errors and workload. Therefore, a variable The multi-sensor perception strategy is divided into two parts, i.e., interactive exploration and fusion decision, which are shown in In the case of imperfect vision sensors, the features of the uncertain operating object are explored by integrating three sources of information. Given the position of the robotic end  according to the new Gaussian distribution is performed to obtain the particles:The random walk of particles is defined as:In the following section, based on the position information and force information of the robotic end and visual estimated operating object features at the current moment, probability calculations are performed on each sampled particle to recursively design a Gaussian distribution so that the features of the uncertain operating object at each moment can be estimated.The robotic end position The contact force When the direction of the end contact force is inside the friction cone, the particle corresponds to the uncertain operating object with the highest probability, as shown in When the robot starts to move toward the operation object, vision can easily provide feature information of the object. The current moment object features can be estimated by the Euclidean distance between To improve the accuracy of the estimation, the posterior probabilities obtained from these two information sources are integrated to obtain the weighting coefficient of the particles. At a certain moment, given the end position and robotic contact force, the weight of the particle can be expressed as:Redefine the Gaussian distribution of particles as:Since there may be errors in the shape and position of the uncertain object after sampling and estimation, historical information and rules of inertia thinking are used to correct the estimated value of the features of the uncertain object to improve the accuracy of the estimation, as shown in (1) Memory adjustment correction methodThe shape features of the uncertain object are calculated based on the estimated value, after completing the sampling estimation. According to the uncertain object proposed in n-th element in According to the estimated value To obtain the most suitable correction angle, historical information is introduced to participate in the correction calculation. The history information collection of angle is defined as The angle error The posterior probability of the angle based on the angle error A simple fuzzy system with two fuzzy rules is established, and the fuzzy membership function is:The history information at the current moment is defined as The depth In order to obtain the most suitable correction depth, historical information is introduced to participate in the correction calculation. The history information collection of depth is defined as The depth error The posterior probability of the depth based on the depth error The history information at the current moment is defined as After obtaining the correction angle and correction depth, the initial correction value (2) Inertia thinking correction methodHuman tactile perception is an iterative process of recognition–decision–correction. In this part, the features of the uncertain object will be corrected based on the result of the fused decision and the sensor information. For the sake of correcting the estimated features of the uncertain object, a novel method is proposed based on inertial thinking in the following.Rule 1: When the robot moves towards the target position, the end of the robot should gradually approach the target position,If In the process of exploration, if humans perceive a collision, they will explore in the opposite direction.Rule 2: If the end of the robot collides with The end of the robot collides with The end of the robot collides with After the correction is completed, As shown in The D-S theory is used to analyze the position information provided by the robot and the force information provided by the force sensor. This fusion decision strategy provides a mechanism to represent and process the uncertainty from robots and force sensors. Moreover, Dempster’s combination rules  are usedFirst, the recognition framework The main elements of the recognition framework, Next, the basic probability assignment (BPA) of different categories to which different information sources belong is calculated. In the method in this paper, the fuzzy naive Bayes method is used to generate BPA for each category and assign it to D-S theory. Let According to D-S theory, there is a compound hypothesis that an object may belong to both For systems with multiple information sources, the overall BPA , After the fusion is completed, the entire decision-making process has changed from multiple information sources to single information source decision-making. Choose the hypothesis with the greatest probability as the predicted category of the sample in the test data. Finally, the result of the task assessment The n-degree-of-freedom robot dynamics are:The above formula is rewritten into Cartesian coordinate form as:Rewrite the above formula further:In this part, the uncertain of the robot model and the uncertain of the object are considered in the design of the robot controller. In the outer loop, the pliability model is introduced and combined with a multi-sensor perception strategy to perceive the object and provide a command position The pliability model is:The position error is defined as:Sliding mode is defined as:The robot reference state is defined as:The controller can be designed as:Simulation and physical robot task experiments are designed for the narrow uncertain object. The proposed whole solution scheme is evaluated in terms of intelligence, autonomy and safety. (1) accuracy of interactive exploration for the features of the uncertain object Let Impedance coefficient:Sliding mode parameters:Inertial matrix estimates:In the simulation, the initial position of the robot is set near the operation object . The initial features of the uncertain object are given and are in error with the expected value. Since the estimates of our method are based on the previous moment’s ones each time, the range of applicability of interactive exploration can be tested by adjusting the initial error. Considering that the entire operating object should be stabilized after the task is completed, the preload force is introduced and was set to 5 N.We give the initial features of the uncertain object, and the errors of these features (target position) from the expected values are −0.8 mm, −3 mm, 0, 3 mm and 10 mm, respectively. As can be seen from In addition, to verify the advantages of the proposed method in terms of estimation accuracy, we also evaluate the MAC and ITC methods. The simulation results of MAC are represented in In During the ITC design stage, we consider four possible scenarios that can cause inaccurate estimation (only three scenarios have appeared in the results of many simulations so far). Moreover, with the introduction of the ITC, the estimation results of the interactive exploration method are more accurate. Therefore, the validity of the design in this paper was verified.The fusion decision results can be viewed as a classification of the current task progress (finished and unfinished). Therefore, the confusion matrix is proposed to evaluate the performance of the fusion decision strategy. As shown in The result in To further validate the performance of the proposed strategy in more complex and uncertain objects, a peg-in-hole experiment with dynamic effects is designed, and the experimental equipment is shown in Two sets of workpieces (operating tools and simulation components) are used in the experiment to verify the versatility of the proposed method for different workpieces. As shown in Operation tool 1: full length is 176 mm, diameter of bottom end is 20 mm, diameter of top end is 40 mm, tilt angle Operation object 1: hole deep is 80 mm, hole diameter of bottom end is 20 mm, hole diameter of top end is 40 mm, and tilt angle Operation tool 2: full length is 197 mm, diameter of bottom end is 19 mm, diameter of top end is 13 mm, tilt angle Operation object 2: hole deep is 32 mm, hole diameter of bottom end is 13 mm, hole diameter of top end is 20 mm, and tilt angle In the experiment, the basic parameters used in the control system are as follows.Impedance coefficient:We first show the result of the fusion decision by the position and force on the end of the robot with the finished and unfinished operation, as shown in Some details are shown in As shown in In this section, we conduct experiments on the proposed system under the dynamic effects conditions of In the previous experiment, we illustrated the generality of the proposed system in terms of safety. To verify the safety attributed to the proposed method, we compare the proposed system with two benchmark experiments: (1) guide operation by MSP only, without impedance control, and (2) variable impedance control only, without MSP. For each method, experiments are performed sequentially at three types of dynamic effects. As shown in (1) The maximum contact force (orange) is demonstrated using only MSP-guided operation without impedance control. This result is expected and indicates that a pliability model is needed to accomplish the operation task to minimize the contact force between the robot and the uncertain object. Although the target position is updated by MSP, it leads to large contact forces when guiding the robot movement, which is undesirable since the robot–object interaction is not considered.(2) Variable impedance control is a classical approach to deal with the problem of robot interaction with an uncertain object, which adjusts the impedance parameters online by contact forces to accommodate the uncertain object with dynamic effects. The approach using variable impedance control only without MSP (green) presents multiple peaks, which means that the robot guided only by variable impedance without MSP may lead to frequent collisions and possibly even divergence during operation. Frequent collisions can also exacerbate dynamic effects.(3) In summary, the proposed method (blue) demonstrates minimal contact forces and no multiple collisions. It indicates that the method proposed in this paper is effective.In this paper, we focused on the issue of robotic autonomy operations in the real-world unstructured environment. Missing or inaccurate visual information was also considered due to confined space limitations and interference from complex environments. In order to satisfy the three requirements of intelligence, autonomy and safety, a multi-sensor perception strategy for the robot was proposed to achieve a humanoid autonomy operation process integrating exploration, decision and guidance with uncertain objects. In terms of intelligence, it was our goal to obtain information about the features of the uncertain object. An interactive exploration method using Bayesian networks was proposed to integrate multimodal information and accurately estimate the features of the uncertain object, which can comprehensively perceive the features of the uncertain object even in the presence of visual occlusion. The exploration approach was general for static objects and multiple dynamic objects. In terms of safety, the proposed system was capable of performing tasks under the uncertain object and minimizing the forces of interaction between the robot and the uncertain object. In terms of autonomy, the proposed fusion decision strategy has enabled autonomous start–stop and guided subsequent operations of the robot, which could reduce the workload of the operators. Based on the D-S theory, the evidence information provided by multiple information sources was fused to judge the task progress, which gives the robot human-like decision-making capability. Moreover, the pliability model was combined with an MSP to reduce the interaction forces during operation. In general, the multi-sensor-based solution scheme showed fine performance for robotic operation tasks with both position and force requirements.There is one more area where the proposed method could be improved. The inclusion of a pose adjustment strategy before the MSP will improve the generality of the method for pegs and holes with multiple angles. This attitude adjustment strategy performs a tilt-right–rotate–alignment process to bring the robotic end into an ideal attitude for operation.


