Objective Evaluation Method Research Articles

Smart predictive analytics care monitoring model based on multi sensor IoT system: Management of diaper and attitude for the bedridden elderly

In this paper, we propose a multi-sensor IoT system-based smart predictive analytics care and movement monitoring model that can be applied to various diapers and solve these problems for the bedridden elderly. A multi-sensor is designed to monitor the condition of the diaper and the movement of the bedridden elderly, in addition, to know the use condition of the diaper and the attitude of the bedridden elderly. In addition, through the changed pattern of the time series data acquired from the multi-sensor, a model that can know not only the presence or absence of urine/feces/farts but also the attitude of bedridden people is constructed and compared to this, it detects urine/feces/farts, care sensing to know the diaper usage status and the bedridden elderly's attitude duration. We propose smart predictive analytics care monitoring model based on multi sensor IoT system: management of diaper and attitude for the bedridden elderly. The design and proposed method are tested and the results are derived through an accredited certification body for an objective evaluation method.

Reliability of electroencephalogram indicator and event related potential in subacute stroke

Cognitive impairment is observed in 12% to 56% of stroke patients, and screening for cognitive impairment is often complex and time-consuming, with results dependent on patient compliance. Therefore, there is a need for an objective method to assess cognitive impairment regardless of patient compliance. Objective evaluation methods include electroencephalogram (EEG) and event-related potential (ERP). This study was conducted to assess intra-tester reliability of resting EEG-based spectral features and auditory/visual P300 latency/amplitude in patients with subacute ischemic stroke. Twenty patients with subacute ischemic stroke were included in the study. The resting EEG and P300 wave using an auditory and visual oddball paradigm were measured at baseline and once again in 24 hours. The following electrode positions (10-20 system) were constantly recorded: F3 (Frontal), Fz, F4, C3 (Central), Cz, C4, P3 (Parietal), Pz, P4. DAR (delta/alpha ratio) and BSI (brain symmetry index) were determined using EEG data. F3 and F4, C3 and C4 and P3 and P4 were switched according to the stroke side and classified as affected hemisphere (AH) and unaffected hemisphere (UH) after the evaluation. In ERP, the amplitude and latency of P300 were obtained. In reliability analysis of EEG-based spectral characteristics, significant reliability was observed for DAR (ICC = 0.447), BSldir (ICC = 0.713) and BSIdirtheta (ICC = 0.724) (Table 4). DAR was showed a poor ICC level, and BSIdir and BSIdirtheta had a moderate ICC level. Visual P300 latency showed excellent intraclass correlation coefficient (ICC) in several montages (PUH = 0.972, Pz = 0.945). In 6 montages, auditory P300 latency was reliable, while in 9 montages, visual P300 latency was reliable. In 4 montages, auditory P300 amplitude was reliable, while visual P300 amplitude was reliable in 7. The visual P300 was more reliable than the auditory P300. The ICC values for P300 latency were greater than those for amplitude. Therefore, when ERP is performed on subacute stroke patients, visual has higher reliability than auditory.

Photometric Stereo-Based 3D Reconstruction Method for the Objective Evaluation of Fabric Pilling

Fabric pilling evaluation has been considered as an essential element for textile quality inspection. Traditional manual method is still based on human eyes and brain, which is subjective with low efficiency. This paper proposes an objective evaluation method based on semi-calibrated near-light Photometric Stereo (PS). Fabric images are digitalized by self-developed image acquisition system. The 3D depth information of each point could be obtained by PS algorithm and then mapped to 2D grayscale image. After that, the non-textured image could be filtered by using the Gaussian low-pass filter. The pilling segmentation is conducted by using global iterative threshold segmentation method, and then K-Nearest Neighbor (KNN) is finally selected as a tool for the grade classification of fabric pilling. Our experimental results show that the proposed evaluation system could achieve excellent judging performance for the objective pilling evaluation.

Research on the comprehensive evaluation of the value of water conservancy heritage based on expert knowledge and public cognition: a case study of Red Flag Canal

Abstract The scientific construction of the indicator system and the objective evaluation method that apply to the value of water conservancy heritage are of great significance to the promotion and development of water culture and water conservancy heritage conservation. This study constructs an index system for water conservancy heritage value assessment from seven first-level indexes, such as engineering value, economic value, social value, ecological value, artistic value, innovative value and heritage value, builds a fuzzy comprehensive evaluation model based on expert knowledge and public perception and carries out empirical evidence with the example of China's Red Flag Canal. The results show that the overall value of the Red Flag Canal was 94.68 points, which reached a high level. The result is consistent with that the Red Flag Canal was successfully declared as the national water conservancy heritage, thus verifying the scientificity and rationality of the index system and the evaluation method constructed by this study.

