Physical Inspection Research Articles

Multi-site calibration of hydrological model and the response of water balance components to land use land cover change in a rift valley Lake Basin in Ethiopia

This study aims to perform multi-site calibration and validation of SWAT model using streamflow data, and investigating the responses of water balance components to land use land cover (LULC) change in the Gidabo river sub-basin of rift valley lake basin in southern part of Ethiopia. SUFI-2 algorithm embedded in the SWAT-CUP was employed for sensitivity analysis, calibration, and validation on a monthly basis. The 17 years (1990–2006) streamflow data for three (Aposto, Bedessa, and Measso) gauging stations were used for calibrating the model while 8 years (2007–2014) streamflow data was used for validating the model. The calibrated and validated SWAT model was then used to investigate the response of water balance components to LULC change for three periods (1990, 2005, and 2019) which were performed using ERDAS Imagine 2014 with a maximum likelihood classifier. The most common statistical model performance evaluation indices namely Coefficient of Determination (R2), Nash-Sutcliffe Efficiency (NSE), and Percent Bias (PBIAS) were used to evaluate performance of the SWAT model in simulating sub-basin hydrology; in addition to physical inspection of observed and simulated streamflow hydrograph. The findings of the multi-site model performance evaluation indicated that the values of R2 ranged from 0.80 to 0.64 and 0.74 to 0.72 during calibration and validation periods respectively. The values of NSE ranged from 0.74 to 0.61 and 0.71 to 0.65 during calibration and validation periods respectively whereas PBIAS ranged from 19.70 to -3.20 and 18.10 to 0.80 during calibration and validation periods respectively. The calibration and validation results indicated that the SWAT model would simulate fairly well the historical streamflow at three gauging stations. The mean annual streamflow response to LULC change for the periods 1990–2005 and 2005–2019 was observed to increase by 2.13% (1.16m3/s) and 3.62% (2.04m3/s), respectively and the mean seasonal streamflow was obtained to increase during wet season (April-September) while decreasing trend was observed during dry season (October-March) in all three gauged stations. Results also revealed that there were significant spatiotemporal variations of surface runoff, groundwater flow, lateral flow, and evapotranspiration in the sub-basin. The multi-site calibration and validation together with uncertainty analysis detects spatial variability and simulates the water balance components under changing LULC, which is paramount importance for planning and formulating appropriate integrated land and water resources management and development strategies in the rift valley lake basin of Gidabo river sub-basin in Ethiopia.

Investigating Surface Fractures and Materials Behavior of Cultural Heritage Buildings Based on the Attribute Information of Point Clouds Stored in the TLS Dataset

To date, the potential development of 3D laser scanning has enabled the capture of high-quality and high-precision reality-based datasets for both research and industry. In particular, Terrestrial Laser Scanning (TLS) technology has played a key role in the documentation of cultural heritage. In the existing literature, the geometric properties of point clouds are still the main focus for 3D reconstruction, while the surface performance of the dataset is of less interest due to the partial and limited analysis performed by certain disciplines. As a consequence, geometric defects on surface datasets are often identified when visible through physical inspection. In response to that, this study presents an integrated approach for investigating the materials behavior of heritage building surfaces by making use of attribute point cloud information (i.e., XYZ, RGB, reflection intensity). To do so, fracture surface analysis and material properties are computed to identify vulnerable structures on the existing dataset. This is essential for architects or conservators so that they can assess and prepare preventive measures to minimize microclimatic impacts on the buildings.

Purchase and sale and prohibition of uncertainty (gharar) in the Islamic tradition

The article deals with the requirements of Islamic law to the classical contract of sale. The authors conclude that the prescriptions regarding the conclusion of a contract of sale, the object of sale and price formation are largely explained by the attraction of Islam to fairness in trade. Analyzing the object of sale, the authors refer to the concept of property al-mal and its forms — al-‘ayn property and al-dayn property. They insist that al-dayn is not an analogue of “obligation”, “debt” or “right of claim” in the civilian or common law’s traditions, but a unique concept of Islamic law, literally meaning “property-in-the-future”. Considering limitations to sale of aldayn property, this article presents the approaches of madhhabs regarding the admissibility of and conditions for the sale and purchase of bay’ al-dayn. The basic tool of Islamic law on its way to a sustainable trade turnover is the prohibition of transactions involving excessive uncertainty gharar. The authors reveal the meaning of this concept, which has been widely discussed among Muslim scholars, and distinguish the notion of gharar from the notions of risk and gambling maysīr. Application of gharar prohibition to the contract of sale has its own characteristics and gharar becomes key point in deciding whether it is admissible to sell a non-existent thing — bai‘ al-ma‘dum and sell a thing that is not available for physical inspection at the time of the transaction — bai‘ al-ghayb. In this context, the authors pay attention to the distance sale of goods by preliminary inspection, by sample and by description. Islamic law offers an effective mechanism for removing the uncertainty gharar from the contract of sale, giving the buyer the right of khiyar al-ru’yah, which is the right to unilaterally withdraw from the contract at the moment of physical inspection of the goods.