Cassava is a key food security crop in Central Africa, but its production depends largely on the use of local farmers’ varieties characterized by inherently low yield which is compounded by generally high susceptibility to various growth and yield-limiting pests and diseases. Improved cassava genotypes have demonstrated the potential to substantially improve cassava’s contribution to food security and the development of the cassava industry and the improvement of nutrition status elsewhere in Western Africa. Eleven improved cassava genotypes were compared with a local landrace (LMR) used as a check under field conditions over two years in eight locations, grouped in four agro-ecologies in Cameroon. Pest and disease abundance/incidence and damage severity were evaluated. At harvest, root yield and carotenoid content were measured. Best linear unbiased predictors showed the lowest breeding value for LMR with the cassava mosaic virus disease (+ 66.40 ± 2.42) compared with 1.00 ± 0.02% for the most susceptible improved genotype. Two genotypes (I010040-27 and I011797) stood out for having higher predicted fresh root yield means which were at least 16 times greater compared with LMR. Predicted total carotenoid content was the highest (+ 5.04 ± 0.17) for improved genotype I070593 compared with LMR which showed the lowest (− 3.90 ± 0.06%) and could contribute to the alleviation of vitamin A deficiency from cassava-based food systems. Diffusion of high-yielding and nutritious genotypes could alleviate food and nutritional security in Central Africa. Manihot esculenta Crantz), is the main source of calories for 800 million people across the globe1. No other continent depends on cassava to feed as many people as does Africa2. Its production is estimated at 178 million tons—61% of global production—produced annually in sub-Saharan Africa (SSA)3. Population growth and demands by emerging cassava industries are increasingly straining current production capacities that rely widely on low-yielding farmers’ local varieties that are particularly susceptible to widespread and emerging pests and diseases such as cassava mosaic virus disease, cassava brown streak virus disease, and cassava whiteflies8. Moreover, the local varieties are deficient in micronutrients, thus their consumption could lead to micronutrient deficiency, also referred to as hidden hunger9. Acute deficiencies in one or more micronutrients, including vitamins A, C, E, and minerals are reported in about two billion people9. In Cameroon, about 39% of preschool-aged children and 18% of pregnant women are deficient in vitamin A. For example, acute malnutrition is estimated at around 4.8% in the East region of Cameroon10. According to UNHCR (2018), nearly 265,000 refugees from the Central African Republic have sought shelter in eastern Cameroon, increasing the level of food insecurity in the region.Cassava  and its partners have developed new cassava genotypes to improve the livelihoods of millions of farmers in SSA. It is now widely recognized that traditional staple crops  are no longer providing adequate and enough solutions to the world’s food insecurity19; however, its production in Cameroon and elsewhere—particularly in Central Africa—is constrained by heavy yield losses from pests and diseases among which are: (1) cassava mosaic virus disease (CMD) transmitted largely by the whitefly Bemisia tabaci (G.) and by infected cassava stems used as vegetative propagules; (2) cassava anthracnose disease (CAD) caused by the fungus Colletotrichum gloeosporioides (Penz.) Sacc. and also vectored by Pseudotheraptus devastans Dist. (Het. Coreidae); and (3) cassava green mite (CGM) Mononychellus tanajoa (B.)23. CMD is the most challenging disease as it can cause 25–90% yield losses, with substantial negative impact on people’s livelihoods24, particularly where CMD-susceptible traditional farmers cassava varieties are used compared with the CMD-resistant improved varieties8. Host plant resistance provides the cheapest and simplest technology where chemical inputs are not available or affordable.Cassava is resistant to adverse environments25 and for sustainable improvement in the lives of millions of people in developing countries, particularly in Africa and South Asia27.Crop improvement has traditionally focused on increasing crop yield and building resistance to pests and diseases. In recent years, enhancement of crops nutrient has been increasingly incorporated in breeding programs. Biofortification of staple food crops like cassava has been advocated as one of the cost-effective solutions to combat the scourge of micronutrient malnutrition32. In a previous study8, we evaluated a set of 18 cassava genotypes, mostly oriented toward industrial processing, across eight environments in Cameroon to assess the level of stability of their yield and pest and disease resistance. The principal objective of the present study was to evaluate and select new cassava genotypes suitable for non-fermented products prepared using a single-step process after peeling (boiling or frying) and with high resistance to CMD and other pests, and with higher provitamin A content under specific environments. Broadly, the results from this Cameroon study are likely to be extended to countries sharing similar ecologies, mainly in the Congo Basin, as Cameroon, with its varied environments, is considered the gateway to the rest of Central Africa.Genotype x environment interaction is the greatest challenge to breeders due to differential genotypic responses across environmentsThe levels of soil pH and various soil chemical characteristics varied among locations. Soil pH in Foumbot (6.06 ± 0.02) differed significantly from the other locations, with Bambui and Njombe being most acidic (3.93 ± 0.01 and 3.93 ± 0.06 respectively). The highest organic carbon content (6.96 ± 0.03) was recorded in Bambui. Ekona, Foumbot, and Meiganga differed from the other locations with their higher level of Ca, Mg, and P. Meyomessala soil had the highest sand content while Njombe and Bambui soils had the highest clay and silt respectively  , which showed the lowest CAD incidence,—to + 4.90 ± 3.21 for LMR which also had the highest CAD severity (+ 0.07 ± 0.01) (Table p < 0.001) in genotype x environment interactions for all the parameters  and severity (0.64) compared with CAD. The linear mixed model test indicated highly significant effects  was predicted on I090616, while the lowest was on I071026 (− 3.73 ± 4.80) (Table Two genotypes (I010040-27 and I011797) stood out for having the highest predicted fresh root yield means among all the tested genotypes Table . The yiep < 0.001) for genotype and environmental interactions for all tested traits  among the traits was estimated from TCC Table . The lints Table .The quadrants in Fig. 8, provide a highly important set of data on the effects of genotype and environment on 28 cassava genotypes that are in advanced stages of development. Moreover, the two studies together, are a rarity in evaluations that covers a very wide spectrum of pest/disease resistance, yield, and nutritional value, all with a significant potential contribution to food and nutritional security in Central Africa. The four agroecological zones in which the genotypes were tested are representative of the agro-ecologies of the Congo Basin, including nearly all states in Central Africa, except the Sahelian zone33. Importantly, we found that the environment was not the main determinant of a genotype response to cassava mosaic virus (CMD) as the heritability was close to one; this opens the possibility of introducing genotypes with good performance in terms of productivity, yield stability, and resistance to pest and disease into areas with similar characteristics as in Cameroon. Indeed, as with varieties for industrial processing, the tested genotypes were initially selected based on their resistance to CMD and yield, as well as provitamin A content for the yellow root genotypes, traits in which variability comes from genetic differences, with very little contribution from environmental factors34. We noted, however, two genotypes, I070593 and LMR, that had CMD severity scores of 2.8 and 2.6 respectively on average for both years, although the incidence on the same genotypes was nearly nil (less than 2% on average). Our two checks, I010040-27 and LMR, displayed on average the same incidence and severity as in the previous study8; however, the other improved varieties  were five-fold more resistant to CMD compared with the 16 of the previous study, thus confirming the improvement made on the current set of varieties with respect to CMD resistance and the necessity to disseminate those genotypes. The significant interaction observed between environment and genotype for CMD infection could be related to the virus strains present in the locations as previous studies established the presence of various CMD strains in Cameroon, particularly the Ugandan variant which is the most virulent and present in the east region (Gamboula)35.Multi-environment experiments are a primary focus in plant breeding programs; therefore, their prediction accuracy, compared with observed value, is crucial for selection recommendation of cultivars, and the identification of mega-environments. This study showed variable responses of a set of new cassava genotypes for food and nutritional value in contrasting environments in Cameroon, thus justifying the necessity to evaluate genotype by environment interactions. This study, together with the previous study conducted in the same locations, but with different genotypes36. Contrary to CMD, Cassava Anthracnose Disease (CAD) was found mostly in the forest areas where relative humidity and rainfall significantly influence the levels of CAD inoculum pressure, in addition to favoring the development of its vector Pseudotheraptus devastans Dist (Het. Coreidae)23. CAD severity was statistically similar on all genotypes, but with low incidence. Genotype I071026 did not show CAD symptoms during the 2nd year. CAD has become an economic threat to cassava production as severe outbreaks have been reported22. Affected plants display necrotic lesions on leaves and stem, reducing planting material availability37. Careful selection of clean planting material and good field maintenance (timely weeding and field aeration) could help in reducing CAD pressure in the forest zone where it is most prevalent.Typical CMD symptoms on cassava plants are misshapen leaves which hamper the growth of the plant and reduce root yields, hence lowering productivity and profitability8; however, the lack of CMD symptoms could mean that whiteflies did not carry