The evaluation of the functional state of the neuromuscular system (NMS) in elite female judokas according to the muscular activity indices is influenced by the force (F) and force-velocity (F-V) efforts. The implementation of the individual correction plan in the elite female judokas’ process of instruction and training must be based on the accurate determination of the force and force-velocity effort areas throughout the training and competitive periods.max—time to reach the maximum muscle contraction, (msec); Fy –examination of elasticity indices in different muscles, (Hz); J–explosive muscular strength, (kg/s). Measurements were made for six muscle groups and 9 indices of fitness tests: 5 force tests (F) and 4 force-velocity tests (F-V). The research was carried out during 24 cycles, each one lasting two weeks: 12 training cycles and 12 competitive ones. Each cycle lasted two weeks. During the research, the model plan of training for F and F-V was used, determining the optimal areas of F and F-V training efforts in the preparation and competitive periods. In the experimental groups (A and C), according to the data of judokas’ NMS functional state evaluation, the individual correction of the F and F-V efforts was performed every two weeks. As for the control groups , traditional methods of training were used.The research involved 44 elite female judokas, divided in to two experimental groups  and two control groups . To diagnose the NMS, 21 elite female judokas were evaluated, belonging to different classification categories, divided into three groups: group I–category I (Cat. I), group II–candidates for Masters of Sports (CMS) and group III—Masters of Sports (MS).The evaluation of NMS was performed at the end of each two-week cycle, using 3 tests: Tmax, Fy and J indices was determined. The value of the Fy index at F effort is 32% in group I, 30% - in group II, 27% - in group III, 28–30% at the effort of F-V. The total number of corrections in group A: 79 negative corrections and 59 positive corrections, while in group C: 65 negative corrections and 89 positive ones. Within the F-V effort, the number of effort corrections in group A was: 68 negative corrections and 92 positive; in group C - 81 positive and 78 negative corrections. The female judokas’ results in the final stage of EG–A were significantly improved in F indices by 52.15%, F-V by 6.22% and 6.18%. In the EG–C, the F increased considerably by 7.52%, F-V by 5.67% and 7.20%. These results characterize the level of physical training.The NMS evaluation of the female judokas was made every two weeks and the level of correlation of TThe functional state of the NMS in elite judokas, determined according to the temporal indices of reaching the maximal muscular contraction, the muscle explosive strength and the muscles elasticity, is subjected to dynamics under the influence of force effort and force-velocity effort. Sports training is a long-term adaptation to sports activities. For creating the most comfortable and efficient process of training, it is generally necessary to take into account the dynamics of athletes’ functional capacities in different periods of preparation. The current approaches to training process planning are very valuable in this regard. Concurrently, the mechanisms of adaptation, which are the basis for obtaining and developing the optimal effect of training remain insufficiently studied in many branches of sports .e.g., In performance judo, the use of biomechanical measurements, fitness tests and special fitness tests (specific to judo), the investigation of the blood lactate concentration, the evaluation of heart rate and the perceived effort in a competition can provide an optimal control of training . The evae.g., One of the main problems of sports training is the differentiation of physical activity depending on the adaptive skills of the body. Opportunities to improve and streamline sports preparation are provided by introducing science based management methods into the training process, and using the information technologies for the evaluation of the functional state of athletes’ neuromuscular system (NMS) . The chaNeuromuscular fatigue is the result of neuromuscular activity. Quantitative assessments of the peripheral neuromuscular fatigue are made using electromyograms . In ordeIn general, the multi-annual training system for judokas should not notably differ from the same training system for the representatives of other combat sports. Achieving the best performance requires high levels of muscle power, accompanied by a moderate use of the aerobic metabolic pathway .Over the last few decades, women’s sports have progressed quite intensely. This is determined both by the social status of women and by their continuous tendency to assert themselves and be equal to men. The presence in the professional sports of women in the pre-involution period reveals and updates, for the physiology of age and the sports practice, the functional capacity of female body’s cardiovascular system to adapt to an intense physical activity at such a mature age. It is necessary to take into consideration the osteogenic effects of judo in the female practitioners during the premenopausal and postmenopausal period .e.g., e.g., e.g., e.g., The corrections must be applied in the instruction and training process of elite female judokas following an accurate determination of the effort areas related to force and force-velocity e.g., . It is ae.g., Women’s training should be planned differently than men’s training, even in the same sport, given the characteristics of the female body. The theory and practice of judo are evolving quite intensely, but most scientific investigations essentially reflect the particularities of sports training only in the male judokas e.g., . At the From our point of view, the specialized scientific literature provides an insufficient number of works dealing with the preparation of the force and force-velocity effort in the elite female judokas. Unfortunately, to date, the degree of judo influence on the female body, the functional state level of the neuromuscular system (NMS) in the female judokas and the determination of the optimal effort areas in training and competitive periods have not been established with sufficient precision.Purpose of the research. Determining the optimal areas of effort in terms of force and force-velocity according to the changes in the functional state of the neuromuscular system in the process of elite female judokas’ instruction and training.Research hypotheses. The correlative analysis of the basic indices concerning the NMS functional state in the elite female judokas will establish the weight between the evaluated indices of the main muscle groups in each classification category investigated.We also consider that the implementation of the individual correction plan in the instruction and training process will have to be based on the exact determination of the areas of force efforts and force-velocity efforts in the training and competitive periods.n = 11 and CG (B), n = 11 with athletes of category I (Cat. I) and candidates for Masters of Sport (CMS) while the EG (C), n = 11 and CG (D), n = 11 included athletes in the category of Masters of Sport (MS). For the diagnosis of the neuromuscular system (NMS) functional state, 21 elite female judokas were selected, divided into three groups as follows: group I, n = 7 – judokas (Cat. I), group II, n = 7 – (CMS), group III-a, n = 7 – (MS), aged between 20–25 years. According to the Unique Sports Classification of the Republic of Moldova for the years 2018–2021, in order to be included in Cat. I, the judoka must take up to the 6th–7th place in the Championships of the Republic of Moldova (CRM); for the CMS position—she must win the 1st up to 5th place in CRM standings; for MS category, the 6th to 9th place in the standings of the European Seniors Championships.The research involved 44 elite female judokas, belonging to different weight categories , with an average and standard deviation of the age of 22.64 ± 1.53 years. The judokas were divided into four groups: two experimental groups (EG) and two control groups (CG). Depending on the level of sports classification, the judokas were distributed as follows: EG (A), The experimental study was approved by the Ethics Commission of the State University of Physical Education and Sports of the Republic of Moldova, in accordance with the Ethical Standards of the Declaration of Helsinki (ec_usefs4-11-2021). The participants gave their written consent for the study in conformity with the recommendations of the Biomedical Research Ethics Committees .The research was carried out in a laboratory provided with certified and accredited equipment.max–the time to reach the maximum muscle contraction, evaluated by the method of selective electromyography (msec); Fy–examination of the elasticity indices of different muscles, which was measured through the method of seismo myotonometry (Hz); J - explosive muscular strength, which was evaluated with the tensometric platform and the modular system of tensometric equipment (kg/s).The functional state of NMS in the female judokas was checked by means of three tests: TThe instrumental methods used to obtain specific information on the functional state of the female judokas’ neuromuscular system (NMS) included the following research methods :gastrocnemius; rectus femoris; biceps femoris; biceps brachii and triceps brachii. The test was made immediately after the warm-up. Prior to starting each study, the maximum possible level of the bioelectric activism of female athletes’ muscles was assessed. To this end, the maximal level of muscles activism was maintained (3 s) under the conditions of their isometric contractions and the retroactive visual control on the oscilloscope screen . In order to determine the necessary time for reaching the maximum contraction, the athletes were requested to contract the studied muscle intensely and quickly ((a) Method of selective electromyography (EMG): it was applied to determine the time to reach maximum muscle contraction. EMG was performed using flat electrodes attached to the following muscles:  quickly .