Virtual Metrology in Semiconductor Fabrication Foundry Using Deep Learning Neural Networks

Physical metrology inspections are crucial in semiconductor fabrication foundry to ensure wafers are fabricated within the production specification limits and prevent faulty wafers from being shipped and installed in customers’ devices. However, it is not possible to examine every wafer as such inspection would incur impractical cost on manpower, finances, and production cycle time (CT) of fabrication foundries (fabs). Virtual metrology (VM) presents an alternate approach to perform metrology inspection without incurring high costs by using machine learning (ML) models. By leveraging historical equipment and process data, ML models can be calibrated to estimate the targeted metrology variables to estimate the quality of wafers, thereby performing virtual inspection on wafers. Recently, VM researchers begin introducing deep learning (DL) into VM research works to examine its capability. Specifically, the VM researchers experimented on the convolutional neural network (CNN). The targeted metrologies are metrologies of plasma-based processes in both etching and chemical vapor deposition. Initial success has been reported by the VM researchers. While various CNN-based VM models have been proposed plasma-based fabrication processes, it has yet to be experimented in photolithography process. Motivated by the initial successes of CNN in plasma-based processes, this work is an initiative to experiment CNN’s performance in predicting the overlay errors of photolithography process. Using data from a real fab, this work first establishes a baseline using the methodology of a prior work. Then, the prediction results of the proposed CNN model are compared with the baseline. The results showed that CNN is able to further reduce the prediction errors.

Toward Autonomous Physical Security Defenses Using Machine Learning

The sheer increase in interconnected devices, reaching 50 B in 2025, makes it easier for adversaries to have direct access to the target system and perform physical attacks. This risk is exacerbated by the proliferation of Internet-of-Battlefield Things (IoBT) and increased reliance on the use of embedded devices in critical infrastructure and industrial control systems. Existing anti-tamper designs protect against limited forms of attacks and have deterministic tamper responses, which can undermine the availability of systems. Advancements in physical inspection techniques have enabled stealthier attacks. Therefore, there is a pressing need for more intelligent defenses that ensure a longer operational time while keeping up with the expected increase in the capabilities of adversaries. This study proposes to enhance existing physical protection methods by developing an intelligent anti-tamper using machine learning algorithms. It uses an analytic system capable of detecting and classifying multiple types of behaviors (e.g., normal operation conditions, known attack vectors, and anomalous behavior). The system also has a layered response mechanism and recovery scheme, which reduces false alarms and prolongs the operational time. An experimental platform was constructed and used for data collection and machine learning model training. This study also explored the impact of adversarial learning attacks on the proposed system and subsequently developed a countermeasure. The final prototype was capable of recognizing two types of normal operating conditions (sheltered and exposed environments) and four types of physical attacks. It also has adaptive response and recovery mechanisms.

Mangosteen Quality Grading for Export Markets Using Digital Image Processing Techniques

Accurate quality grading of mangosteen to meet the needs of consumers is very important for improving the value of the export business. Mangosteen fruit ripens quickly after harvesting, and shipping transportation time is a critical factor. Traditional grading methods by physical visual inspection result in delays and human-induced errors. This paper proposed an automatic grading system of mangosteen fruit that utilizes image processing techniques. The maturity stage, class, and size of mangosteen for the export market are analyzed. There are seven stages of maturity from stage one through to six and the under the mature stage, four classes (extra class, class B, class C, and non-standard class) and seven sizes (Jumbo through to Mini). Skin color, skin defect areas, completeness of calyx integrity are also considered. The preprocessing steps consisted of noise removal using a median filter and image enhancement using the grey level transformation. A combination of the mean intensity of red and green images was used to classify the maturation of the fruit. Areas damaged by yellow latex, cracks, and insect pests were extracted, and calyces were counted for class sorting. The length of the diameter was used for size classification. The thresholding, mathematical morphology, and extended minima transform techniques were also used. The average accuracy of the system was 99.54%, with a high accuracy rate for classifying the premium export grades. Results demonstrated that our proposed system was effective and could be used to improve productivity as an accurate and efficient grading method for mangosteen export.