enough virus loads to efficiently transmit the virus, as an increase in whitefly numbers can lead to the higher efficiency of CMD transmission on cassava38 and also could likely be explained by the resistance mechanism of this cassava line. This contradicts other findings39 which reported that 10 whiteflies per plant constituted an adequate population for the spread of CMD due to their persistent mode of transmission.Interestingly, the genotype I090521 did not show any CMD symptoms over the two trial years despite harboring the highest number of whiteflies per plant as previously demonstrated with four genotypes 3. Therefore, promoting the new genotypes with an average yield of 31 t/ha could potentially increase production in Cameroon to 12,353,035 tons with the current production areas  which would represent an increase from 11 to 24% of the cassava production in Central Africa. It is worth noting the sharp increase in yield of the check I010040-27 which almost doubled within two years after its first evaluation. Cassava's potential to alleviate food and nutritional security in Central Africa would substantially increase if neighboring countries sharing similar ecologies with Cameroon —where cassava is an essential food security crop—also adopt the new genotypes.The observed resistance to major disease was translated into a higher yield for the improved genotypes.These varieties could also be carriers of genes for higher yield. Current cassava production in Cameroon  stands at 5,798,909 tons  with an average yield of 14.5 t/ha (resp. 8.9 t/ha)40. Dry matter content was constant for all genotypes across all environments. As a polygenic trait, dry matter varies from one genotype to another (20–40%) and is usually stable across locations41. Genotypes with high dry matter (> 30%) are generally mealy with high starch content44, making them suitable for processing into flour and starch which have been shown to improve the potential for cassava adoption and commercialization for income generation and livelihoods improvement45.Two genotypes  produced the highest and most stable fresh root yield across locations, which are qualities that favors them for dissemination throughout the targeted environments to improve cassava yields and hence food security. Overall, tested cassava genotypes performed best at Ekona and Bambui, probably because of the high K and Organic C in their soils8, thus justifying the improvement of their nutritional content and the need to promote them for nutritional security in central Africa. Total carotenoid content is known to be affected by the location in which the genotype is grown, especially in sweet potato (Ipomoea batatas (L.)46, but it appears not to be the case for cassava as the levels of provitamin A (β-carotene) of a genotype were stable across all the different environments used in the present study and elsewhere47. These results are very encouraging, but it would be necessary to conserve as much of the provitamin A as possible when cassava is transformed into different products—including cooking—to harness the full potential of biofortified cassava’s contribution to reductions in vitamin A deficiency48.Nutritionally-biofortified genotypes evaluated in this study contain up to 6-folds higher provitamin A β-carotene compared with the local genotype, underlining the potential contribution of the biofortified genotypes to nutritional security in Cameroon and central Africa. These varieties have almost 3 times (up to 11.1 μg/g) the level of carotenoids contents of our previous set of yellow varietiesThis study identified high-yielding cassava genotypes with higher levels of resistance/tolerance to pests and diseases and with elevated provitamin A-improved nutritional content. Disseminating the selected genotypes for cassava production in Cameroon—and by extension elsewhere in Central Africa—would improve cassava production for food and nutritional security. Despite the good performance of most of the tested genotypes, there is also a strong need to conduct consumer preference studies to match the usability of these newly developed varieties to actual use of cassava in the area of introduction to ensure proper adoption by the end-users in the various agro-ecologies.www.cassavabase.org). All improved genotypes were tested along with two cassava genotypes from our recent work8 which were used here as references (1) for high yield (I010040-27) and (2) for high susceptibility to cassava mosaic virus disease (LMR). Including reference genotypes is a common practice in such studies. The present and previous8 study were conducted in the same locations (not same fields) in Cameroon and followed a similar methodology to provide a basis for comparisons between them. The first study8 used mostly white-fleshed genotypes oriented toward industrial processing, while the second (present) study emphasized a new set of white-fleshed genotypes for boiling and yellow-fleshed genotypes with higher total carotenoids content. The studies complied with the local and national regulations in Cameroon.IITA had the permission to collect all the plants used in this study. The improved cassava genotypes used were selected in Nigeria by the IITA cassava breeding unit and sent to IITA Cameroon. Accession names and their pedigree are available in the cassava database Table  . The locations of Mbalmayo, Meyomessala, and Gamboula are in the humid forest zone which is characterized by a bimodal rainfall pattern, while the locations of Njombe and Ekona are in the humid forest with monomodal rainfall patterns. The locations of Foumbot and Bambui are in the Western Highlands while Meiganga is in the high Guinean savannah Fig. . VegetatThe trial was set-up in a completely randomized block design with three replicate blocks comprised of 5 × 6 m plots of 42 plants (with 1 m spacing between and within rows) of each of the 12 genotypes. Plants were grown under rainfed conditions for 12 months and managed according to prevailing farmer practices. Pesticides and fertilizers were not used at any time during the trials. Plots were manually weeded with machete and hoe as needed.49. Total N was determined from a wet acid digest50 and analyzed by colorimetric analysis. Exchangeable Ca, Mg, K, and P were extracted using the Mehlich-3 procedure51, and the cations were determined by flame atomic absorption spectrophotometry. Exchangeable P from the resulting extract above was determined with the molybdate blue procedure52. Particle size was determined with a hydrometer.At each location, 5 soil samples were collected from each plot and mixed thoroughly in a plastic basin to obtain a composite soil sample. A subsample of 250 g of soil from each plot was used for the determination of various soil physical and chemical properties at the IITA-Cameroon Analytical Laboratory. Soil samples were air-dried and ground to pass through a 2-mm sieve. The sample was further ground to pass through a 0.5 mm sieve for C and N analysis. Soil pH in water was determined in a 1:2.5 (w/v) soil: water suspension. Organic C was determined by chromic acid digestion and spectrophotometric analysisBemisia tabaci Gennadius) was counted on the top  of the plant, while the number of nymphs was counted on the 14th fully developed leaf53. The cassava green mite (CGM) was counted on the fifth fully developed leaf using a head lens . CMD incidence (presence/absence) was scored on the whole plant foliage, while CAD incidence and severity were scored based on disease symptoms on the stems. Disease and damage scoring was done on a scale of 1 (no symptoms observed) to 5 (severe symptoms on plant parts)54.Cassava disease incidence and severity were evaluated at 3, 6, and 9 months after planting on 10 plants per plot, excluding border rows, while alternating plants within a row. On each plant, the number of whitefly adults , above-ground biomass (stems and leaves) and storage roots were weighed using Macro scales type with optional accessories . Samples of 500 g of the fresh root of each genotype were collected and oven-dried at 60 °C for 48 h to measure their dry matter content. Total carotenoid content (TCC) in storage roots was determined within 24 h of harvest using iCheck Carotene following the BioAnalyt protocolIncidence data was calculated for CMD and CAD for each plot by calculating the percentage of sampled plants that showed symptoms of the diseases.56 to perform a stability analysis of multi-environment trial data (MET57) using parametric and non-parametric. MET allows the identification of genotypes that display a small temporal variability—which is desired by breeders and is beneficial to growers, or cultivars that are consistent from location to location—which is desired by and is beneficial to seed companies and breeders57. Incidence data were calculated for CMD and CAD by calculating the percentage of sampled plants that showed symptoms of the diseases. Whitefly and CGM densities were log-transformed to reduce heteroscedasticity inherent in insect and mite counts. The best linear unbiased prediction (BLUP) was used to predict Breeding Values (BV) of each genotype for cassava mosaic disease incidence and severity, cassava anthracnose disease incidence and severity, whitefly and cassava green mite densities, fresh root yield (FRY), biomass (BY), dry matter (DM), total carotenoid content (TCC), CMD and CAD severity. The BLUP was performed using the linear mixed model's approach (ANOVA) that considered cassava genotype as fixed factor and locations and year as random factors. The model also included genotype by location (G × L) interactions.We used the metan package of the R 3.6.2 software60.To select genotypes that combine high performance and stability, we introduced the weighted average of absolute scores from the singular value decomposition of the matrix of best linear unbiased predictions for the genotype × environment interaction effects generated by a linear mixed effect model index (WAASB), which is a superiority index that allows weighting between performance  and stability (WAASB index). The first step is rescaling FRY and WAASB; CMD and WAASB that can be directly used to compare genotypes. The best values for FRY and CMD are the highest value and for WAASB is the lowest value


Scientific Reports 10.1038/s41598-020-77405-3, published online 24 November 2020Correction to: The original version of this Article contained an error. An affiliation was omitted for the author Jan Komdeur, which is now listed as Affiliation 4:Nature Seychelles, Victoria, Mahé, SeychellesThis has now been corrected in the HTML and PDF versions of this Article, and in the accompanying Supplemental Material.