(b) Method of seismomyotonography: it was used to assess the functional state of athletes’ peripheral NMS according to the elasticity index of the following muscles: gastrocnemius, rectus femoris, biceps femoris, latissimus dorsi, biceps brachii and triceps brachii. The frequency of the muscle mechanical vibrations after the adjusted striking of the muscle was used as an index of elasticity. The frequency of vibrations was measured by means of the SKG seismic transmitter (Seismocardiograph 2000). The transmitter was attached to the analyzed muscle. The signal from the transmitter was sent to the computer, where the information was subsequently processed using a special program. The testing was carried out before the training sessions throughout the entire period of research .tibialis anterior, extensor digitorum longus; extensor hallucis longus) and feet flexor muscles  was established by means of the tensometric platform. The athlete, standing on the platform, jumped vertically as high and fast as possible from semi-squat position. The transmitters needed to enter the information into the computer system were located on the lower part of the tensometric platform. The explosive power of the biceps brachii, triceps brachii and back muscles was determined with the help of the tensodynamic system, which was connected to the tensometric platform. During the test, the athlete—with straightened legs, back slightly bent, both hands upwards (brief explosive strength of the back muscles)—had to rapidly perform a cable push-pull (triceps brachii or biceps brachii). The signal sent by the tensometric transmitters was directed to the computer system, for further processing  Method of tensometry. The explosive power of the leg’s extensor muscles  Pedagogical-sports testing. Tested indices: force (F) and force-velocity (F-V) e.g., .gastrocnemius) was found out by standing on tiptoes, with legs, torso and arms straightened (F3). To determine the force of the biceps brachii, the athlete did pulldowns with the arms bent at 110 degrees and straight legs and torso (F4). The force of the triceps brachii is determined while the arms are bent with elbow joints at 110 degrees; the tensometric force transducers were placed at shoulders height of the studied subjects (F5). The explosive strength is determined when the test is performed on the tensometric platform, with 160 degrees bent legs at the knee joints (F-V1).(d.1) The tensometric device was used in the research for assessing the preparation level of the muscle force. This device determined the force of the back lumbar muscles (F1): the athlete-subject of the research stretched her legs and arms, with her torso inclined at an angle of 130 degrees when starting the pulls. For measuring the force of the thigh extensor muscles (F2), the athlete bent her legs at an angle of 160 degrees at the beginning of the pulls, while her arms and torso were straight. The force of the feet extensor muscles (Morote Seoi-nage (two handed back-carry throws) (F-V2). In order to standardize the task of the test, all participants performed the same type of throw (two-handed back-carry throws). The testing procedure was established in accordance with the recommendations of the specialists Yu.P. Zamjatin, B.I. Tarakanov, 1985, who used this test in wrestling. The testing procedure is described below  Five ed below . The judnt e.g., .Tai Otoshi (body drops) (F-V3). The structure of the technique performed in this test differs essentially from the one described in the previous test. At the same time, the procedure for testing and determining its results is exactly the same as the one presented above.(d.3) Five (d.4) Rope climbing (F-V4). The tested judoka stood on the tatami and grabbed the rope with both hands. At the whistle signal and the simultaneous start of the stopwatch, the athlete began to climb the rope without the help of her legs. A marking was made on the rope, 4 m above the tatami; the judoka was supposed to touch by hand this sign as fast as possible. When the marking was touched, the stopwatch was stopped and the result of the test was estimated with 0.1 s margin of error.The research was conducted over a period of 24 two-week cycles (12 training cycles and 12 competitive ones), in two stages (E):E1 (training): the basic parameters of the NMS functional state in all muscle groups were evaluated depending on the size of the force effort and force-velocity effort in the judokas from groups I, II and III. The judokas belonging to the experimental and control groups  were submitted to the initial pedagogical-sports testing of the force (F) and force-velocity (F-V) indices.- E2 (competitive): the basic parameters of the functional state of NMS in all muscle groups were evaluated according to the size of force effort and force-velocity effort in the judokas belonging to groups I, II and III. The judokas from the experimental and control groups  had the final pedagogical-sports testing of the force (F) and force-velocity (F-V) indices.- The model training plan for F and F-V was applied throughout the research. The following exercises were used for the efforts related to force: (1) standard pushups “all the way up and all the way down”; (2) behind the neck press  on the “Hercules” exercise machine; (3) barbell behind neck squats, maximal weight. These exercises composed a single set. The following exercises were performed for the force-velocity efforts: (1) standard pushups in 10 s; (2) behind the neck press (using 50% of the own body weight) in 10 s; (3) barbell behind neck jumps from semi-squat position, in 10 s. These exercises too formed a single set. The analysis of the judokas’ NMS was made every two weeks of training. The minimum number of sets in the exercises related to force was 10, and the maximum number was 35, performed throughout two weeks. The minimum number of sets in the exercises related to force–velocity, along two weeks, was 15, while the maximum number was 45. The force effort was reduced by 10–50% (group A) and by 10–45% (group C); the force-velocity effort was reduced by 10–45% within the correction and increased by 10–50%.Based on these model-characteristics and the training plan, the optimal areas of force and force-velocity training efforts were established in the training and competitive periods during the training annual cycle. In the experimental groups (A and C), in accordance with the data of judokas’ NMS functional state evaluation, every two weeks, the individual correction of the effort and effort-velocity efforts was performed .max, Fy and J). Instead, the control groups of female judokas  worked with traditional training methods.The plus sign (+) shows that the positive correction of the force effort and force-velocity effort was performed for each athlete and predetermines the increase of the training effort. The negative sign (-) expresses the achievement of the negative correction of the force efforts and force-velocity effort for each judoka; it means the diminution of the effort. The number of positive and negative corrections for each athlete within a monthly cycle change from 0 to 3 , version 23. Descriptive statistics methods were used to calculate mean, standard deviation (SD) and Cohen’s max, Fy and J indices of the main muscle groups and to balance the efforts of force and force-velocity.The evaluation of the female judokas’ NMS functional state was performed every two weeks. It allowed to determine the level of correlation between Tmax index increases from 23% in group I to 41% in group III; inversely, the value of Fy index decreases from 40% to 32% in groups I and III, while the value of J index decreases from 32% to 27% in groups I and III. Therefore, one can notice significant differences in the percentage ratio of the basic parameters value at the same time with the increase of the female judokas’ classification level from category I to the Master of Sports title (MS).The correlative analysis enabled also to determine the comparative percentage ratio of the parameters of NMS functional state in the female judokas, depending on the force and force-velocity training efforts.max index goes up from 31% in group I to 39% in group III; the value of the Fy index decreases from 41% in group I to 31% in group III; the value of J index increases insignificantly from 28% in group I to 30% in group III.max index of the rectus femoris muscle (curves are denoted by figure “1”) and of the gastrocnemius muscle (curves are denoted by figure “2”). The figure illustrates the directly proportional exponential dependencies of Tmax indices and Hc. The range of each optimal area is determined by the dispersion value of the data obtained in the group and constitutes approximately 25 msec. Within the optimal area, the force effort made during a two-week training cycle is shown in relation to the Tmax index of the respective muscle. The area of negative correction of the force training effort  and the gastrocnemius muscle (2). The force-velocity effort during the two-week training cycles included 15 to 45 sets of exercises. The Tmax index of the rectus femoris muscle evolved from 100 msec to 230 msec, respectively, starting with group III and ending with group I; the Tmax index of the gastrocnemius muscle changed from 60 msec to 170 msec in those groups. The range of each optimal zone is about 25 msec. The positive correction area is distributed above the optimal areas and the negative correction area is located below the optimal areas.max index of the biceps femoris, biceps and triceps brachii muscles . The data presented in the figure show the directly proportional exponential dependencies of the Hc parameters on the Tmax index. The Tmax index of the biceps femoris increased from 105 to 240 msec, which corresponds to the force effort in 10 to 35 sets of exercises. The Tmax indices of the biceps and triceps brachii were almost identical, that is why their optimal areas coincide in Figure. The Tmax index value of the biceps and triceps ranged from 40 msec to 150 msec, which also corresponds to the minimal and maximal number of exercise sets. Figure presents the optimal areas of force-velocity training effort depending on the Tmax of the biceps, triceps and biceps femoris. The Tmax index of the biceps femoris oscillated from 110 up to 230 msec in the groups III–I. The Tmax indices of the biceps and triceps coincided, so they were presented as identical optimal areas. They ranged from 50 msec to 150 msec, which corresponds to the force-velocity effort in 15 to 45 sets of exercises.max index of the latissimus dorsi. As shown in Figure, the Tmax index of the latissimus dorsi changed in group I from 160 msec to 260 msec, in group II from 140 msec to 240 msec and in group III—from 120 msec to 200 msec. The range of each optimal area is about 30 msec. Figure highlights the optimal areas of force-velocity training effort related to Tmax index of the latissimus dorsi. The Tmax index changed from 160 msec to 260 msec in group I, from 140 msec to 240 msec in group II and from 120 msec to 220 msec in group III. The range of each optimal area was approximately 30 msec. The area of negative correction is situated above the optimal areas while the area of positive correction is located below the optimal areas.Fy index of the tested muscles . The data summarized in y indices. The range of each optimal area is determined by the value of data dispersion in the group and represents approximately 1.5 Hz. The Fy index ranged between 28 Hz and 35 Hz in group I, between 31 and 37 Hz in group II and between 32 and 39 Hz in group III. The area of negative correction is above the optimal areas and the area of positive correction is placed below the optimal areas. The force training effort progressed from the minimal value (10 sets of exercises) to the maximal one (35 sets