Label-free quantitative proteomics and stress responses in pigs-The case of short or long road transportation.

Ethical livestock production is currently a major concern for consumers. In parallel, research has shown that transport duration is an important factor affecting animal welfare and has a negative impact on the final product quality and on the production cost. This study applied proteomics methods to the animal stress/welfare problem in pigs muscle-exudate with the aim to identify proteins indicative of molecular processes underpinning transport stress and to better characterise this species as a biomedical model. A broader perspective of the problem was obtained by applying label-free LC-MS to characterise the proteome response to transport stress (short or long road transportation) in pigs within the same genetic line. A total of 1,464 proteins were identified, following statistical analysis 66 proteins clearly separating pigs subject to short road transportation and pigs subject long road transportation. These proteins were mainly involved in cellular and metabolic processes. Catalase and stress-induced phosphoprotein-1 were further confirmed by Western blot as being involved in the process of self-protection of the cells in response to stress. This study provide an insight into the molecular processes that are involved in pig adaptability to transport stress and are a step-forward for the development of an objective evaluation method of stress in order to improve animal care and management in farm animals.

Extraction and Quantification of Words Representing Degrees of Diseases: Combining the Fuzzy C-Means Method and Gaussian Membership

Due to the development of medical data, a large amount of clinical data has been generated. These unstructured data contain substantial information. Extracting useful knowledge from this data and making scientific decisions for diagnosing and treating diseases have become increasingly necessary. Unstructured data, such as in the Marketplace for Medical Information in Intensive Care III (MIMIC-III) data set, contain several ambiguous words that demonstrate the subjectivity of doctors, such as descriptions of patient symptoms. These data could be used to further improve the accuracy of medical diagnostic system assessments. To the best of our knowledge, there is currently no method for extracting subjective words that express the extent of these symptoms (hereinafter, "degree words"). Therefore, we propose using the fuzzy c-means (FCM) method and Gaussian membership to quantify the degree words in the clinical medical data set MIMIC-III. First, we preprocessed the 381,091 radiology reports collected in MIMIC-III, and then we used the FCM method to extract degree words from unstructured text. Thereafter, we used the Gaussian membership method to quantify the extracted degree words, which transform the fuzzy words extracted from the medical text into computer-recognizable numbers. The results showed that the digitization of ambiguous words in medical texts is feasible. The words representing each degree of each disease had a range of corresponding values. Examples of membership medians were 2.971 (atelectasis), 3.121 (pneumonia), 2.899 (pneumothorax), 3.051 (pulmonary edema), and 2.435 (pulmonary embolus). Additionally, all extracted words contained the same subjective words (low, high, etc), which allows for an objective evaluation method. Furthermore, we will verify the specific impact of the quantification results of ambiguous words such as symptom words and degree words on the use of medical texts in subsequent studies. These same ambiguous words may be used as a new set of feature values to represent the disorders. This study proposes an innovative method for handling subjective words. We used the FCM method to extract the subjective degree words in the English-interpreted report of the MIMIC-III and then used the Gaussian functions to quantify the subjective degree words. In this method, words containing subjectivity in unstructured texts can be automatically processed and transformed into numerical ranges by digital processing. It was concluded that the digitization of ambiguous words in medical texts is feasible.

A Narrative Review of the Usefulness of Indocyanine Green Fluorescence Angiography for Perfusion Assessment in Colorectal Surgery.