Nanoporous Shape Memory Alloys (SMA) are widely used in aerospace, military industry, medical and health and other fields. More and more attention has been paid to its mechanical properties. In particular, when the size of the pores is reduced to the nanometer level, the effect of the surface effect of the nanoporous material on the mechanical properties of the SMA will increase sharply, and the residual strain of the SMA material will change with the nanoporosity. In this work, the expression of Young’s modulus of nanopore SMA considering surface effects is first derived, which is a function of nanoporosity and nanopore size. Based on the obtained Young’s modulus, a constitutive model of nanoporous SMA considering residual strain is established. Then, the stress–strain curve of dense SMA based on the new constitutive model is drawn by numerical method. The results are in good agreement with the simulation results in the published literature. Finally, the stress-strain curves of SMA with different nanoporosities are drawn, and it is concluded that the Young’s modulus and strength limit decrease with the increase of nanoporosity. Functionally gradient materials and porous materials are new smart materials developed to meet the needs of modern aerospace industries and other high-tech fields ,2,3,4. AAs the size of the material decreases, the properties of the material will change. For example, microcarbon has higher power storage performance and is often used as a supercapacitor ,10,11. PResearch into the macro-mechanical properties of nanoporous materials with interfacial effects has attracted more and more attention from scholars at home and abroad in recent years. Sharma predicted that the effective elastic modulus of nanoporous materials depends on the size of pores ,15. Xun Most of the above studies are about porous carbon or single metal nanoporous materials, but the research on nanoporous SMA is rarely mentioned, especially the effect of size on material properties. In view of this, the relationship between the mechanical properties of SMA materials with nanopores and the surface effects, especially the relationship between the mechanical properties of SMA materials and different nanopore diameters or nanoporosities, respectively, is discussed in this work. Combining the framework of micromechanics theory including surface effect, firstly, the effective Young’s modulus of nanoporous SMA is calculated by composite material equivalent method. A constitutive model of SMA with nanopores considering surface effect and residual strain is then established.When the size of the material reaches the nanometer level, the surface effect needs to be considered. The stress corresponding to the surface effect is the surface stress, which can be defined in many ways. Nix et al. proposed an atomic interpretation of surface/interface stress, in which the relationship between surface stress and strain is attributed to the change in the bonding environment of atomic bonds . Bottomlensor εs , which iSun et al. pointed out that when considering the change of the stress field, the effective elastic properties will be affected by the surface stress . Therefo follows (3)κ3=3κApplying the above theory to nanoporous SMA materials, using SMA as the matrix, and degenerating the nano-inhomogeneous inclusion into nanopores, i.e., (There are four unknown constants and two unknown quantities r models .(18)ξ={However, it is difficult to measure the elasticity Lame constants Then the Young’s modulusResidual strain refers to the strain that the material cannot return to its original state after being unloaded. Shape memory alloys with large porosity exhibit greater macroscopic residual strain. It has been found that the residual strain increases approximately linearly with the increase of porosity by Sourav Gur et al. . In ordeThe research on the constitutive model of SMA has been fully developed in recent decades, and it has been reported in detail in theoretical research and experiments ,28. In tFor SMA with nanopores, the constitutive model considering the surface effect and the porosity of nanopores can be expressed as follows:. whereξnp={0   In order to obtain the analytical solution of the model in this paper, the surface elastic constants of aluminum are assumed to be the surface elastic constants of nanoporous SMA. The surface elastic constants of aluminum are taken from the papers of Miller and Shenoy, in which two sets of surface moduli are used, namely,2=−92.41 . The numvSMA=0.3 ).For brevity, define It is seen from  by Zhao . The surThe variations of the Young’s modulus The value of The relationship between the normalized Young’s modulus From In this paper, the effective Young’s modulus of SMA with nanopores can be obtained. Gur et al. established a nanoporous NiTi shape memory alloy model with different porosities. The initial size of the model is 250 Å × 250 Å × 250 Å, and the pore size is 10–50 Å. And through molecular dynamics simulation, the stress-strain curves of NiTi shape memory alloys with different porosities were obtained , from whIn this work, based on the micromechanical framework and considering the surface effect, the effective Young’s modulus of the SMA with nanopores is obtained. Based on Young’s modulus and residual strain, a constitutive model of nanoporous SMA is established. In the numerical results, the effective Young’s modulus is plotted against nanopore radius, nanoporosity and martensite volume fraction, and the stress–strain curves of SMAs with different nanoporosities are plotted.The effective Young’s modulus of nanoporous SMA, which is independent of the volume fraction of martensite, depends on the radius of nanopores and nanoporosity.The surface effect decreases with the increase of nano pore size, and the effective Young’s modulus of nanoporous SMA is close to the macroscopic theory when the nano pore radius exceeds 50 nm.The constitutive model of nanoporous SMA is derived, which is in good agreement with the simulation data in the literature.


BPaL, a 6 month oral regimen composed of bedaquiline, pretomanid, and linezolid for treating extensively drug-resistant tuberculosis (XDR-TB) is a potential alternative for at least 20 months of individualized treatment regimens (ITR). The ITR has low tolerability, treatment adherence, and success rates, and hence to limit patient burden, loss to follow-up and the emergence of resistance it is essential to implement new DR-TB regimens. The objective of this study was to assess the acceptability, feasibility, and likelihood of implementing BPaL in Indonesia, Kyrgyzstan, and Nigeria.We conducted a concurrent mixed-methods study among a cross-section of health care workers, programmatic and laboratory stakeholders between May 2018 and May 2019. We conducted semi-structured interviews and focus group discussions to assess perceptions on acceptability and feasibility of implementing BPaL. We determined the proportions of a recoded 3-point Likert scale , as well as the overall likelihood of implementing BPaL  that participants graded per regimen, pre-defined aspect and country. We analysed the qualitative results using a deductive framework analysis.In total 188 stakeholders participated in this study: 63 from Kyrgyzstan, 51 from Indonesia, and 74 from Nigeria The majority were health care workers (110). Overall, 88% (146/166) of the stakeholders would likely implement BPaL once available. Overall acceptability for BPaL was high, especially patient friendliness was often rated as acceptable . In contrast, patient friendliness of the ITR was rated as acceptable by 45%. Stakeholders appreciated that BPaL would reduce workload and financial burden on the health care system. However, several stakeholders expressed concerns regarding BPaL safety (monitoring), long-term efficacy, and national regulatory requirements regarding introduction of the regimen. Stakeholders stressed the importance of addressing current health systems constraints as well, especially in treatment and safety monitoring systems.Acceptability and feasibility of the BPaL regimen is high among TB stakeholders in Indonesia, Kyrgyzstan, and Nigeria. The majority is willing to start using BPaL as the standard of care for eligible patients despite country-specific health system constraints.The online version contains supplementary material available at 10.1186/s12889-021-11427-y. Despite increasing access to new diagnostics and anti-tuberculosis (TB) medicines, treatment success rates for extensively drug-resistant TB (XDR-TB) remain low and contribute to the ongoing transmission of DR-TB . GloballThe Global Alliance for TB Drug Development (TB Alliance) has developed a 6 month oral regimen consisting of three drugs: bedaquiline (Bdq), the new drug pretomanid, and linezolid (Lzd). This BPaL regimen was successful in over 90% of patients with XDR-TB, multidrug resistant TB (MDR-TB) treatment failure, or intolerance to MDR-TB treatment in the Nix-TB trial . Side efImplementation of the BPaL regimen would entail essential changes in clinical and programmatic TB management . The redTo ensure rapid adoption after the regimen is endorsed by regulatory authorities, evidence is needed on health care system readiness, barriers and requirements among those implementing the intervention –13. The We used a concurrent mixed methods design. The qualitative component, consisting of semi-structured interviews and focus group discussions (FGD) among stakeholders, explored the acceptability and feasibility of seven aspects of PMDT, comparing ITR and BPaL. The seven aspects of PMDT were: patient baseline assessment and monitoring of treatment efficacy, treatment safety monitoring, patient friendliness, patient support, programmatic aspects, human resources, and procurement and supply chain management (PSCM).For the quantitative component of the study, we used a Likert scale to quantify how acceptable stakeholders perceived each PMDT aspect for ITR and BPaL, as well as the overall likelihood of implementing BPaL. We triangulated the two data types to explore if quantitative findings could be explained by the qualitative results.We conducted the study from May 2018 – May 2019 among health care workers , programmatic stakeholders  and laboratory stakeholders  in Indonesia, Kyrgyzstan, and Nigeria. Target participant numbers per subgroup are shown in Supplementary file We chose Indonesia, Kyrgyzstan, and Nigeria to depict various geographical settings , with differences in TB burden  and DR-TB) and health systems infrastructure. The estimated TB incidence per 100,000 population in 2018 was 316 in Indonesia, 116 in Kyrgyzstan and 219 in Nigeria . The estThe conceptual framework from Atun et al.  guided tWe developed the interview guide and questionnaire  and PMDT aspect. We also determined the proportion of stakeholder that chose likely, neutral and not likely per scenario of implementing BPaL as SoC. We stratified results by country.A total of 194 stakeholders participated in this study. Four Kyrgyz participants were excluded from all analyses due to inaudible recordings and two Kyrgyz participants were excluded due to declined consent for recording. Three stakeholders in Indonesia and three in Nigeria did not fill out the questionnaire for the quantitative part. Thus in total, 188 stakeholders were included in the qualitative data analysis and 182 in the quantitative analyses (97 and 94% respectively)  as the Nigerian health care worker: “ … (compared to the) individualized treatment regimen (there are many) benefits are … no matter how somebody tries, taking a drug for 20 months is not easy … in terms of adherence, … out of pocket cost, … side effects … (with the 6 months regimen) they (the patients) are going to be treated quickly and … resume their normal economic activities … I think there are more benefits for them.” [FGD]Another benefit was that stakeholders believed that the BPaL regimen would increase patients’ quality of life during treatment and would improve treatment adherence, which would contribute to higher treatment success (Table Indonesian caregiver: “Side effects (of BPaL are) … much less … compared to the individualized (regimen) … so for the patient’s level of … adherence … perhaps it’d be better because what happens so far, the patient cannot bear the side effects and