of exercises). Figure shows the optimal areas of the force-velocity training effort depending on the Fy index of the tested muscles . The optimal areas are exponential curves, each curve having a range of approximately 1.5 Hz. The Fy index evolved from 28 to 35 Hz in group I, from 30 to 37 Hz in group II and from 32 to 39 Hz in group III. If the Fy indices values of the tested muscles exceed the 40 Hz threshold, then the risk of traumas in the respective muscles increases significantly, especially at the force-velocity efforts.J indices of the extensor digitorum longus and extensor hallucis longus. c and Hcc parameters on the J index. The optimal areas of the force effort are highlighted with a continuous line. The range of each optimal area is about 30 kg/s. The force effort evolved, during the two-week cycles, from 10 to 35 sets of exercises. At the same time, the explosive strength changed from 500 kg/s to 170 kg/s in group I, from 550 to 220 kg/s in group II and from 600 to 280 kg/s in group III. The optimal areas of the force-velocity effort are marked with a dotted line. The range of each optimal area represents about 55 kg/s. The force-velocity effort increased, within the two-week cycles, from 15 up to 55 sets of exercises. The explosive strength had the following changes: in group I from 510 kg/s to 175 kg/s; in group II—from 555 to 220 kg/s; in group III—from 605 to 280 kg/s. The range of optimal areas of the force effort and force-velocity effort were determined taking into account the parameters dispersion values in each group of sportswomen. The area of positive correction is located above the optimal areas, which shows the increase of the training effort when exceeding the optimal area value, multiplied at the corresponding value coefficient. Below the optimal areas is located the negative correction area, which represents the decrease of the training effort to the size of the deviation for reducing the functional parameter value related to the negative area of effort.J index of the triceps brachii and biceps brachii. The exponential dependencies of the Hc and Hcc parameters on the J index are presented in triceps brachii and biceps brachii almost coincided, so they are shown in J index of the latissimus dorsi muscle. The figure shows the exponential dependencies of the Hc and Hcc parameters on J index. The force effort areas are marked with a continuous line. The range of each area is about 30 kg/s. The explosive strength of the muscles within the two-week cycles changed as follows: from 200 to 65 kg/s in group I; from 230 to 90 kg/s in group II; from 256 to 110 kg/s in group III. A dotted line highlights the optimal areas of force-velocity effort training. The range of each zone represents approximately 30 kg/s. The explosive strength of the muscles oscillated from 205 to 70 kg/s in group I, from 235 to 95 kg/s in group II and from 260 to 110 kg/s in group III. The area of positive correction (which represents the increase of the training effort) is located above the optimal areas of the effort. The negative correction area, which means the decrease of the training effort within the two-week cycle, is situated below the optimal areas of effort.The results of the corrections had a positive impact, leading to the considerable increase of judokas’ sports mastery in both experimental groups in terms of improved force and force-velocity capacity  and 3.p < 0.01; p < 0.05) and the force-velocity indices by 6.22% (p < 0.05) and 6.18% , which characterizes the level of physical training. The lack of scientifically substantiated corrections in the training process of the control group athletes entails the insignificant increase of the indices recorded. Thus, the comparison of the results obtained by the female judokas in the control group B (categories I and CMS), at the beginning and the end of the experiment, showed an unobservable tendency to improve the tested indices, namely by 2.83% at force (F1-5) and by 2.73% (F-V1) and by 3.85% (F-V2-4). Regarding the differences between the averages in groups A and B, one can notice significant differences in final testing at the indices of F1-4  and at the indices F-V1 and F-V4 (p < 0.001). Although all the analyzed indices increased to some extent, the low efficiency of the traditional methods of judokas’ training was quite obvious from the initial stage of the experiment.The analysis of the data included in p < 0.01; p < 0.05 and F4, p < 0.05) and force-velocity by 5.67% (p < 0.05) and 7.20% , which indicates the level of physical training. The findings mentioned above refer also to the athletes of the control group—MS. In this group, the test results proved to be even lower: increase of force by 3.93% (p > 0.05) and force-velocity by 2.97% and 1.73% (p > 0.05), which clearly proves the stability of the indices of the physical training level in the elite sportswomen. As for the differences between the averages of the groups C and D, there are significant differences in the final testing at the indices of F1-3 (p < 0.001) and at F-V1 (p < 0.05). The insignificant increase of the physical training indices also leads to analogous tendencies regarding the criteria of the technical-tactical mastery, which also stabilized and almost did not change at the end of the research.A similar situation can be found out when analyzing the testing results of the judokas in the experimental group—MS . In thisThe scientific innovation brought by this paper is the determination of the elite female judokas’ physical and functional reserves for the first time. The interconnection between the dynamics of the athletes’ musculoskeletal system state and the adjustment of the force and force-velocity efforts was also highlighted. The range of optimal values related to effort correction was established according to the data on the functional state of the judokas’ neuromuscular system and the medical-pedagogical examination results. The system of implementing the corrections of force and force-velocity efforts in the female judokas’ training process was approved experimentally.max, Fy and J indices of the main muscle groups revealed the presence of significant correlations between these parameters and the value of force and force-velocity efforts. The data reveal important differences of the determined percentage ratio depending on the athletes’ mastery and the type of the training efforts. At the same time, there is a general trend of significant increase in the value of Tmax index when the sports mastery increases. A distinctive feature of the efforts influence on the NMS functional state lies in the diminution of the Fy index value during the force effort  and its insignificant increase (from 28% to 30%) during the force-velocity effort. Corrections are needed when an imbalance between two groups of muscles is found out, which could impede the execution of the technique and could increase the risk of injury. In such a case, workouts with the balance board are proposed  between the indices defining the NMS functional state and the adjustment of the force and force-velocity efforts were calculated by the derivation method. The correlative analysis of the tested parameters helped to determine the percentage ratio between the indices showing the NMS functional state of the judokas of category I (group I), CMS (group II) and MS (group III), depending on the total value of the force and force-velocity training effort. Therefore, the analysis of the judokas’ NMS functional state at Ted e.g., .max index on the parameters of force effort and force-velocity effort reveal a significantly high degree of indices correlation (R = 0.548–0.854 according to the training cycle and the tested muscle). When examining the results of the elasticity indices evaluation in different muscles (Fy) related to the force-velocity effort, it was found out that the correlation coefficient value of these indices rarely has a significant nature (R = 0.509–0.852). The insignificant changes of the Fy index are practically not dependent upon the cycles and periods of the sports training. Lower values of the correlation coefficients were attested when analyzing the dependency of the explosive strength indices (J) on the force effort and force-velocity effort. In the given case, the great majority of the correlation coefficients had significant variations . At the same time, some variations of the coefficients recorded during the test are insignificant. The isokinetic analysis of the knee pair of flexors and extensors in the elite judo female athletes can prevent lateral asymmetry, thus reducing the risk of injury , different states (levels of fatigue) were determined during their preparatory period, depending on the training task . Determimax, Fy and J in each training cycle, for each group of subjects separately . A minimum number of force effort corrections were done along the first two training cycles, fact entailed by athletes’ NMS adaptation processes. A maximum number of positive and negative corrections were done in the sixth training cycle (the highest volume of force effort—35 sets of basic exercises—is achieved within this cycle). At the end of each training cycle, the total number of corrections decreased twice compared to the maximal value. At the same time, the force effort consisted of 16 sets of exercises. The total number of negative corrections in the experimental groups was 79 and the positive ones—59 (group A); as for the group C, a number of 65 negative corrections of the force effort and 89 positive corrections were done. In some cases, the negative corrections of the training efforts in both experimental groups were replaced by recovery activities , and in other groups the force effort was diminished by 10–50% (group A) and by 10–45% (group C). When making positive corrections, the physical effort was intensified by 10–50%. The total volume of force efforts during this period, after making the negative and positive corrections, did not change significantly (p >0.05). Within the force-velocity effort, 68 negative corrections and 92 positive ones were made in group A, while in group C there were 81 positive corrections and 78 negative ones throughout the entire period. Sometimes, the training sessions were replaced by activities of recovery . Within the correction, the force-velocity effort was reduced by 10–45% and increased by 10–50%. The total volume of force-velocity efforts, after making the positive and negative corrections, did not change significantly (p > 0.05). There were examined the differences in force-velocity characteristics and the maximal power and rise height of the body’s centre of mass, measured in the counter-movement jump (CMJ) and the spike jump (SPJ), in the case of the judokas, boxers and taekwondo athletes , at the beginning and at the end of the experiment, revealed an unnoticeable tendency to improve the tested indices . High leThe considerable improvement in the physical training indices and in the capacities of force and force-velocity leads