Automatic Open Water Flood Detection from Sentinel-1 Multi-Temporal Imagery

Many technical infrastructure operators manage facilities distributed over large areas. They face the problem of finding out if a flood hit a specific facility located in the open countryside. Physical inspection after every heavy rain is time and personnel consuming, and equipping all facilities with flood detection is expensive. Therefore, methods are being sought to ensure that these facilities are monitored at a minimum cost. One of the possibilities is using remote sensing, especially radar data regularly scanned by satellites. A significant challenge in this area was the launch of Sentinel-1 providing free-of-charge data with adequate spatial resolution and relatively high revisit time. This paper presents a developed automatic processing chain for flood detection in the open landscape from Sentinel-1 data. Flood detection can be started on-demand; however, it mainly focuses on autonomous near real-time monitoring. It is based on a combination of algorithms for multi-temporal change detection and histogram thresholding open-water detection. The solution was validated on five flood events in four European countries by comparing its results with flood delineation derived from reference datasets. Long-term tests were also performed to evaluate the potential for a false positive occurrence. In the statistical classification assessments, the mean value of user accuracy (producer accuracy) for open-water class reached 83% (65%). The developed solution typically provided flooded polygons in the same areas as the reference dataset, but of a smaller size. This fact is mainly attributed to the use of universal sensitivity parameters, independent of the specific location, which ensure almost complete successful suppression of false alarms.

Assessment of the availability of snakebite antivenom in health facilities in Ndola District, Zambia: a cross-sectional study.

Despite snakebite antivenom being included on the WHO list of essential medicines, many parts of the world, especially Africa, lack effective and safe antivenoms. A descriptive, field-based, cross-sectional study was undertaken from August to November 2020 in 40 out of 71 health facilities in Ndola district. Interviews and physical inspection were conducted at each facility. The study revealed that only three (8%) of all the private health facilities had antivenom available at the time of the assessment. Factors significantly associated with antivenom supply included lack of central country supply (90%), lack of demand of the antivenom (55%) and no budget allocation for the antivenom (95%). Despite the high number of notified snakebites within Ndola district, there remains poor availability of snakebite antivenom within the district.

Analysis and investigation of the leakage failure of a casing used in a shale gas well

A casing leaked in a shale gas well during pressure testing. A series of experiments including macroscopic observation, non-destructive inspection, physical and chemical inspection, optical microscope, scanning electron microscope (SEM) and energy dispersive spectrometry techniques (EDS) were carried out to analyze the failure accident. The finite simulation analysis (FEA) method was used to analyze the effect of internal pressure on the defective parts of the casing. Based on the experiment result and manufacturing process investigation, the root cause was obtained. During the casing pipe rolling process, the bolts of size M12 × 60 mm on the balance cylinder of the continuous pipe mill were loosened and dropped onto the pipe. Under the dual action of the roller and the mandrel, the bolts are 'inlaid' inside the casing as a dissimilar metal substance. The bolt head almost occupies the entire wall thickness of the casing, resulting in the remaining wall thickness of the casing being less than 1 mm. The dissimilar metal inside the casing destroys the continuity of the pipe and severely reduces the pressure bearing capacity of the casing. The FEA calculation results show that the equivalent stress at the defect is lower than the yield strength of the pipe body during the factory hydraulic test. While, in the field pressure test, the equivalent stress at the defect is far greater than the yield strength of the casing under the action of axial tension and internal pressure. Therefore, the crack at the defect quickly propagated and penetrated the entire wall thickness of the casing, resulting in leakage. In order to avoid similar accidents, suggestions to prevent such failures are proposed.