becomes lost to follow up... he stops taking the medication.” [interview]Besides the reduction of side effects being a benefit, a challenge participants opted was about the side effects of (high-dose) Lzd, including myelosuppression (bone marrow suppression (which leads to reduced production of blood cells) and peripheral neuropathy  , it is very low the patient is dying slowly...” [FGD]In terms of benefits, stakeholders perceived BPaL to be more patient-friendly compared to the ITR resulting from its shorter treatment duration, lower pill burden per day, fewer anticipated side effects, lower financial burden, decreased requirements for higher level of care, and reduced patient discomfort (including risk of hearing loss) due to the removal of injectables Table .Nigerianss Table .Indonesin) Table . StakehoIndonesian health care worker: ( … ) we should pay attention to ( … ) supervise them (the patients) taking ( … ) the drugs … We have to provide counselling for the patients to remind them the importance of taking the drugs. It is the same.” [FGD]Participants thought the BPaL regimen would allow cutting costs for patient support due to its shorter duration, while they thought the type/form of patient support required was the same Table , includiIndonesian Programmatic Stakeholder: “The initial phase and this would be a challenge if it [BPaL] is (implemented) in Puskesmas [Indonesian primary health centres], in an outpatient setting … because we must still separate the patients that have been (tested) negative from the patients who are still positive..” [Interview]Despite the anticipated cost reduction for DR-TB treatment with BPaL, stakeholders from all countries considered current high costs of Bdq and Lzd a challenge . Some Kyrgyz and Nigerian stakeholders had experienced supply challenges with the introduction of the shorter regimen , Bdq and Delamanid (due to lack of registration). They therefore had concerns about sufficient supply of new drugs.Kyrgyz health care worker: “So, its (safety) is unclear yet. For example, with linezolid we notice that side effects are irreversible and with pretomanid we don’t know are they reversible or irreversible... it is not studied yet … ” [Interview]Indonesian and Nigerian stakeholders expressed challenges about current health systems gaps, especially at lower health care levels where BPaL may be implemented. These challenges included limited availability of ancillary drugs (Indonesia) and currently weak monitoring systems for regular haematology and electrocardiogram (ECG) (Nigeria). Stakeholders opted as practical requirement that safety monitoring and side effect management should be guaranteed and provision of ancillary drugs should be free of charge:Nigerian programmatic stakeholder: “We will have to strengthen our system to ensure that patients’ baseline and follow up investigations are done … when they are due so that we will be able to pick up any side effect at an early stage. If that is done, it will make it (BPaL) more friendly, but when that is not done patients will run away from it.” [Interview]For monitoring of treatment safety, stakeholders considered it a benefit that BPaL has shorter duration and less audiometry requirements. However, many also perceived challenges due to uncertainties about safety, possible need for intensified monitoring due to the high-dose of Lzd in the regimen and lack of experience with pretomanid:Nigerian health care worker: “In case we adopt the BPaL and somebody has a serious adverse event (so) that you need to discontinue the linezolid, then what will happen to the potency of the regimen? … If you need to discontinue one of the drugs, what happens to the efficacy of the regimen?” [FGD]Another major challenge expressed by Kyrgyz and Nigerian stakeholders was on safety concerns and the applicability of BPaL among children, pregnant women, and patients with comorbidities.Although some participants perceived the current expected low prevalence of drug resistance to drugs in the BPaL regimen as beneficial, participants from all countries had considered the emergence of resistance to BPaL or its components as a challenge. Nigerian health care workers were also concerned about baseline Lzd resistance as the drug is widely used for other diseases. Other challenges mentioned were about dose related Lzd intolerance and efficacy of the regimen when continuing treatment with only two drugs contributing to resistance to the remaining drugs or weakened regimen efficacy:In Indonesia and Nigeria, the lack of diagnostics and Drug Susceptibility Testing (DST) capacity for regimen allocation was expressed to be an important health systems challenge. This included the lack of access to GeneXpert MTB/RIF and/or second-line line probe assay testing in some areas, and the lack of DST capacity for Bdq and Lzd with liquid culture or genetic sequencing on a large scale.Kyrgyz programmatic stakeholder: “Every patient should have an individual approach. Seriously ill patients with side effects, with additional comorbidities they need a completely different approach.” [Interview]Moreover, stakeholders stressed the importance of introducing BPaL under operational research conditions. The need was expressed for clear local guidelines, capacity building, and training on the use of BPaL. Stakeholders flagged the need for training on monitoring and management of DR TB treatment, related adverse events, and guidance on dealing with patients who fail on a regimen. Clear guidelines on Treatment efficacy- and safety monitoring, management of adverse events, as well as patient support would be needed to support decentralized implementation.Stakeholders expressed the need for clinical studies in certain groups and in a national context. They expressed the need for adjusted treatment guidelines among specific groups:Other crucial practical requirements expressed for BPaL implementation were the needs for diagnostic capacity for DR-TB, regimen design including the drug composition of only three drugs Table . PSCM plWe assessed the acceptability and feasibility of implementing BPaL among key stakeholders in TB care and management from Indonesia, Kyrgyzstan, and Nigeria. Study participants found BPaL more acceptable than the ITR because of anticipated benefits such as improved patient-friendliness and reduced health system burden as a result of increased patient-friendliness, likelihood of improved adherence and anticipated reduced cost of BPaL. Additionally, stakeholders considered the implementation of BPaL feasible within the local health care infrastructure if efforts are undertaken to address practical requirements such as gaps in current treatment and safety monitoring systems that have become more apparent with introduction of recent new drugs and regimens as well as efficient diagnostic and DST capacity.Triangulating the qualitative and quantitative results indicated higher overall patient-friendliness score for BPaL (93%) in comparison to the ITR (45%) could be linked to stakeholders’ anticipated patient challenges with the current ITR which will be improved with BPaL, i.e. shorter duration, absence of injectables, lower pill burden, and lower financial burden to the patient. The shortened treatment duration and reduced costs may explain the higher overall acceptability of BPaL patient support in comparison to the ITR (85% vs. 69%). The higher overall acceptability of programmatic aspects of BPaL (83%) as compared to the ITR (60%) might be linked to the anticipated benefits of improved treatment outcomes as well as reduced financial burden to the health system due to the shorter treatment duration and increased possibility for the decentralization of treatment provision. Higher acceptability scores for the baseline assessment and treatment efficacy monitoring may be driven by stakeholders perceiving BPaL as beneficial in terms of being less burdensome and cost-saving as compared to the ITR. The higher acceptability for human resources for BPaL (79% vs. 59%) could be linked to the benefit of reduced burden on health care workers. The higher acceptability of PSCM (BPaL 80% vs. ITR 67%) may be explained by stakeholders’ positive expectation that PSCM will become simpler, with only three drugs compared to the 15 in ITR. Acceptability ratings in Indonesia may be lower due to concerns about complexities relating to local regulatory requirements and approvals, along with requirements to procure linezolid locally at a very high price. Similar acceptability scores on the treatment safety monitoring on BPaL and ITR may be explained by the expected benefits such as shorter duration (resulting in less treatment monitoring visits and actions) being offset by challenges relating to BPaL safety, and current health systems gaps.Our findings aligned with those of Thomas et al. , and VegMany stakeholders were especially concerned about the side effects of Lzd, including myelosuppression and neuropathy. The ZeNix trial is assessing the efficacy, safety and tolerability of various doses and durations of Lzd in the BPaL regimen . ConsequThe stakeholders showed concern regarding the potential emergence of resistance to novel drugs such as Bdq, which highlights the need for development of rapid DST for new medicines . CurrentThis study has some limitations. We did not include patients in this study. We aimed to represent their experiences indirectly by interviewing health care workers. As per the design of the assessment, many questions regarding the BPaL regimen were of a hypothetical nature and participants did not have any practical experience with BPaL at the time they were interviewed. Therefore, there may have been misconceptions leading to biased perceptions around BPaL. To mitigate these biases we provided each participant with standardized information about BPaL based on the available evidence from the Nix-TB trial. We used convenience sampling for selection of our interviewees. We acknowledge that this method may lead to a non-random sample. We aimed to limit this bias by inviting participants based on a clear guidance on expertise and positions. Another limitation was that the data collection tools were only piloted in Nigeria, the translated tools were not piloted which could have caused misinterpretation due to lingual and cultural differences. Each country employed at least 1 but no more than 3 interviewers to conduct interviews. This may have caused variability, which we tried to minimize by training of interviewers and standardizing semi-structured questionnaires. We addressed this by having an interviewer present who speaks the local language and as we reached data saturation, we do not expect the variability to have limited the quality and richness of our qualitative data.To our knowledge, this is the first study to assess the acceptability and feasibility of the implementation of the BPaL regimen compared to current treatment options, thus providing unique insights from a health care system perspective. The participants appreciated being engaged in identifying and discussing concerns on safety and capacity early on; the richness of the discussions and the findings highlighted the usefulness of early stakeholder engagement when developing implementation strategies for new drugs and regimens. Studies using similar methods could be relevant to conduct future implementation research for a variety of novel drug interventions. A broader perspective should be obtained by also assessing patient perspectives. This limitation notwithstanding, our study provides some baseline evidence that could be useful for the conduct of more robust studies on this, and related research topics.Our assessment provides rich information from different stakeholder groups on perceptions and expectations on the BPaL regimen. It shows that the adoption of BPaL in three high DR-TB burden countries will be accepted and feasible. BPaL could increase the treatment success rate and alleviate the individual and health care system burden of DR-TB. Active TB drug-safety monitoring and management is crucial to address concerns on linezolid safety. National strategic plans should incorporate both the identified and anticipated country-specific challenges and requirements to facilitate smooth roll out of the BPaL regimen.Additional file 1.Additional file 2.Additional file 3.