mainly to a higher standard of the competitive combats and to better results of the technical actions.This is an experimental type research, which is composed of two parts: the diagnosis of the NMS functional state in the elite female judokas of different classification categories at the beginning of the research; the experimental part carried out in two stages, with two experimental groups and two control ones. The individual results and their presentation per group averages of the studied indices is a limit of the research. Due to the small number of elite judokas aged 20–25 years at each classification category and weight category, the results obtained have scientific significance and relevance only at research level and cannot be generalized. However, they have a great practical applicability for judo and other combat sports as well, where the effort of force and force-velocity is a determining factor in achieving sports performance. Because there is no database with the values of the NMS indices in the elite female judokas, the research results were analyzed only by comparison between classification categories and control groups, without reference to the elite athletes’ values, especially the elite female judokas.The functional state of athletes’ neuromuscular system and their level of special training must be determined through the efficient implementation of advanced technologies and mobile computing resources. Thus, the data collection and processing, the objective and fast displaying of the results, the organization and direct development of the specialized evaluations in training conditions are speeded up.The implementation of the individual correction plan in the instruction and training plan for the elite female judokas must be based on the exact determination of the force efforts and force-velocity efforts throughout the training and competitive periods.The functional state of the female judokas’ neuromuscular system, determined on the basis of the temporal indices of the maximal muscular contraction, the explosive strength and the muscles elasticity is subjected to an effervescent dynamic under the influence of the force efforts and force-velocity efforts.10.7717/peerj.13468/supp-1Supplemental Information 1The percentage ratio of the value of the neuromuscular system indices of the female judokas with different levels of qualification, depending on the force and force-velocity effort. The number of corrections of the force effort and force-velocity effort applied in the training of the female judokas of the experimental group are presented. Also presented are Optimal areas of force effort and force-velocity effort based on the Tmax indices of the tested muscles, Optimal areas of force effort training (A) and force-velocity (B) depending on the Fy indices of the tested muscles and Optimal areas of force effort and force-velocity effort depending on the J indices of the extensor muscles of the leg and the extensor muscles of the foot plantar area.Click here for additional data file.


Botryosphaeria dothidea and anthracnose caused by Colletotrichum gloeosporioides are two important apple fruit diseases. It is critical to conduct timely and accurate distinction and diagnosis of the two diseases for apple disease management and apple quality control. The automatic distinction between the two diseases was investigated based on image processing technology in this study. The acquired disease images were preprocessed via image scaling, color image contrast stretching, and morphological opening and closing reconstruction. Then, two lesion segmentation methods based on circle fitting were proposed and used to conduct lesion segmentation. After comparison with the manual segmentation results obtained via the software Adobe Photoshop CC, Lesion segmentation method 1 was chosen for further disease image processing. The gray images on the nine components in the RGB, HSI, and L*a*b* color spaces of the segmented lesion images were filtered by using multi-scale block local binary pattern operators with the sizes of pixel blocks of 1 × 1, 2 × 2, and 3 × 3, respectively, and the corresponding local binary pattern (LBP) histogram vectors were calculated as the features of the lesion images. Subsequently, support vector machine (SVM) models and random forest models were built based on individual LBP histogram features or different LBP histogram feature combinations for distinguishing the diseases. The optimal SVM model with the distinction accuracies of the training and testing sets equal to 100 and 95.12% and the optimal random forest model with the distinction accuracies of the training and testing sets equal to 100 and 90.24% were achieved. The results indicated that the distinction between the two diseases could be implemented with high accuracy by using the proposed method. In this study, a method based on image processing technology was provided for the distinction of ring rot and anthracnose on apple fruits.Ring rot caused by  Botryosphaeria dothidea and apple anthracnose caused by Colletotrichum gloeosporioides is two common diseases on apple fruits  based on the images acquired under controlled conditions.There have been some reports on image-based distinction and recognition of apple diseases , but fewK-means clustering technique was applied to perform image segmentation, color and texture features including global color histogram, color coherence vector, color difference histogram, structure element histogram, local ternary pattern, completed local binary pattern (CLBP), and LBP was extracted, and then the color, texture, and fused features were applied to identify apple fruit images by using a multi-class support vector machine (MSVM), finally, an average identification accuracy of approximately 90% was obtained. In another study conducted by The quality of plant disease images acquired in natural scenes is usually affected by many factors such as uneven illumination, complex background, and blurred edges. It is necessary to explore an accurate and highly automated image segmentation method to segment these disease images. Furthermore, feature extraction after image segmentation is particularly important for image recognition. The local binary pattern (LBP) operator is a local texture descriptor . BecauseIn this study, after preprocessing the digital images of apple fruits infected with ring rot and anthracnose acquired in natural scenes, two lesion segmentation methods based on circle fitting were developed and applied to implement lesion segmentation of the disease images. Subsequently, the gray images on the nine components in the RGB, HSI, and L*a*b* color spaces of the segmented lesion images were filtered by using MB-LBP with pixel blocks in different sizes, and the corresponding LBP histogram features were extracted. Finally, based on these features, SVM models and random forest models were developed to distinguish the two kinds of apple fruit diseases. The aim of this study was to provide a rapid and accurate method for the non-destructive distinction of the two diseases in apple fruits.The distinction of ring rot and anthracnose on apple fruits based on image processing was conducted in accordance with the procedures as shown in A total of 123 apple fruit disease images were acquired using different digital cameras under field conditions, including 60 images of apple ring rot and 63 images of apple anthracnose. Most of the disease images used in this study were acquired in the apple orchards in Shangzhuang Experimental Station of China Agricultural University and Sujiatuo County, Haidian District, Beijing, China in the autumn of 2014 by using two digital cameras Canon PowerShot SX100 IS  and Canon EOS 700D , and were acquired in the apple orchards in Sujiatuo County, Haidian District, Beijing, China in the autumn of 2015 by using the digital camera Canon PowerShot SX100 IS. The other disease images were provided by Shutong Wang from the College of Plant Protection, Hebei Agricultural University, Baoding, China, and He Wang from Forest Pest Management and Quarantine Station of Beijing, Beijing, China.Preprocessing operations of the acquired disease images, including image scaling, color image contrast stretching, and morphological opening and closing reconstruction were performed by using the image processing toolbox in the software MATLAB R2013b .Because the disease images were acquired by using different digital cameras with different settings, there were obvious differences among the images in size. In order to process the disease images by using the same morphological operations, it is necessary to resize them into the same size range. In this study, the acquired disease images were scaled with an equal ratio in the range of 1,000 × 1,000 pixels to 2,000 × 2,000 pixels.rgbstr = imadjust), where rgb is the RGB color image to be processed, and rgbstr is the processed image.Color image contrast stretching is conducive to the enhancement of the color difference between the lesions and the surrounding background, and this operation facilitates the subsequent lesion image segmentation. Color image contrast stretching was operated by using the following MATLAB code: R, G, and B color components were performed using the circular structure element (disk) with a radius of 10, and then the obtained three color component images were integrated into a new color image by using the function “cat” in the MATLAB R2013b software.Morphological opening and closing by reconstruction operations can reduce the noise interference to the real edges . In thisThe backgrounds of apple disease images obtained in natural scenes are usually complex, mainly including soil, branches, and leaves of apple trees, other green plants, and local strong reflection. Automatic and accurate segmentation of lesions on the surface of apple fruit from the complex backgrounds is crucial for disease distinction and identification. Generally, the lesions of ring rot and anthracnose on apple fruits have two distinct characteristics. Firstly, the lesions are usually brown, thus the red component of the lesions in a disease image is often greater than the green component. This characteristic can be used to distinguish green elements such as the leaves of apple trees and other green plants in the background. Secondly, the lesions are located on the surface of apple fruit and are usually nearly round, and this characteristic can be used to distinguish branches of apple trees, soil, and other backgrounds with similar colors to the lesions. In this study, according to the above characteristics, the approximate position of apple fruits in a disease image was determined firstly, and then lesion segmentation was conducted by using the lesion image segmentation methods based on circle fitting. The steps for lesion image segmentation in detail are as follows.Step 1. To make full use of the image color information, the gradient of the integrated color image obtained after morphological opening and closing by reconstruction