Anastomotic leakage is one of the most dreaded complications of colorectal surgery and is strongly associated with tissue perfusion. Indocyanine green fluorescence angiography (ICG-FA) using indocyanine green and near-infrared systems is an innovative technique that allows the visualization of anastomotic perfusion. Based on this information on tissue perfusion status, surgeons will be able to clearly identify colorectal segments with good blood flow for safer colorectal anastomosis. The results of several clinical trials indicate that ICG-FA may reduce the risk of AL in colorectal resection; however, the level of evidence is not high, as several other studies have failed to demonstrate a reduction in the risk of AL. Several large-scale RCTs are currently underway, and their results will determine whether ICG-FA is, indeed, useful. The major limitation of the current ICG-FA evaluation method, however, is that it is subjective and based on visual assessment by the surgeon. To complement this, the utility of objective evaluation methods for fluorescence using quantitative parameters is being investigated. Promising results have been reported from several clinical trials, but all trials are preliminary owing to their small sample size and lack of standardized protocols for quantitative evaluation. Therefore, appropriately standardized, high-quality, large-scale studies are warranted.

Аналитический обзор метрик, используемых для оценки качества мультимедийной информации

Data quality is an indicator that characterizes any transmitted information that can be measured. The very word “measure” suggests the evaluation of these data, the quality of which can be described and quantified. The metric, in turn, is essentially an objective assessment during testing, which makes it possible to determine data distortions that occur during transmission, encoding, digitization, compression, and decoding of video data. The article considers such metrics as PSNR and VQM, and analyzes the ITU-R-BT.500-8.11 standard. A brief overview of the MSU Video Quality Measurement Tool is presented, as well as a simulated video conferencing image acquisition using one of the most popular H264 codecs. The formulas for calculating the PSNR metric, defined through the mean square error (MSE), estimating the loss of image quality by comparing the received video with the downloaded (reference video) are presented. The VQM (Video Quality Metric) metric is considered, which evaluates the distortion in the transmitted video caused by the passage of network packets through the cable line of the transmission system (decoding errors or coding errors), as well as methods for subjective and objective evaluation of images in video conferencing. The advantages and disadvantages of each of the evaluation methods are considered.

Quantitative evaluation of sensitive skin by ANTERA 3D® combined with GPSkin Barrier®.

At present, there are many different evaluation methods for sensitive skin, including subjective, semisubjective, and objective evaluation. Various objective tests focus on assessing changes in barrier functions. It is anticipated that the ANTERA 3D®, in combination with GPSkin Barrier®, will provide better evaluation of sensitive skin. A total of 20 subjects with sensitive skin and 20 healthy participants were recruited. Sensitive skin subjects were treated with an anti-sensitive moisturizing tolerance-extreme cream which has anti-inflammatory and moisturizing effects, twice daily on the whole face for 28 days. VISIA® Skin Detector was used to record clinical images and red area. GPSkin Barrier® was used to measure TEWL and SCH. Texture, hemoglobin, and influenced area (mm2 ) were recorded using ANTERA 3D® . Subjects underwent skin tests and recorded changes at D0 and D28. Data were only collected from healthy participants who did not receive treatment as controls. TEWL, texture, hemoglobin, and affected area in sensitive skin group were significantly higher than those in healthy group, while SCH was significantly lower than that in healthy group (p all<0.05). After anti-inflammatory and moisturizing treatment, the texture, hemoglobin, and affected area of sensitive skin decreased, TEWL decreased while SCH increased (p all<0.05). Based on the results, the combination of the ANTERA 3D® with GPSkin Barrier® could be used as a new kind of quantitative evaluation method for the detection and diagnosis of sensitive skin.

An evaluation model for children’s foot & ankle deformity severity using sparse multi-objective feature selection algorithm

Foot & ankle deformity is a chronic disease with high incidence and is best treated in childhood. However, the current diagnostic procedures rely on doctor’s consultation and empirical judgment, and lack objective and quantitative evaluation methods, resulting in low screening rates. To solve this problem, this paper aims to construct an evaluation model for children’s foot & ankle deformity through data mining and machine learning technologies. Firstly, it proposes the grading rules for children’s foot & ankle deformity severity based on analyzing the existing quantitative indexes and expert experience. Then the 3D foot scanner is used to collect the sample data including 30 foot structure indexes. Finally, an advanced sparse multi-objective evolutionary algorithm (sparse MO-FS) is present for feature selection. The effectiveness of the proposed sparse MO-FS and its search efficiency are proved by comparing 8 feature selection methods and 7 search strategies. Using sparse MO-FS, foot length, arch index, ankle index, and hallux valgus index are selected, which not only simplifies the evaluation model but also improves the average classification accuracy of random forest to more than 98%.