To evaluate the relationship between pancreatic parenchyma loss and early postoperative hyperglycemia in patients with benign pancreatic diseases.A total of 171 patients with benign pancreatic tumors or chronic pancreatitis, whose preoperative fasting blood glucose (FBG) was normal and who underwent partial pancreatectomy were reviewed. The pancreatic volume was measured by CT imaging before and after the operation. According to their different pancreatic resection volume (PRV), 171 patients were divided into five groups: < 30%, 30%–39%, 40%–49%, 50%–59%, and ≥ 60%. The correlation between the PRV and postoperative FBG was investigated. According to the postoperative FBG value, the patients were divided into a hyperglycemia group (HG) and nonhyperglycemia group (non-HG) to explore the best cutoff value of the PRV between the two groups.R = 0.727 and 0.651, respectively). ROC curve analysis showed that the best cutoff value of the PRV between the HG (n = 84) and non-HG (n = 87) was 39.95% with an AUC = 0.898; the sensitivity was 89.29%, and the specificity was 82.76%.There were significant differences in the postoperative FBG among the five groups . The PRV was positively correlated with postoperative FBG in the benign tumor group and chronic pancreatitis group (There was a linear positive correlation between the postoperative FBG level and PRV. Patients with a PRV ≥ 40% are more likely to develop early postoperative hyperglycemia. In recent years, the number of surgeries for benign pancreatic diseases has increased rapidly , 2. On tThe pancreas is an important endocrine organ in the human body. Loss of the pancreatic parenchyma directly leads to decreases in the numbers of multiple endocrine cells  and affects the secretion of hormones such as insulin, glucagon, somatostatin, and pancreatic polypeptides, thus affecting the regulation of blood glucose by the pancreas . EndocriThe postoperative survival time of patients with pancreatic malignant tumors is limited, and for patients with malignant tumors, the first consideration is tumor section followed by preservation of pancreas function. For patients with curable and long-lived benign pancreatic diseases, it is necessary to explore the effect of pancreatic parenchyma loss on postoperative blood glucose. Postoperative hyperglycemia may lead to long-term complications and a decline in the quality of life in these patients. In this study, our aim was to measure pancreatic volume by CT imaging and to explore the relationship between pancreatic parenchyma loss and postoperative blood glucose to provide some reference for the maintenance of pancreatic function after partial pancreatectomy.In this study, retrospective data from patients who underwent partial pancreatectomy in our hospital from October 2016 to October 2020 were collected. The inclusion criteria were as follows: (1) resection of the pancreatic parenchyma; (2) plain and contrast-enhanced CT images before and two week after the operation; (3) available pathological results provided after the operation; (4) no use of hypoglycemic drugs or insulin; and (5) no use of hormones, antipsychotics, or antitumor drugs. The exclusion criteria were as follows: (1) poor image quality that could not be used for analysis; (2) pathological results indicative of malignant tumors; (3) functional neuroendocrine tumors; and (4) diagnosed diabetes mellitus or impaired fasting blood glucose before surgery , 22 with nonfunctional neuroendocrine tumors of the pancreas, 3 with schwannomas, and 53 with chronic pancreatitis .This study was approved by the ethics committee of our institution. CT examinations were performed for preoperative diagnosis and postoperative evaluation of recovery. Blood glucose measurement is a parameter included in clinical biochemistry blood tests. This study only collected these results, did not interfere with the patient’s treatment plan, and did not divulge the patients’ personal information.The blood glucose levels of the patients during the hospitalization period were statistically analyzed. The average FBG level 7 days before the operation was taken as the preoperative FBG value (results of 2 to 5 tests over 7 days), and the average FBG value 14 days after the operation was defined as the postoperative FBG value .According to the postoperative FBG, the patients were divided into three groups. FBG ≥ 126 mg/dL (7.0 mmol/L) was classified as the hyperglycemic group (HG), FBG 110 mg/dL–126 mg/dL (6.1 mmol/L–7.0 mmol/L) was classified as the impaired fasting blood glucose group (IFG), and FBG < 110 mg/dL (6.1 mmol/L) was classified as the normal glycemia group (NG).CT was performed with a Siemens SOMATOM Definition AS+ 128 CT scanner. The voltage of the tube was 120 kV, the tube current adopted intelligent current regulation technology, the pitch was 1.0, the width of the collimator was 0.6 mm×128, the layer thickness was 2.0 mm, the layer spacing was 2.0 mm, and the visual field was 390×390 mm. The enhanced scan was performed with a nonionic iodine contrast agent (350 mg I/ml), which was injected into the median cubital vein with a high-pressure syringe at a flow rate of 2.5 ml/s and a total volume of 1.0 ml/kg. The arterial phase, portal phase, and delayed phase were scanned 25–30 s, 55–65 s, and 150–180 s after injection, respectively.Measurement of the pancreatic volume was performed on a Siemens syngo.via postprocessing workstation. Portal venous phase images from the enhanced CT scans were selected for measurement. At this time, the enhancement of the pancreas was obvious, the boundary was clear, and the contrast between normal pancreatic tissue and the tumor, surrounding fat, and peripheral blood vessels was clear, which could effectively avoid interference.3) was automatically calculated according to the delineated area and layer thickness. The volume of the pancreas was measured by two radiologists with 3-5 years of working experience who were blinded to the patients’ clinical information, and the average value of the measured results was taken as the final result. The uniformity between the two radiologists was tested using the intraclass correlation coefficient (ICC).The outline of the pancreas of the patient was drawn layer by layer (layer thickness = 2 mm) to avoid peripheral blood vessels, surrounding organs, tumors (including the cystic part and the solid part), stones (larger than 5 mm), calcification (larger than 5 mm), inflammatory exudation, postoperative necrosis, etc., and only the enhanced pancreatic parenchyma was outlined  = preoperative pancreatic volume (cm3) - postoperative pancreatic volume (cm3) and PRV ratio = (1-postoperative pancreatic volume/preoperative pancreatic volume) × 100%. According to the PRV, 171 patients were divided into 5 groups based on resection volume: < 30%, 30%–39%, 40%–49%, 50%–59%, and ≥ 60%.The following equations were used to calculate the relevant parameters: PRV  curves were used to analyze the best cutoff value, sensitivity, and specificity of the PRV among the different postoperative blood glucose groups. The chi-square test was performed on a variety of clinical factors in the HG, IFG, and NG. Among the 171 patients, 76 were male and 95 were female, with an average age of 49.1 ± 13.3 years. A total of 71 patients underwent DP, 61 patients underwent PD, 25 patients underwent DPPHR, 11 patients underwent EN, and 3 patients underwent CP.P = 0.162). However, there was a significant difference in postoperative FBG between the benign pancreatic tumor group and the chronic pancreatitis group (P = 0.010). The postoperative FBG in the chronic pancreatitis group was higher than that in the benign pancreatic tumor group. There was a significant difference in FBG before and after the operation (P < 0.001) and the blood glucose level after surgery was higher than that before surgery  , IFG (n = 52) and NG (n = 35). As shown in Table According to postoperative FBG, 171 patients were divided into three groups: HG . The IFG and NG were combined to form the nonhyperglycemia group (non-HG). ROC curve analysis showed that the best cutoff value of the PRV between the HG and non-HG was 39.95% with an area under the curve (AUC) of 0.898 (P < 0.001); the sensitivity was 89.29%, and the specificity was 82.76% . ROC curve analysis showed that the best cutoff value of the PRV between the HG and non-HG was 39.99% with an AUC of 0.909 (P < 0.001); the sensitivity was 86.79%, and the specificity was 90.77% . When comparing the benign tumor and chronic pancreatitis groups, we found that there was a statistically significant difference in postoperative FBG with the chronic pancreatitis group presenting a higher postoperative FBG. One possible reason is that benign tumors of pancreas may have no adverse effect on the background pancreatic parenchyma, and the compensatory ability of the residual pancreatic parenchyma is strong after partial pancreatectomy, while chronic pancreatitis, as an irreversible chronic inflammatory disease of the pancreas, may also affect the function of the residual pancreas, thus affecting the regulation of blood glucose after surgery [From Table  surgery , 14.Due to the high variability in the locations of pancreatic tumors, the selected procedure and scope of resection also differ. The chosen operation will reduce the pancreas parenchyma while removing the lesion. Pancreatic glands are nonrenewable and pancreatic parenchyma loss directly leads to the loss of many kinds of endocrine cells and impacts the secretion of hormones, thus affecting pancreatic-mediated regulation of blood glucose . SeveralP < 0.001), which was consistent with the cutoff value of new-onset postoperative diabetes in the abovementioned study. At the same time, we also found that there were significant differences in postoperative FBG levels in the different PRV groups , and the correlation analysis between the PRV and postoperative FBG indicated that there was a positive linear correlation.In the study, we found that patients with a PRV ≥ 40% were more likely to develop early postoperative hyperglycemia , 21% after DP (95% CI: 16%–25%), and 6% after CP (95% CI: 3%–9%) . CompareP = 0.037) [In the pancreas of healthy adults, islets are mainly distributed in the body and tail . In fact= 0.037) . In our This study is a single-center retrospective study in which the long-term blood glucose index values of the patients were not available, so it was unable to analyze longitudinal changes in glucose metabolism after the operation, which limits our interpretation of the results. At the same time, because the number of patients with chronic pancreatitis undergoing surgery is limited, they were not divided into separate groups in the analysis of postoperative blood glucose. Therefore, extending the postoperative follow-up time and further expanding the number of cases will be goals for our next study.In summary, there was a positive linear correlation between the postoperative early blood glucose level and the PRV in patients with benign pancreatic lesions. Furthermore, patients with a PRV ≥ 40% were more likely to develop early postoperative hyperglycemia.