operations was first calculated. Assuming that c is the gradient of any point  in the color image, it can be calculated according to the method described by r, g, and b be the unit vectors of the R-axis, G-axis, and B-axis in the RGB color space, respectively, and the vectors u and v can be defined as:Let andgxx, gyy, and gxy represent the dot products of these vectors u and v, as follows:Let andc can be given by the angle θ, which can be calculated by using the following formula:here, the direction of the maximum change rate of x, y) in the direction of the angle θ can be given by using the following formula:and the value of the change rate at point  can be calculated.The partial derivatives of Formulas (3), (4), and (5) can be calculated by using the Sobel operator, and then the gradient of any point , was set to 20. The purpose of edge detection is to preserve the real edge, remove the false edge, and present the edge image in a binary pattern. In the binary edge image, the edge of the junction of the diseased and healthy regions may have breakpoints. Therefore, in this study, the circular structure element with a radius of 2 was used to conduct a dilation operation on the edge image to obtain the continuous lesion edge as much as possible.Step 3. To remove the green background such as the leaves of the apple tree and other green plants from the image, the pixel points with the green component greater than the red component were assigned a value of 0, and the other pixel points were assigned a value of 1, and then the green-background-subtracted binary image can be obtained. The green apple fruits in the image can also be removed in the process of the background subtraction. Because the lesions of the two apple fruit diseases are usually brown for which the green component is much smaller than the red component, they could still be completely retained in the image after the background subtraction, and thus the subsequent lesion extraction will not be affected. The binary edge image obtained in Step 2 was inversed, and then multiplied with the green-background-subtracted binary image, thus a new binary image was obtained.Step 4. Cavity filling of the binary image obtained in Step 3 was carried out. To avoid the adhesion between apple fruits and the background in the image and remove the relatively small background target, the circular structure element with a radius of 50 was used to conduct the opening operation on the binary image obtained after cavity filling.Step 5. The areas of all the remaining connected components were calculated, and any region for which the area of the connected component was less than two-thirds of the area of the maximum connected component was removed. The retained regions were regarded as the regions where apple fruits may exist.Step 6. Assuming that the number of the retained regions was M, that is, the number of the regions where apple fruits may exist was M, let j = 1, then the convex hull of the jth apple fruit region was calculated and the region contour was extracted. Considering that apple fruits are usually near-circular, circle fitting of the jth apple fruit region was carried out based on the contour combined with the least square method. Circular curve fitting by using the least square method was carried out according to the specific calculation method as described by Suppose the formula of the circular curve to be fitted is:Rad is the radius of the circle curve, and Ax and By are the abscissa and ordinate of the circle center, respectively.in which xi, yi) where i = 1, 2, …, N, and N represent the number of pixel points on the contour line. The distance from the ith pixel point in the set to the circle center is di, thenSuppose the pixel point set on the contour line is  to the circle center and the square of the radius of the circular curve, δi, can be described as the following formula:The difference between the square of the distance from the point  be the sum of squares of δi, thenLet a, b, and c were calculated to minimize Q . The partial derivatives of Q  with respect to a, b, and c were calculated, respectively, and then were set to 0, thus the extreme points could be achieved and the values of the corresponding parameters a, b, and c could be obtained. The partial derivatives of Q  with respect to a, b, and c were calculated according to the following Formulas (12), (13), and (14), respectively.The least-square method was used to calculate and achieve the optimal fitted circular curve, that is, the parameters a, b, and c were obtained, the fitted values of Ax, By, and Rad could be estimated according to the following Formulas (15), (16), and (17), respectively.After the values of the corresponding parameters jth apple fruit contour was conducted, the distances between all the pixel points in the image and the circle center were calculated, then the pixel points with a distance less than the circle radius were assigned a value of 1 and the other pixel points were assigned a value of 0, and thus the binary image of the jth apple fruit region was obtained.After circle fitting of the Step 7. Two methods were tried to find the real lesion edges in this study, thus the corresponding lesion image segmentation methods were classified as Lesion segmentation method 1 and Lesion segmentation method 2, respectively. For Lesion segmentation method 1, the binary edge image obtained in Step 2 was multiplied with the circle fitting binary image of the jth apple fruit region, in order to retain the edge inside the apple fruit region and remove the edge outside the apple fruit region; the convex hull areas of all the edges were calculated, and the edge with the largest convex hull area was considered as the edge of the junction of the diseased and healthy regions; then the convex hull contour corresponding to this edge was calculated, and the circle fitting method of apple fruit region was used to fit the contour, finally the region obtained by circle fitting was treated as the region where the disease lesion was located. For Lesion segmentation method 2, firstly, the circular structure element with a radius of 20 was used to conduct the closing operation on the image obtained by the opening operation in Step 4, and a binary image was obtained. The purpose of this operation was to reduce the possible depressions in the retained regions. Subsequently, the binary edge image obtained in Step 2 was multiplied with the circle fitting binary image of the jth apple fruit region and then was multiplied with the above binary image obtained by closing operation, aiming to retain the edge inside the apple fruit region and remove the edge outside the apple fruit region. The remaining procedures of Lesion segmentation method 2 were the same as that of Lesion segmentation method 1.Step 8. Let j = j+1, if j ≤ M, then Steps 6 and 7 will be repeated, otherwise the operations for the lesion image segmentation will be finished.After segmentation, each pixel in a lesion image was determined as a lesion pixel or a healthy pixel. The evaluation of image segmentation performance can be conducted by referring to the evaluation method of a binary classification model . The manN1 is the total number of lesion pixels in a lesion image correctly determined by using one of the segmentation methods described above, N2 is the total number of lesion pixels in the lesion image determined by using the manual segmentation method, and N3 is the total number of the pixels in the lesion image. All of these three indices range from 0 to 1. To evaluate the performances of the two lesion segmentation methods, the image dataset of apple ring rot comprising 60 images, the image dataset of apple anthracnose comprising 63 images, and the aggregated image dataset comprising all of the 123 images, were constructed by using the acquired images after preprocessing. The segmentation method with larger values of Recall, Precision, and Score, was chosen as the automatic lesion segmentation method for further disease image processing and disease distinction.where To reduce the influence of illumination on the image features, MB-LBP operators with pixel blocks in different sizes were used to filter the gray images on the nine components in the RGB, HSI, and L*a*b* color spaces of the segmented lesion images, and then the corresponding LBP histogram vectors were calculated.1-LBP, MB2-LBP, and MB3-LBP, respectively. For each MB-LBP operator, the number of neighborhoods was set to 8, and the neighborhood radius was set to 2. The MB3-LBP operator, as shown in 1-LBP operator and MB2-LBP operator are the same as the MB3-LBP operator except for the size of each pixel block.Initially, all of the segmented lesion images were resized to 256 × 256 pixels. The three-scale sizes of pixel blocks (sub-regions) were set as 1 × 1 pixels, 2 × 2 pixels, and 3 × 3 pixels, and the corresponding MB-LBP operators were recorded as MB1-LBP with the size of the pixel block of 1 × 1, MB2-LBP with the size of the pixel block of 2 × 2, and MB3-LBP with the size of the pixel block of 3 × 3, respectively, and the corresponding local binary pattern histogram vectors were calculated as the features of the lesion images  of the total number (N) of LBP histogram features used for modeling was treated as the number of features randomly selected. If N1/2 was a decimal, the integral number obtained by rounding up the decimal was considered the value of the feature number.A random forest, composed of multiple decision trees, can realize prediction by integrating the prediction result of each decision tree . This moFor apple ring rot, the results of image preprocessing and image segmentation, taking an image as an example, are shown in After lesion segmentation operations of all the diseased images were conducted by using the two lesion segmentation methods , the statistical results of Recalls, Precisions, and Scores for the two methods based on the three image datasets described above are shown in For the image dataset of apple ring rot, when Lesion segmentation method 1 was used, the mean and median of the Recalls were 0.93 and 0.99, respectively; the mean and median of the Precisions were 0.92 and 0.95, respectively; and the mean and median of the Scores were 0.93 and 0.95, respectively. For this image dataset, when Lesion segmentation method 2 was used, the mean and median of the Recalls were 0.81 and 0.89, respectively; the mean and median of the Precisions were 0.93 and 0.96, respectively; and the mean and median of the Scores were 0.87 and 0.93, respectively. The results demonstrated that, for the image dataset of apple ring rot, the means and medians of the Recalls and Scores obtained when Lesion segmentation method 1 was used, were higher than those obtained when Lesion segmentation method 2 was used; and the mean and median of the Precisions were similar when Lesion segmentation method 1 and Lesion segmentation method 2 were used, respectively. The results indicated that Lesion segmentation method 1 was more suitable for lesion