An objective evaluation method for head motion estimation in PET—Motion corrected centroid-of-distribution

Head motion presents a continuing problem in brain PET studies. A wealth of motion correction (MC) algorithms had been proposed in the past, including both hardware-based methods and data-driven methods. However, in most real brain PET studies, in the absence of ground truth or gold standard of motion information, it is challenging to objectively evaluate MC quality. For MC evaluation, image-domain metrics, e.g., standardized uptake value (SUV) change before and after MC are commonly used, but this measure lacks objectivity because 1) other factors, e.g., attenuation correction, scatter correction and parameters used in the reconstruction, will confound MC effectiveness; 2) SUV only reflects final image quality, and it cannot precisely inform when an MC method performed well or poorly during the scan time period; 3) SUV is tracer-dependent and head motion may cause increases or decreases in SUV for different tracers, so evaluating MC effectiveness is complicated. Here, we present a new algorithm, i.e., motion corrected centroid-of-distribution (MCCOD) to perform objective quality control for measured or estimated rigid motion information. MCCOD is a three-dimensional surrogate trace of the center of tracer distribution after performing rigid MC using the existing motion information. MCCOD is used to inform whether the motion information is accurate, using the PET raw data only, i.e., without PET image reconstruction, where inaccurate motion information typically leads to abrupt changes in the MCCOD trace. MCCOD was validated using simulation studies and was tested on real studies acquired from both time-of-flight (TOF) and non-TOF scanners. A deep learning-based brain mask segmentation was implemented, which is shown to be necessary for non-TOF MCCOD generation. MCCOD is shown to be effective in detecting abrupt translation motion errors in slowly varying tracer distribution caused by the motion tracking hardware and can be used to compare different motion estimation methods as well as to improve existing motion information.

A Viability Analysis of Tumor-Bearing Frozen Autograft for the Reconstruction After Resection of Malignant Bone Tumors Using 99m Tc-MDP Scintigraphy.

Several methods are used to reconstruct bony defects after malignant tumor excision. Tumor-bearing frozen autograft reconstruction is a biological procedure in which tumor-bearing bone is reused after devitalization with liquid nitrogen to kill tumor cells. The viability of frozen autografts has not been fully evaluated over time. We therefore aimed to evaluate the viability of devitalized bone grafts, using 99m Tc-MDP scintigraphy. Seventy-four patients who underwent frozen autograft reconstruction after the excision of a malignant bone tumor were enrolled. Two hundred forty-two postoperative 99m Tc-MDP scans were reviewed. For a quantitative analysis, the region of interest on the frozen bone segment and a symmetric region of interest on the contralateral normal area were manually set. The radioactive tracer uptake ratio was calculated by dividing the count density of the frozen bone segment by that of the contralateral normal area in each image. An uptake ratio of 0.9 to 1.1 was defined as a normalization of tracer uptake. Normalization of tracer uptake was achieved in 95% to 97% of the cases by 60 months postoperatively, and earlier in the middle zone and peripheral zone in the pedicle freezing group in comparison to the free freezing group (both P = 0.03). Fracture and nonunion was associated with a low uptake ratio, whereas infection was associated with a high uptake ratio before the occurrence of the event. The calculation of the uptake ratio using 99m Tc-MDP scans was an objective and accurate evaluation method. The period to normalization of tracer uptake in the pedicle frozen bone was significantly earlier than that in the free frozen bone. The postoperative complications can be also predicted.

Teaching quality evaluation of China’s network music education APP

ABSTRACT With the advent of the Internet era in recent years, social music education has gradually shifted from the original entity education mode to the mode of entity plus network teaching. No matter for school music education, professional music education or social music education, the teaching quality is the most important evaluation index. This research firstly found out the basic dimensions that accord with the teaching quality required by the three parties, constructing the quality evaluation index system; and then, on the basis of expounding the connotation of each index, it determined the weight of each index by using method of fuzzy analytic hierarchy process, providing ideas and methods for scientific, objective and comprehensive evaluation of the teaching quality of network education APP.

Deep learning-based automated quantification of goblet cell mucus using histological images as a predictor of clinical relapse of ulcerative colitis with endoscopic remission.