The walkability of a neighborhood impacts public health and leads to economic and environmental benefits. The condition of sidewalks is a significant indicator of a walkable neighborhood as it supports and encourages pedestrian travel and physical activity. However, common sidewalk assessment practices are subjective, inefficient, and ineffective. Current alternate methods for objective and automated assessment of sidewalk surfaces do not consider pedestrians’ physiological responses. We developed a novel classification framework for the detection of irregular walking surfaces that uses a machine learning approach to analyze gait parameters extracted from a single wearable accelerometer. We also identified the most suitable location for sensor placement. Experiments were conducted on 12 subjects walking on good and irregular walking surfaces with sensors attached at three different locations: right ankle, lower back, and back of the head. The most suitable location for sensor placement was at the ankle. Among the five classifiers trained with gait features from the ankle sensor, Support Vector Machine (SVM) was found to be the most effective model since it was the most robust to subject differences. The model’s performance was improved with post-processing. This demonstrates that the SVM model trained with accelerometer-based gait features can be used as an objective tool for the assessment of sidewalk walking surface conditions. Walking is one of the most popular and cheapest forms of physical activity. A high level of walking in a community leads to various public health, environmental, and economic benefits ,2,3,4. TTo take pedestrians’ perceptions into account, one of the common sidewalk assessment practices is through pedestrian interviews or surveys . HoweverWith the advancement of wearable sensors, it is possible to measure and analyze human physiological responses to surrounding environments. The portability and affordability of these sensors makes it possible to develop a real-time sidewalk condition monitoring system that incorporates the personal characteristics of pedestrians. A few studies have been conducted on using machine learning techniques for sidewalk assessment utilizing smartphone acceleration data collected from subjects. To our knowledge, no studies have been conducted on utilizing machine learning techniques that incorporate gait analysis to assess sidewalk walking surface conditions with a single accelerometer. Furthermore, no study has determined the most suitable placement of a single wearable sensor to assess walking surface conditions.In this study, we propose a novel classification framework for the walkability domain that uses machine learning to analyze gait features extracted from a single wearable accelerometer for the detection of irregular walking surfaces. We also identify the most suitable location on the human body to place a single accelerometer for irregular walking surface detection. We determine the most effective machine learning model along with an optimal subset of gait features that best discriminates between good and irregular walking surfaces, which can be implemented as a real-world application for identification of problematic walking areas in a continuous manner. Furthermore, the optimal subset of gait features helps to understand gait parameters most affected by irregular walking surfaces.The remainder of the paper is structured as follows: First, we present a review of related works. Next, the experimental design and the research methodology utilized in this work are discussed. The results are then provided followed by a discussion on the findings and implication of this study.A pedestrian survey is one of the common approaches used to detect sidewalk defects . This meMany advanced methods have been proposed to automatically assess roadways based on urban data such as images, videos, or GIS technologies ,14,15,16Only a few methods have been proposed to assess sidewalk or roadway surfaces in an automated fashion that incorporates human bodily responses using machine learning techniques. Miyata et al.  estimateSeveral studies have discovered that it is feasible to utilize pedestrians’ physiological responses measured with wearable sensors placed at various locations to detect different sidewalk characteristics or defects ,27,28. TSeveral studies have placed sensors at different locations to examine the effects of the external environment and irregular surfaces on subjects’ gait parameters. In examining the correlation between pedestrians’ gait patterns and the built environment, Kim et al. utilized acceleration data from the right ankle to compute gait parameters . AnotherEmploying sensors at multiple locations for real-time continuous monitoring is not practical. Furthermore, adding data from multiple locations in the analysis causes the process to be computationally intensive . In addiThe workflow of incorporating gait analysis with machine learning techniques is illustrated in Twelve healthy subjects—eight males and four females—were recruited to participate in the study. The subjects wore three accelerometers at different locations on the body. As shown in The linear accelerations of the body were measured using Mbient sensors . These tri-axial accelerometers were configured to sample data at 100 Hz. The experiment was set up to mimic a real-world sidewalk setting. A stretch of well-paved, smooth, and levelled walking paths at The Peter Kiewit Institute of the University of Nebraska at Omaha, denoted with starting and ending points, was selected for the experiment. Within that stretch, four irregular walking surface segments were created: a grass-covered surface segment, a surface segment with obstructions, an uneven surface segment, and a debris-covered surface segment. These walking segments are typical walking surfaces that are likely to be encountered in the real-world. X, Y, and Z axes of the ankle accelerometer represent signals in Vertical (V), Anteroposterior (AP), and Mediolateral (ML) directions, respectively, as illustrated in X, Y, and Z axes represent V, ML, and AP directions, respectively.The For data pre-processing, the timestamp data from the three accelerometers were first synchronized using the synchronize function in MATLAB R2022a . Then, the raw acceleration data were labelled by referring to the video recordings. Since the aim was to analyze gait patterns to detect irregular walking surfaces, all irregular walking surface scenarios were grouped into one Irregular class. Before extracting gait features, stride segmentation was first performed on the raw data using the AP directional acceleration of the right ankle accelerometer for accurate stride recognition . The strWe extracted features that have demonstrated to be useful in mobility studies ,37. FirsWe first determined the most suitable sensor location for irregular walking surface detection. To ensure that the most suitable sensor location was subject agnostic, we used a protocol that iterates through all 12 subjects to leave one subject out as the test set and the remaining subjects as the training set. For each iteration, the three sensor locations were evaluated using a stratified five-fold cross-validation (CV) method repeated five times to compare the classification performance of each of the classification models mentioned in Since incorporating additional features is computationally costly for sensor-based systems and affects model interpretability, there is a need to systematically identify the optimal subset of the original extracted feature set of the most suitable location. We compared two popular feature selection techniques in this study: Elastic Net (ENET) and Maximum Relevance and Minimum Redundancy (MRMR). Prior to selecting features, the extracted features were normalized to zero mean and scaled to unit variance.i-th stride, respectively. Multicollinearity occurs when there is a strong correlation between features that could lead to excessively complex models and overfitting. ENET  is a popThe optimal α and λ parameters were selected using a stratified five-fold CV with a grid search. This was repeated 12 times using the leave-one-subject-out as the test set protocol. Gait studies on mobility have demonstrated that good prediction metrics can be achieved with only eight to 10 features while balancing model complexity and computational cost ,37. HencTo identify the optimal number of ENET top features to include in the final ENET feature subset, based on the feature profile, we added the features one-by-one starting with the most important feature, and ran our models using a repeated stratified five-fold CV to obtain the performance metric. The classification performance across all models would improve until they plateau as more important features were added. We determined the optimal number of features threshold based on the model that yielded the best metrics across all iterations of feature adding, since we are evaluating ENET and MRMR based on the best metric that each method can achieve. The threshold would be the point where the rate of improvement of the metric decreases. We identified that threshold objectively using an algorithm called Kneedle . This isMRMR ,41 is a k features we would like to select. The MRMR framework iterates k times until the top k features are selected. At each iteration, each