segmentation of the images of ring rot on apple fruits.For the image dataset of apple anthracnose, when Lesion segmentation method 1 was used, the mean and median of the Recalls were 0.95 and 1, respectively; the mean and median of the Precisions were 0.94 and 0.97, respectively; and the mean and median of the Scores were 0.94 and 0.97, respectively. When Lesion segmentation method 2 was used on this image dataset, the mean and median of the Recalls were 0.91 and 0.99, respectively; the mean and median of the Precisions were 0.96 and 0.97, respectively; and the mean and median of the Scores were 0.93 and 0.97, respectively. The results demonstrated that, for the image dataset of apple anthracnose, the mean and median of the Recalls, Precisions, or Scores obtained when Lesion segmentation method 1 and Lesion segmentation method 2 were used, respectively, were similar, and all the indices were more than 0.9. The results indicated that these two lesion segmentation methods were both suitable for lesion segmentation of the images of apple anthracnose.For the image dataset of the aggregated image dataset obtained after aggregation of the two image datasets of apple ring rot and apple anthracnose, when Lesion segmentation method 1 was used, the mean and median of the Recalls were 0.94 and 0.99, respectively; the mean and median of the Precisions were 0.93 and 0.96, respectively; and the mean and median of the Scores were 0.93 and 0.96, respectively. For this aggregated image dataset, when Lesion segmentation method 2 was used, the mean and median of the Recalls were 0.86 and 0.96, respectively; the mean and median of the Precisions were 0.95 and 0.97, respectively; and the mean and median of the Scores were 0.9 and 0.95, respectively. The results showed that, for the aggregated image dataset, the mean and median of the Recalls or Scores obtained when Lesion segmentation method 1 was used, were both higher than those obtained when Lesion segmentation method 2 was used, and the mean and median of the Precisions obtained when the former method was used were similar to those obtained when the latter method was used.The results described above indicated that Lesion segmentation method 1 was more suitable for lesion segmentation of the images of ring rot and anthracnose on apple fruits. Therefore, Lesion segmentation method 1 was selected for realizing the automatic segmentation of the lesion images of the two apple fruit diseases in this study.R component of the lesion image filtered by the MB1-LBP operator, and R2 denoted the LBP histogram feature of the gray image of the R component of the lesion image filtered by the MB2-LBP operator, R1G1 denoted the combination of R1 and G1, and the rest features’ names could be deduced by analogy. The results showed that the optimal SVM model for disease distinction was built based on the feature L1a1 and that this SVM model had the best distinction performance. For this optimal SVM model, the parameters Cbest and gbest were 12.126 and 0.144, respectively, and the distinction accuracy of the training set was 100% and the distinction accuracy of the testing set was 95.12%. The model for which the distinction performance ranked second among all the built SVM models, was built based on the feature R1B1 with the parameters Cbest and gbest of 21.112 and 0.047. For this model, the distinction accuracies of the training set and testing set were 96.34% and 92.68%, respectively. The model for which the distinction performance ranked third among all the built SVM models, was built based on the feature R1 with the parameters Cbest and gbest of 21.112 and 0.082. For this model, the distinction accuracy of the training set was 93.9% and the distinction accuracy of the testing set was 90.24%. The SVM model was built based on the feature R1G1B1 with the optimal parameters Cbest and gbest of 194.012 and 0.016 and the SVM model was built based on the feature L1a1b1 with the optimal parameters Cbest and gbest of 6.964 and 0.082, the distinction accuracies of the training set were both 100% and the distinction accuracies of the testing set were both 87.8%. For the SVM model built based on the feature L1b1 with the optimal parameters, Cbest and gbest of 2.297 and 0.25, the distinction accuracies of the training set and testing set were 97.56 and 85.37%, respectively. For the SVM model built based on the feature R1G1 with the optimal parameters, Cbest and gbest of 2.297 and 0.144, the distinction accuracies of the training set and testing set were 92.68 and 85.37%, respectively. The results demonstrated that accurate distinction of apple ring rot and apple anthracnose can be achieved by using the SVM modeling method based on LBP histogram features. The LBP histogram features used in the above SVM models with satisfactory distinction performances were obtained by filtering the gray images of the related components with the MB1-LBP operator. Compared with the other two MB-LBP operators (MB2-LBP and MB2-LBP), the pixel block of the MB1-LBP operator is the smallest, and the highest fineness of the image texture can be obtained after image filtering with it, which may be helpful to improve the ability of the models to distinguish between apple ring rot and apple anthracnose.The distinction results of the SVM models based on the LBP histogram features of the gray images on each individual component in the RGB, HSI, and L*a*b* color spaces of the segmented lesion images are shown in The distinction results of the random forest models built based on the LBP histogram features of the gray images of the three components in the RGB, HIS, and L*a*b* color spaces of the segmented lesion images of apple ring rot and apple anthracnose are shown in 1-LBP, MB2-LBP, and MB3-LBP operators, respectively, and the corresponding LBP histogram features were extracted for further disease distinction. The results demonstrated that for the built disease distinction SVM model based on the feature R1, R1G1, R1B1, L1a1, L1b1, R1G1B1, or L1a1b1, the distinction accuracies of the training set and testing set were high, and the satisfactory disease distinction performance was achieved. Among these SVM models, the distinction performance of the model built based on the feature L1a1 was optimal. The obtained results showed that the satisfactory disease distinction performance could be achieved when the random forest model was built based on the features R1, I3, R1G1, R1B1, H1S1, H3I3, L1b1, L3a3, R1G1B1, H1S1I1, or L3a3b3. Among these random forest model models, the distinction performance of the model built based on the feature R1B1 was optimal. For both the SVM model and the random forest model based on the feature R1B1, the distinction accuracies of the training set and testing set were more than 90%, indicating that the feature R1B1 can be utilized to well distinguish between ring rot and anthracnose on apple fruits. In practical applications, the disease image database as a training set may be very large. Generally, the random forest model runs faster than the SVM model, and it is easy to realize large-scale parallel computing and rapid analysis of massive data by using the random forest method. Considering these factors, it is suggested that using R1B1 features to build a random forest model can be carried out for the distinction of the images of ring rot and anthracnose on apple fruits. The results indicated that it is feasible to distinguish between ring rot and anthracnose with typical symptoms on apple fruits by using the method proposed in this study.Diseases play important roles in the reduction of the yield and quality of apple fruits. Accurate disease diagnosis is a key prerequisite for the prevention and control of apple diseases. In this study, taking ring rot and anthracnose on apple fruits as the research objects, the lesion image segmentation of the two apple diseases was carried out, and then the MB-LBP features were extracted from the segmented lesion images, finally, the distinction of the images of the two apple diseases was conducted by using both the SVM method and the random forest method. According to the characteristics of the lesions of the two apple diseases, two lesion segmentation methods based on circle fitting, Lesion segmentation method 1 and Lesion segmentation method 2, were developed and compared. The statistical results of three evaluation indices including Recall, Precision, and Score of the two lesion segmentation methods indicated that Lesion segmentation method 1 was better than Lesion segmentation method 2. Therefore, Lesion segmentation method 1 was selected to realize automatic segmentation of the lesion images in this study. To reduce the influence of illumination on the features of lesion images, the gray images of the nine components in the RGB, HSI, and L*a*b* color spaces of the segmented lesion images of the two apple diseases were filtered by using MBDisease images obtained in natural scenes often have complex backgrounds, which can induce uneven illumination, various noises, blurred lesion edges, and other phenomena in the images. Therefore, under these circumstances, it is difficult to conduct complete lesion image segmentation. Extracted features from the segmented lesion images are the bases of disease image recognition. However, uneven illumination and illumination changes can affect the extracted image features. In this study, the MB-LBP operators were used to extract the texture features in different scales and to reduce the influence of image noise caused by the factors including uneven illumination and illumination changes and based on the extracted features, satisfactory distinction results of the two apple diseases were achieved by using both the SVM method and the random forest method. As a local texture descriptor, the LBP operator has been utilized in plant disease image recognition . It has Deep learning has been applied to plant disease image recognition . It can In recent years, image processing and recognition techniques have been developed and applied in many fields such as automatic apple picking , non-desTrichothecium roseum, and Phytophthora rot caused by Phytophthora cactorum , there are other apple fruit diseases such as scab, fruit moldy core rot caused by cactorum . The rescactorum , but usuThe original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.HGW contributed conception of the study. HGW and QF designed the experiments. QF, SW, HW, ZQ, and HGW performed the experiments. QF and HGW analyzed the data and wrote the draft of the manuscript. All authors contributed to manuscript revision, read, and approved the final version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Three ETLs, including MoS2, lithium quinolate (Liq), and a MoS2/Liq bilayer, were evaporated onto ITO-integrated polyethylene terephthalate substrates (PET-ITO), and the properties of transmittance, water contact angle, and reflectivity of the films were analyzed. The results revealed that MoS2 was helpful to improve the lipophilicity of the surface of