Mucin depletion is one of the histological indicators of clinical relapse among patients with ulcerative colitis (UC). Mucin depletion is evaluated semiquantitatively by pathologists using histological images. Therefore, the interobserver concordance is not extremely high, and an objective evaluation method is needed. This study was conducted to demonstrate that our automated quantitative method using a deep learning-based model is useful in predicting the prognosis of patients with UC. Deep learning-based models were trained to detect goblet cell mucus area from whole slide images of biopsy specimens. This study involved 114 patients with UC in endoscopic remission with a partial Mayo score of ≤ 1. Biopsy specimens were collected during colonoscopy, and the ratio of goblet cell mucus area to the epithelial cell and goblet cell mucus area was calculated as goblet cell ratio (GCR). The follow-up time was 12months, and the primary outcome was the relapse rate. Clinical relapse was defined as partial Mayo score of ≥ 3. Sixteen patients (14%) experienced clinical relapse. In the relapsed group, the GCRs of specimens obtained from the cecum, ascending colon, and rectum were significantly lower than those of specimens in the relapse-free group (p = 0.010, p = 0.027, p < 0.01). In the rectum, patients with a GCR of ≤ 12% had a significantly higher relapse rate than those with a GCR of > 12% (45% [10/22] vs. 6.5% [6/92]; p < 0.01). Quantifying goblet cell mucus areas using a deep learning-based model is useful in predicting the clinical relapse in patients with UC in clinical and endoscopic remission.

Connotation and mitigation of polyphenolic astringency in Chinese medicine

Taste is one of the important factors in the design of oral drug preparations. Polyphenols are the secondary metabolites produced in the growth process of Chinese medicine with a variety of physiological activities. However, astringency perceived from polyphenols tastes uncomfortable. As one of the true taste of Chinese medicine, astringency with drying, rough, and wrinkled sensation, seriously affects the texture of Chinese medicine and the compliance of patients. Due to the universality of polyphenolic astringency in Chinese medicine and the weakness of modern research, this study systematically reviewed and summarized the latest research on the mechanism of polyphenolic astringency, the astringency evaluation method, and the astringency-mitigation technology. Through comprehensively analyzing the quantification methods, such as sensory evaluation, animal preference evaluation, chemical evaluation, bionic evaluation, and polyphenol-protein interaction evaluation, the direction of overall astringency assessment with &quot;unified dimension&quot; was proposed. Since the characteristics of Chinese medicine and the mechanism of polyphenolic astringency did not reach a consensus, this study proposed the idea of astringency mitigation suitable for Chinese medicine. This study is intended to deepen the understanding of astringency associated with Chinese medicine, and establish a real and objective astringency evaluation method for Chinese medicine, thus promoting the technique of astringency mitigation of polyphenolic Chinese medicine preparations from trial and error to science.

Objective Evaluation of CT Imaging in the Treatment of Lumbar Disc Herniation.

The value of CT imaging in evaluating the efficacy of percutaneous transforaminal endoscopic discectomy (PTED) in the treatment of lumbar disc herniation (LDH) is explored. A total of 105 patients with LDH admitted to our hospital from March 2018 to September 2019 are selected for treatment with PTED, and all patients undergo CT examination before and after surgery. The CT imaging parameters (CT value of spinal canal soft tissue shadow, maximum back shift distance, longitudinal axis length, and intervertebral space height) before and 1 week after operation, the Japanese Orthopaedic Association (JOA) scores before and 6 months after the operation are compared, and the excellent and good rate of the operation effect is calculated. The correlation between JOA score and CT imaging parameters are analyzed by Pearson correlation method. The experimental results prove that PTED is effective in treating LDH. CT imaging can quantitatively measure the data of herniated intervertebral discs to clarify the recovery of the compressed dural sac and nerve roots, and the results are highly consistent with JOA score, which can be used as PTED objective evaluation method for the treatment of LDH.

GA-GDEMATEL: A Novel Approach to Optimize Recruitment and Personnel Selection Problems

The complexity of human resource management (HRM) requires an integrated method of subjective and objective evaluation rather than intuitive decisions such as multicriteria decision-making (MCDM). This study proposes a hybrid Genetic Algorithm and Decision-Making Trial and Evaluation Laboratory (GA-GDEMATEL)-based grey theory systems approach to solve personnel selection problems in a real-case study from a Vietnamese agriculture manufacturing and services corporation. First, the GDEMATEL approach is deployed to investigate the causal relationship between the proposed criteria and determine the subjective weights of recruitment criteria. Second, the GA model utilizes selection, crossover, and mutation with a new objective function of Minimizing Distance to Ideal Solution (MDIS) to find the optimal solution for robust recruitment based on GDEMATEL weights. Notably, the GA-GDEMATEL could be exploited effectively in a short time to optimize personnel selection in “deep and wide” aspects. Moreover, the study’s findings on recruiting evaluation and selection problems provide a support model and new research perspectives to the literature and help managers achieve the best solution by dealing with qualitative and quantitative criteria more effectively.