An Investigation on the Impact of Digital Revolution and Machine Learning in Supply Chain Management

The machine learning has made it possible to discover various disciplines and patterns of the supply chain management (SCM). The entire industrial world is trying to gain contextual intelligence of machine learning discovering various new disciplines of the supply chain network. Here, the study has highlighted the iterative queries of digital revolution in supply chain. Physical inspection and potential applications have enlisted in the discussion here. The aim of the study is to acquire more knowledge and insight about the digital revolution and machine learning in activating the supply chain. The literary view in this article has illustrated significant role of machine learning addressing digital revolution in reducing the freight costs, enhancing delivery performance and minimizing the challenges in suppliers as the best advantages of supply network. It has processed discussing how machine learning targets the linear collaboration synergies in present day industrial world. Discussion on these factors has given a better understanding about machine learning. The article has been processed with secondary qualitative analysis highlighting the issues with formulation of appropriate themes. The core construction of machine learning is ideally suited offering knowledge into SCM performance which is not available in the prior technologies. Machine learning is offering today to be a new technology with highest efficiency in strengthening the Supply chain. The qualitative approach of this article expresses the power and emphasize its rate of use pointing the measurement in a comprehensive manner. The major purpose is to define the reach of endpoints of machine learning to ensure the highest productivity in SCM. In addition to this, global industrial pace is broadening day by day where the power of machine learning has become more applicable observing the recent trend in global enterprises. This research article is hopeful enough in giving the meaningful view on the topic following all its variables.

Primary biliary cirrhosis associated with myasthenia gravis after postpartum: a case report

BackgroundAutoimmune diseases refers to a class of diseases involving abnormal immune response of human body and tissue damage caused by the dysregulation of autoimmune balance or destruction of immune tolerance. Recent research has revealed that the occurrence of autoimmune diseases is influenced by genetic, hormonal, immunological, and environmental factors. As sex hormone levels change obviously during pregnancy and postpartum, the morbidity and recurrence rate of autoimmune diseases increase during this period.Case presentationA 31-year-old Asian woman was admitted to our hospital for myasthenia gravis and treated with methylprednisolone and pyridostigmine bromide 3 months postpartum. Physical examination and laboratory inspection after admission suggested that the patient had primary biliary cirrhosis. Subsequently, azathioprine was added to the treatment, and the symptoms of both diseases were successfully controlled.ConclusionsThis case exhibits a rare condition of myasthenia gravis combined with primary biliary cirrhosis postpartum. Given the fluctuation of the immune status during the postpartum period, combined autoimmune diseases need to be taken into account when patients develop clinical symptoms of an autoimmune disease. Therefore, detailed physical and laboratory examination can help to prevent the missed diagnosis of these diseases.

Occupational Health and Safety Risks and Hazards among Workers in the Gambian Building Construction Sites: A Mixed-Method Study Design

Background: Providing occupational health and safety (OHS) services to employees has been a global problem for an extended period. A safe workplace should pose no avoidable risk to employees' physical, psychological, or social wellbeing and should provide opportunities for employees to improve and support their health. This study aimed to assess the occupational health and safety risks and hazards among workers at the construction sites in Kombo North District of the Gambia.
 Methods: A mixed-method study design was conducted across construction workers in Kombo North District, West Coast Region of the Gambia. Data was generated using validated OHS risk assessment matrix, structured questionnaires, environmental and physical inspection and key informant interviews. Descriptive statistics, including a composite scoring system, were used to present the results of this study.
 Results: Of the 157 respondents in this study, 98.1% were males, and about one-third of these construction workers were 31-40 years of age. About 46% and 34.4% spent 1-5 and 6-10 years in the construction industry, while about 40.2% of the respondents never been to school. The study revealed that physical risks and hazards in the form of falling from a height, electric shock, etc. were the most common forms compared to other categories such as ergonomics, biological and chemical risks and hazards. There is no reporting system or registry in place across the study sites.
 Conclusion: This study provides evidence that physical hazards reported being the most common across other forms of ergonomics, biological and chemical risk and hazards. There is an urgent need for reactivation and implementation of OHS advocacies, health education, and other preventive strategies to control common workplace risks and hazards in their various forms.

Factors influencing eco-industrial development in Africa: A SWOT analysis of a Tanzanian industrial park

Eco-industrial parks (EIPs) have been proposed as a transformative model for assisting developing countries in upgrading their industrial systems to meet higher global environmental standards while boosting economic competitiveness. However, for many industrial settings, the requisite contextual requirements have yet to be clarified. This paper aims to contribute to filling this gap. It examines the potential of transforming a case study Tanzanian industrial park, an Export Processing Zone (EPZ), into an EIP. The park was assessed against four criteria (roundput, locality, diversity and gradual change) using SWOT (strengths, weaknesses, opportunities, and threats) analysis. The paper draws upon key informant interviews, document reviews and physical site inspection. Findings reveal several strong and weak points of the EPZ, painting a scenario of a zone that is not based on the cycling of resources, does not have a diverse cooperation network arranged locally, and does not rely on the flow of renewables. However, the presence of a park management team, existing synergies, planned synergies and overall national and global development priorities make the park potentially strong as a whole. Our findings underscore the need for deliberate policy interventions. They can be applied to comparable contexts to pinpoint critical areas when planning the interventions.