the ETL, which was conducive to the deposition of the active layer. In addition, the reflectivity of MoS2 to the light ranging from 400 to 600 nm was the largest among the pristine PET-ITO substrate and the PET-ITO coated with three ETLs, which promoted the efficient use of the light. The efficiency of the FOPV with MoS2/Liq ETL was 73% higher than that of the pristine device. This was attributed to the nearly two-fold amplification of the MoS2 array to the light field, which promoted the FOPV to absorb more light. Moreover, the efficiency of the FOPV with MoS2 was maintained under different illumination angles and bending angles. The results demonstrate the promising applications of MoS2 in the fabrication of FOPVs.In this work, we investigated the influence of MoS Flexible organic photovoltaics (FOPVs) have become one of the hottest directions in the field of OPV research ,2. Neith2 make it one of the most attractive 2D materials in applications in ETLs [2 nanosheet as the ETL [2 nanosheet played an important role as a sub-photo sensitizer and an ETL, providing effective charge separation in the OPV. However, a deeper analysis of the performance improvement of FOPVs brought by MoS2 is still needed.Two-dimensional (2D) materials are a class of widely researched ETLs due to their merits of high optical transparency, high charge carrier mobility, high stability, and tunable work function ,33,34,35 in ETLs ,37,38,39 the ETL . They re2 micro-nano array as an ETL in FOPV. Three ETLs, which are lithium quinolate (Liq), MoS2, and a MoS2/Liq bilayer, were applied in FOPV. Then the performance differences between the ETLs were studied by analyzing their transmittance, water contact angle, and reflectivity. The results revealed that MoS2 was helpful to improve lipophilicity, which was conducive to the deposition of the active layer. The reflectivity of MoS2 to the light ranging from 400 to 600 nm was the largest, which promoted the efficient use of the light. The efficiency of the FOPV with MoS2 EIL was 73% higher than that of the pristine FOPV. This was primarily attributed to the nearly two-fold amplification of the MoS2 array to the light field, which promoted the FOPV to absorb more light. Moreover, the efficiency of the FOPV with MoS2 was maintained under different illumination angles and bending angles. The results demonstrate the promising applications of MoS2 in the fabrication of FOPVs.This work investigated the application of a MoS2 ETL), and Film D (with MoS2/Liq ETL), respectively.The characteristics of the four kinds of films were explored in detail on the basis of transmittance, absorption, water contact angle, and reflectivity. The films containing different ETLs on the PET-ITO substrate were defined as Film A (without ETL), Film B (with Liq ETL), Film C  compared to that of Liq (3 nm) could also be the cause for its high reflectivity. In addition, there might be a waveguide function of the nano-array structure, which could further limit the transmission of light [2 was preferred as the ETL to promote the effective use of the light.of light . To makeoc), and short-circuit current density (Jsc). Despite that the Voc and the Jsc of Device C are not as good as those of Device D, its filling factor (FF) is the highest among the four films. The Voc and the Jsc of Devices A and B are nearly the same, but Device B has a larger FF than Device A. Since the work function of MoS2 is located between that of ITO and the LUMO of PC71BM, as shown in the inset of oc of Devices C and D was optimized. The corresponding values of the four devices (averaged from three devices) are summarized in oc, Jsc, FF, and PCE of Device D are 0.66 V, 10.66 mA cm−2, 46.71%, and 3.3%, respectively, which are the best among the four devices. The PCE of Device C and Device D increased by 63% and 73% compared to that of Device A. In addition, the J-V characteristic curves of the four devices are all “S-shaped”, which means that there exists a leakage current between layers, and hence, there still exists an opportunity for the optimization of the device structure. Meanwhile, the external quantum efficiency (EQE) and integrated Jsc were also analyzed. As shown in sc of 15.15 mA/cm2.The J-V test for four devices is shown in 2/Liq ETL was significantly better than others. To illustrate the conclusion in detail, we analyzed the surface morphology of the MoS2 ETL. As depicted in 2 is no longer a thin film in terms of morphology, but rather a micro-nano array with the ability of light field amplification. The schematic diagram of the devices with the MoS2 array and Liq film is presented in 2 showed the optical field amplification effect, leading to the absorption of more light. To reveal the influence of the MoS2 array on the performance of the FOPV, we further adapted the FDTD simulation to investigate the light field of the films. As can be seen from 2 array on the light field is significantly demonstrated. The intensity of the light field in the active layer is nearly doubled compared to the device without an array structure. This ability promoted the FOPV to absorb more light, which contributes to enhanced device performance.From the above analyses, it could be concluded that the performance of FOPV containing MoS2 array can greatly reduce the light angle sensitivity of the device, which allows the device to collect light energy more effectively at different time periods in practical applications. Therefore, the energy loss caused by the light angle was reduced, and the application of the FOPV was greatly broadened.The relationship between the efficiencies of the devices and illumination angles is shown in 2 insensitive to the bending angle, but its efficiency is also higher than the initial efficiency, even though the bending angle is approximately 10°. Hence, the device containing MoS2 was very conducive to its subsequent practical application.For FOPV, not only the illumination angle but also the bending angle plays an indispensable role in the practical application of the device, especially when the devices are applied to the surface of flexible objects such as curtains, backpacks, and solar sails, which cannot maintain a fixed angle for collecting the light source. Therefore, it is important to maintain the performance under different bending angles of the objects to which the devices are applied. 2 powder  and aluminum (99%) were purchased from Sigma Aldrich. Liq , MoO3 , donor material PTB7-Th, and acceptor material PC71BM  were all purchased from Lumtec Optoelectronic Materials Co. Ltd. The proportioning method for the construction of the active layer is given here. The weight ratio of the PTB7-Th:PC71BM solvent was 2:3. The solvent was produced by mixing the chlorobenzene and the 1,8-diiodooctane according to the ratio of 97:3. The vacuum evaporation equipment used to thermally evaporate ETLs was purchased from Shenyang Lining Vacuum Co., Ltd. . MoS2 was placed on the tungsten boat and fixed between two electrodes in the evaporation chamber. Then, the chamber was vacuumed to 10−4 mbar, and the current source was turned on to evaporate the MoS2. Liq was put in a crucible surrounded by the heating source and was sublimated at 260−270 °C. A crystal oscillator located on the top of the chamber  was used to detect the rate of evaporation and the thickness of the film. We kept the lifetime of the oscillator above 85% to guarantee its high accuracy. For each ETL, we used atomic force microscope (AFM) analysis to measure their thicknesses, and the calibration parameter between the test and measured thickness was set in the Deposition Controller. Therefore, the error of the detected thickness of 10 nm (MoS2) and 3 nm (Liq) was less than 0.2 nm.The PET-ITO substrates  were purchased from Shanghai Quanhua Trading Co. Ltd., and the average transmittance of the substrate at 400 to 700 nm was 70%. MoS3 (5 nm)/Al (120 nm). We defined Device A as the pristine FOPV without an ETL, Device B with 3 nm Liq, Device C with 10 nm MoS2, and Device D with MoS2 (10 nm)/Liq (3 nm) as the ETL. The structure and energy level of Device D are shown in the inset of There are four kinds of FOPVs with different ETLs. The pristine structure was ITO (200 nm)/ETLs/PTB7-Th:PC71BM (80 nm)/MoO3 was evaporated onto the active layer, and a 120 nm Al electrode was deposited.The PET-ITO substrates were ultrasonically cleaned in deionized water, acetone, and isopropanol sequentially and were dried under the tungsten lamp. Then, the substrates were UV-ozone treated for five minutes. The ETLs were thermally evaporated onto the substrate at a rate of 0.3 Å/s, and then PTB7-Th:PC71BM was spin-coated at a speed of 1000 rpm for 90 s. The spin-coated substrate was wiped with a cotton swab with chloroform to expose the electrodes. The substrate was moved into the evaporation chamber again and was vacuumized for 1 h to pump away the solvent. Then, 5 nm MoO−2. The programmable light source meter (Keithley 2400) and the sunlight simulator AM 1.5 G were used to simulate the solar spectrum to collect the J-V characteristic curve of the device. All performance tests were carried out in the environment without encapsulated devices.The FOPVs were connected to the external power supply and then continuously exposed to light with an intensity of 100 mWcmWater contact angle measurement was analyzed to reveal the wettability of the film surface by measuring the liquid–solid contact angle. In this test, the contact angle goniometer was used to measure the surface tension, wettability, and other information of deionized water and different substrates. The measurement method was a circle-fitting method.The reflectivity test was based on the external quantum efficiency (EQE) detection platform. The 7-SCSpec solar cell measurement system manufactured by the 7-STAR company was used to first test the reflectance spectrum of the standard white plate and then test the reflectance spectrum of the sample. Eventually, the reflectivity of the sample was calculated by using the standard reflectivity.A is the absorbance, T is the transmittance, K is the molar absorption coefficient, b is the sample thickness, and c is the sample concentration.The basic principle of the transmittance test can be described as follows: When the incident light is exposed to the surface of the sample, part of the light passing through the sample can be collected by the machine, and then the transmittance of the sample at each frequency can be obtained by comparing the wavelengths of the incident light and the collected light. The basic principle of the absorbance test is to record the absorption spectrum by taking advantage of the transition phenomenon produced when the molecules in the sample are absorbing ultraviolet and visible light. The relationship between the transmittance and the absorbance satisfies Formula (1) (Beer–Lambert Law):2 ETL on the inverted flexible FOPVs. The properties of the ETLs, including transmittance, the water contact angle, and reflectivity, were systematically analyzed. The results revealed that MoS2 was helpful to improve the lipophilicity of the surface of the ETL, which was conducive to the deposition of the active layer. The reflectivity of MoS2 to light ranging from 400 to 600 nm was the largest among the pristine PET-ITO substrate and the PET-ITO coated with three ETLs, which promoted the efficient use of the light. The efficiency of the FOPV with MoS2 EIL was 73% higher than that of the pristine device. This was primarily attributed to the nearly two-fold amplification of the MoS2 array to the light field, which promoted the FOPV to absorb more light. Moreover, the efficiency of the FOPV with MoS2 was maintained under different illumination angles and bending angles. The results shed light on the promising applications of MoS2 in the fabrication of FOPVs.In summary, we investigated the influence of MoS