Objective Signal Analysis for Investigating Feasibility of Active Noise Cancellation in Hearing Screening.

With the development of active noise cancellation (ANC) technology, ANC has been used to mitigate the effects of environmental noise on audiometric results. However, objective evaluation methods supporting the accuracy of audiometry for ANC exposure to different levels of noise have not been reported. Accordingly, the audio characteristics of three different ANC headphone models were quantified under different noise conditions and the feasibility of ANC in noisy environments was investigated. Steady (pink noise) and non-steady noise (cafeteria babble noise) were used to simulate noisy environments. We compared the integrity of pure-tone signals obtained from three different ANC headphone models after processing under different noise scenarios and analyzed the degree of ANC signal correlation based on the Pearson correlation coefficient compared to pure-tone signals in quiet. The objective signal correlation results were compared with audiometric screening results to confirm the correspondence. Results revealed that ANC helped mitigate the effects of environmental noise on the measured signal and the combined ANC headset model retained the highest signal integrity. The degree of signal correlation was used as a confidence indicator for the accuracy of hearing screening in noise results. It was found that the ANC technique can be further improved for more complex noisy environments.

Emotionally Intelligent Chatbots: A Systematic Literature Review

Conversational technologies are transforming the landscape of human-machine interaction. Chatbots are increasingly being used in several domains to substitute human agents in performing tasks, answering questions, giving advice, and providing social and emotional support. Therefore, improving user satisfaction with these technologies is imperative for their successful integration. Researchers are leveraging Artificial Intelligence (AI) and Natural Language Processing (NLP) techniques to impart emotional intelligence capabilities in chatbots. This study provides a systematic review of research on developing emotionally intelligent chatbots. We employ a systematic approach to gather and analyze 42 articles published in the last decade. The review is aimed at providing a comprehensive analysis of past research to discover the problems addressed, the techniques used, and the evaluation measures employed by studies in embedding emotion in chatbot conversations. The study’s findings reveal that most studies are based on an open-domain generative chatbot architecture. Researchers mainly address the issue of accurately detecting the user’s emotion and generating emotionally relevant responses. Nearly 57% of the studies use an enhanced Seq2Seq encoding and decoding of the input of the conversational model. Almost all the studies use both the automatic and manual evaluation measures to evaluate the chatbots, with the BLEU measure being the most popular method for objective evaluation.

Magnetoencephalographic evaluation of repaired lip sensation in patients with cleft lip.

BackgroundCleft lip is the most common congenital anomaly worldwide. Nevertheless, lip somatosensory characteristics of patients with cleft lip after cheiloplasty have not yet been determined. The present study used magnetoencephalography to objectively evaluate the lip sensation in patients with unilateral cleft lip to establish a new objective evaluation method.MethodsParticipants were 15 patients with unilateral cleft lip after cheiloplasty (UCL group), and 30 healthy young subjects (control group). Five points of the upper and lower lips were stimulated electrically to measure somatosensory evoked magnetic fields (SEFs). The sources of the magnetic fields were modeled as single equivalent current dipoles (ECDs). ECDs located on the central sulcus by superimposition on magnetic resonance images were analyzed. Latency and intensity at 50–75 ms (cP60m) observed in the UCL group were compared with those in the control group. Thresholds of tactile stimuli in both groups were obtained using Semmes–Weinstein monofilaments for subjective sensory evaluation.ResultsNo significant difference was found in the intensity of the cP60m or subjective evaluation between the groups. However, the latency of the cP60m was significantly longer in the upper lip of the UCL group than in the control group.ConclusionsSEFs showed a difference in lip sensation between the UCL group and the control group, suggesting that longer latency might be caused by the effects of surgical scarring on the neurotransmission pathway. These results suggest SEFs as useful for the objective evaluation of lip sensations. This study might improve future surgical procedures and lip functions of patients with cleft lip.