feature would be scored based on this formula:Y is the class label, S is the set of selected features, |S| denotes the number of features, S is one of the features in the feature set, and Y is measured with an F-statistic as denoted by F, Random Forest (RF), Logistic Regression (LR), Ada Boost (ADA), and Extreme Gradient Boosting (XGB). SVM, RF, LR, and ADA are classification algorithms commonly used for gait analysis. XGB  was seleTo select the most effective model, we trained the top three classifiers observed during feature selection using the best feature subset. We used the leave-one-subject-out as the test set protocol to evaluate the subject-wise generalizability of our final models. As each iteration would yield a different training set, we tuned the hyperparameters for classifiers at each iteration using a randomized search with a stratified five-fold CV. The optimized models were then evaluated using the test set. The classifiers were compared using the test metrics averaged across all subjects.Since the class imbalance problem may bias certain performance metrics such as accuracy except for the area under the ROC curve , the AreBased on the label distribution in We used an over-sampling technique called Synthetic Minority Oversampling TEchnique (SMOTE) . SMOTE cTo determine whether the impact of the location on the classification performance is statistically significant for each classifier, a one-way ANOVA test was performed. Based on the results of Tukey’s pairwise test in Since the right ankle accelerometer is the most suitable location for discriminating between good and irregular walking surfaces, we performed feature selection on the right ankle feature set for optimal feature subset selection.From the leave-one-subject-out as the test set protocol, the optimal λ ranged from 0.001 to 0.01 while α ranged from 0.0 to 0.9. It resulted in 17 features, since the top 10 features selected in each iteration differ. Some features were selected as frequently as other features, which means they have the same importance and usefulness in discriminating between good and irregular walking surfaces. Therefore, to determine the optimal number of top ENET features to include in the final ENET feature subset, we added the features batch-by-batch instead of one-by-one, starting from the most important feature, and ran them through all five models. As observed in We then used the Kneedle algorithm to objectively identify the threshold that balances the trade-off between model performance and training computational cost. Since different curves produced by different classifiers would yield different thresholds, we used the Kneedle algorithm to identify the optimal number of ENET top features based on the model that yields the best metric across all iterations, which is RF. Based on The frequency profile of the top 10 selected features by MRMR compiled from the leave-one-subject-out as the test set protocol is shown in There are 17 features in total. To determine the optimal number of top MRMR features to include in the final MRMR feature subset, we added one feature batch at a time moving down the importance rank and evaluated them with our models. The results are illustrated in Therefore, we ran the Kneedle algorithm on the performance results of both models. As we can see from The best classification performance achieved by the full feature set and feature subsets selected by ENET and MRMR is shown in Looking at We trained our top three classifiers identified during feature selection with the optimal feature subset. The test results for all three classifiers for each subject iteration including the average test results are shown in k consecutive strides were sampled into one segment to produce the final prediction for that segment, sliding to the next segment by the step size of one stride. The results are shown in k, the classification performance improved across all three classifiers, which confirmed our assumption. With post-processing, the average AUC of the most effective model, SVM, improved from 80% to 85%.We observed that when subjects were walking on irregular walking surfaces, interrupted gait occurred intermittently among normal gaits. Not every stride was interrupted. Up until this point, we detected irregular walking surfaces on a per stride basis by predicting if each stride occurred on an irregular surface or not. Therefore, we assumed that if we combined several consecutive strides’ walking surface predictions by a classifier and took the average of the predicted probability of occurring on an irregular walking surface of the combined gaits to produce a final prediction of the walking surface covered by the combined gaits, it would improve the classification metric. We use a sliding window approach to segment the per stride prediction obtained from classifiers for each subject. In this study, we identified the most suitable placement of a single accelerometer for the purpose of discriminating between good and irregular walking surfaces, which is at the ankle. Then, we selected the optimal subset of gait features extracted from the raw accelerations of the ankle sensor to train several machine learning classifiers for comparison. The most effective model could detect irregular walking surfaces with satisfactory classification performance. Our results demonstrate the feasibility of utilizing wearable accelerometers and a machine-learning approach to differentiate good and irregular walking surfaces.Our results show that the accelerometer placed at the right ankle had better capability of estimating walking surface conditions compared to accelerometers placed at the hip and the head. It improved the classification performance of various models. This could be because changes in the magnitude of accelerations were smaller at the head and the hip compared to the ankle when subjects were walking on irregular walking surfaces. Therefore, changes in underlying stride parameters could be better captured when the sensor was placed at the ankle. Furthermore, as the ankle sensor was closer to the ground, a subtle gait adaptation for each stride when walking on irregular walking surfaces can be captured. Therefore, we recommend that a wearable acceleration sensor be placed at the ankle when implementing the proposed method in a real-time walking surface condition assessment application.This study also determined an optimized feature set that balances computational cost for a real-time sensor-based system, model interpretability, and classification performance. The optimized feature set consisted of eight features: VM, VVMD, VMD, VM30, AVM, LVMD, VHSD, and VVM. The feature VM was found to be the strongest predictor. AVM and VVM, which characterize the whole stride acceleration of the ankle sensor in different directions, were also selected. They may have been selected because subjects would adapt their whole gait to maintain their stability while walking on irregular walking surfaces. Three out of eight features selected characterize the double-stance phase: VVMD, LVMD, and VMD. Since the double-stance phase occurs when the body weight transitions from one limb to another , stabiliSVM was found to be the most generalizable subject-wise despite the limited number of subjects. The results have demonstrated that SVM was more robust to individual differences compared to RF and XGB. Its classification performance was also further improved with post-processing by combining the predicted probability of several strides to produce final predictions. This means that when the proposed method is implemented as an application, at least five seconds of data need to be measured since the average stride time is around 1.10 s based on our data.Since current sidewalk condition assessment usually relies on trained experts from governmental agencies or voluntary participation of residents or pedestrians, the intervals between assessments are long due to staffing and budget limitations . On the One of the limitations of this study is that the experiment was not conducted in a real-world walkable and less walkable neighborhood. Subjects could exhibit different walking patterns in an experimental setting. The other limitation is that the sample size in terms of the number of subjects is small. To address that, we drew conclusions repeatedly by iteratively leaving one subject out as the test set to evaluate our methods. Despite these limitations, this study is the first step towards an objective and automated assessment of sidewalk walking surface conditions of a neighborhood.For future work, we will develop a deep learning model for the same purpose with a single accelerometer placed on the ankle. We are considering using a Long Short-Term Memory network, which is widely used in the domain of human activity recognition. Future experiments will be conducted in a real-world walkable and less walkable neighborhood with more subjects. The best machine learning classifier and the optimal feature set can be used to develop an irregular walking surface detection model utilizing real-world data. Additionally, GPS data can also be incorporated to locate and identify the cause of problematic walking surface areas.In this study, we proposed a novel method for irregular walking surface detection using machine learning techniques and accelerometer-based gait features extracted from a single sensor. We also identified the most suitable location for sensor placement among the three locations commonly used to measure the effect of external environment on subjects’ gait parameters, the optimal feature set, and the most effective classifier for irregular walking surface detection. Our results indicate that the most suitable location for sensor placement is a subject’s ankle. We also find that SVM is the most effective model because it is the most generalizable and can achieve satisfactory classification performance with limited data. Furthermore, we also demonstrate that classification performance can be improved by taking several consecutive strides into account to make predictions. In conclusion, our results support the potential application of the proposed method as an objective tool for assessing the sidewalk walking surface condition of a neighborhood.