The tests were carried out in a computerized numerical control (CNC) machining center used in the furniture industry. Based on the measurements of the direct tool wear indicator (W), the drill wear curves were determined and the relative tool life index, standard deviation, coefficient of variation, and the implantation quality index of tool life were calculated. The studies have shown that the modification of the drill surface layer by the nitrogen ion implantation process increases the tool life. The obtained results allow the research to be the continued in a wider scope.The paper presents the effect of nitrogen ion implantation on the tool life of the tools commonly used in the furniture industry for drilling particleboards. Nitrogen ions with different accelerating voltages of 25, 40, 55, and 70 kV and a fluence of 5 × 10 The increasing use of wood-based composites in the furniture and construction industries has created a need for high-performance and complex tooling systems that are capable of resisting the aggressive wear environment associated with the machining of these materials.Regardless of the introduction of new tool materials in wood machining, such as WC-Co composites and polycrystalline diamonds, high-speed tool steel (HSS) is still a tool material of choice in CNC drilling . The popThe three-layer particleboard used in the tests can be described as a material with low machinability due to an increased tool wear caused by the presence of minerals, adhesives, and fillers . At the The wear of the cutting tools is a limiting factor in the high-performance machining of wood and wood-based panels. Tool wear affects not only tool life, but also energy consumption, surface finish, and production rate. To increase productivity and lower operating costs, advanced cutting tools are required that can provide longer tool life, less unplanned downtime, and better surface quality.Improving the durability of cutting tools has been of interest to many researchers for many years ,6,7. TooIn the case of steel tools used in the woodworking industry, the modification and the improvement of the properties of the surface layer were realized by one of the most known and widespread technologies of ion nitriding ,10 and pThe deposition of additional layers usually means the application of hard coatings produced by physical vapor deposition or chemical vapor deposition ,13. For Ion implantation is a method of modifying the subsurface area  with a wResearch on the durability of carbide blades used for milling a three-layer chipboard, subjected to implantation with nitrogen ions, showed an increase in the durability of the tools .However, there are few scientific reports that concern the implantation of the drill bits used for cutting in the wood industry with ions . WilkowsThis work is a continuation of the above-mentioned work and presents the results of research aimed at extending the service life of the high-speed steel drills used in the processing of wood and wood-based materials by applying nitrogen ion implantation at various ion energies.Double-edged HSS Leitz drills  for blind drilling, with a diameter of 10 mm and a total length of 68 mm , were us2+ + N+, in the ratio ~1:1; so, there were two elementary charges per three atoms. For example, in the case of the N2 molecule implanted with the acceleration voltage of 70 kV, each atom carries the energy of 35 keV, according to the law of energy conservation. It means that, for example, for a total fluence of 5 × 1017 cm−2, the fluence of 1.65 × 1017 cm−2 is implanted with the energy of 70 keV and the fluence of 3.35 × 1017 cm−2 is implanted with the energy of 35 keV. The average charge state (ACS) is at the level of 0.67 [Nitrogen of 99.999% purity was used as the source of the implanted ions. The implanted nitrogen was delivered as two kinds of ions, i.e., N17 cm−2 in all cases. The acceleration voltage of the implanted ions was 25, 40, 55, or 70 kV. The beam current density was at a level of 0.6 mAcm−2. The implanted drills were clamped onto a stainless-steel plate to avoid overheating effects; so, the estimated value of temperature of the implanted drills did not exceed 200 °C. The working pressure in the vacuum chamber was at a level from 2 to 5 × 10−3 Pa.The implanted fluences (doses) were 5 × 10maxN, projected range pR, range straggling ΔpR, kurtosis, and skewness) [The ion implantation processes were preceded by Monte Carlo simulations of the main parameters of the depth profiles of the implanted elements (such as peak volume dopant concentration kewness) , using fkewness) . The simkewness) , from th17 cm−2. The detailed information about the values of the acceleration voltage and the energy of the implanted ions is presented in In all cases, the simulations were performed for room temperature and for the total implanted fluence of 5 × 10The selected elements of the microstructure in the transverse micro-sections, obtained using SEM and EDS methods, were presented in our previous paper . No chan3 was machined. The characteristics of this material are presented in The tool life tests were carried out on 30 drills of one type. Six repetitions of cutting were used for each type of implantation and reference drills. The cuttings were performed using the Centateq P-110 Homag CNC machining center , as shown in 3 were blind drilled to a depth of 15 mm with five tools simultaneously , using drilling gear V12/H4 × 2Y, as shown in Workpieces with dimensions of 1000 × 400 × 18 mm−1 and a spindle speed of 6000 rpm. The value of the tool wear indicator W (the maximum size of the corner wear) was measured as shown in W indicator of the drill were calculated from Equation (1),W′ is the corner wear of the first edge of the drill (mm) and W″ is that of the second edge of the drill (mm).Drilling was carried out for the cutting parameters recommended by the tool manufacturer, i.e., feed speed 2 m∙minThe analysis of the tool wear was performed with the use of vision methods, based on images taken with a Canon EOS 40D digital camera, with a CMOS matrix resolution of 10.1 MPx, equipped with the Canon EF 100 mm f/2.8 Macro USM lens. The images were processed in the Gimp 2.10.24 open-source program for editing raster graphics.The machining was conducted in the form of blunting cycles. The number of holes for particular cycles and the overall number of holes are given in R2, determined using Microsoft Excel 2010 spreadsheet, are presented in The modelled depth profiles of the nitrogen ions implanted in the iron substrate are shown in 23 cm−2 for the acceleration voltage of 25 kV to 6.88 × 1022 cm−2 for 70 kV. A more than twofold change has a polynomial dependence on voltage with the determination factor R-squared displayed in the chart.We can see that the value of the peak volume dopant concentration changes from 1.56 × 10The calculated values of sputtering yield are relatively low, and they change from 0.94 to 0.8 for the used range of the acceleration voltage. This change can be described by a 2nd degree polynomial trendline, with the significant determination factor at the level of 0.9995.The values of the projected range, the range straggling, the kurtosis, and the skewness change in the discussed range display linear dependence on voltage. The values of the projected range and the range straggling increase with the growth of the acceleration voltage, and they are at a level of tens of nanometers. This is a typical trend. In contrast, the values of kurtosis and skewness decrease with the growth of the acceleration voltage. The relatively high values of the kurtosis and the skewness are caused by the non-homogeneity of the nitrogen ion beam.W) on the number of holes made with each tool during the test. Thirty tools were tested. It should be emphasized that the wear curves of virgin (un-implanted) drills have a different shape as compared to the implanted drills. The primary/initial wear zone is clearly visible, with rapid initial wear, as shown in RI) of the best modification was 1.17, which meant that the tool life was 17% higher than the virgin tools group. The best implantation variant was the one obtained for the acceleration voltage of 70 kV, but the differences between the means for the implanted tools groups were not statistically significant.CV) of the virgin drills was more than twice as high as the worst variant of the implanted drills. The coefficient of variation of tool life is of great importance in industrial practice. For drills that wear in a similar time, i.e., with a low value of the coefficient of variation, it is easier to automate the machining process than when the coefficient of variation of tool life is large. An interesting effect of implantation is a significant reduction in the coefficient of variation of tool life (The coefficient of variation of tool life (ool life b.QI), being the ratio of the relative index of tool life (RI) and the coefficient of variation of tool life (CV):QI—the quality index of tool life, RI—the relative index of tool life, and CV—the coefficient of variation of tool life.Objectively, the quality of the tool modification process can be characterized by the quality index of tool life (QI) value, the better the tools in terms of industrial utility. In the group of tested tools, as shown in QI index was almost six times higher than the QI index obtained for the virgin tools group.The quality index is a very important industrial parameter, next to the relative index of tool life. The higher the quality index . The index QI for this group of drills was 17.88, while for the virgin tools it was 3.08.Nitrogen ion implantation with an acceleration voltage of 40 kV is characterized by the highest quality of the modification process described by the quality index (The wear curves for the implanted tools do not follow the classic wear theory (the Lorenz wear curve). They are clearly linear, and no rapid initial wear in the break-in period occurs.Based on the results, the following conclusions can be drawn:Based on the previous experience, the authors plan to extend the works of the implanted drills. The investigations of the ion implantation of carbide drills will be next.