The Impact Study of Re-Measurement of Fishing Vessels Based at Tumumpa Coastal Fishing Port

Physical inspection of fishing vessels is part of the flow applied by the Directorate General of Capture Fisheries to verify and confirm the congruence of the actual dimension of the fishing vessel with the official document of fishing license. This inspection includes the calculation of the vessel size measured in Gross Tonnage (GT) which determine the amount of fishery retribution paid as Non-Tax State Revenue (PNBP) in the capture fisheries sector. The purpose of this study is to examine the size discrepancy due to mark down practices by re-measurement and to calculate PNBP based on mooring services at Tumumpa Coastal Fishing Port, Manado. A comparison method using a t-test is applied to investigate the difference between two measurements. Based on the test, there is a significant difference between written and actual measurements of GT which affects PNBP.
 Keywords: GT, PNBP, re-measurement, mark down, Tumumpa Coastal Fishing Port.

Integrating Unmanned Aircraft Systems into State Department of Transportation Highway Bridge Inspection Procedures: Challenges, Implications, and Lessons Learned

Rapid proliferation of small, unmanned aircraft systems (UAS) promises to revolutionize traditional methods used to carry out civil engineering surveys and analyses and conduct physical infrastructure inspections. One of the most promising areas of implementation of innovative UAS technology includes the integration of UAS into current state Department of Transportation (DOT) bridge inspections. While regular bridge inspections are paramount for road user safety, many traditional inspection methods and procedures are cumbersome, expensive, and time consuming; present significant hazards to both the traveling public and the inspection personnel; and are disruptive to normal operations of the transportation facilities. The results of recent studies indicate that UAS can serve as a useful tool in many highway bridge inspection procedures, while significantly reducing costs and time and improving safety. The major factors that affect the success of integrating UAS into the bridge inspection process relate to selection of the proper types of UAS platforms and avionics, data collection sensors and processing software, as well as conduct of task-specific pilot training. The paper provides an examination of current standard bridge inspection procedures and protocols currently carried out by state DOTs; an evaluation of state DOT experiences with the integration of UAS technology into bridge inspections; and an assessment of the issues and challenges associated with this technology. It is expected that this paper will be of interest to a wide range of stakeholders representing state and federal governments, academia, and industry.

Medical semiotics in the telemedicine era: The birth of telesemiotics

BackgroundTelemedicine and videoconferencing distance examination are new and growing swiftly. Distance alters the patient-physician diagnostic context interfering with the traditional methods used to collect and interpret medical signs, introducing new constraints and opportunities. This study is an early contribution to the exploration of the changes in medical semiotics introduced by telemedicine. ObjectiveThe main objective is to characterize the impact of telemedicine on medical semiotics and to analyze its consequences on distance medical examination. MethodsOn empirical bases, an inductive reasoning was built on the observation of telemedical practice and personal experience analysis and supported by the research of existing models and literature. ResultsThe impossibility to touch the patient is the main constraint of telemedicine. While history taking and listening to the patient’s symptoms depend on videoconferencing technology, for physical inspection, two main options exist: a helper-mediated physician-patient interaction and a direct physician-patient interaction without third-party intervention. In the latter case, the physician has to rely either on devices and-or on the patient becoming the physician’s hands. This enhances the physician-patient partnership in the diagnostic process increasing the role of communication and means that the diagnostic tests usually performed by the physician need to be transformed to allow self-execution. Paradoxically, modern distance examination imposes a return to classical semiotics and puts the patient at the very core of the examination process through his/her active participation. The live use of connected medical devices and the direct access to computer facilities offer new opportunities for improved signs gathering and synchronous medical collaboration. ConclusionWe define telesemiotics, a special branch of medical semiotics mostly centered on self-performed physical examination, improved physician-patient communication and the use of computer facilities, that needs to become an integral part of medical training. It is hypothesized that the multiplication of empowered patients, actors of their own health, physically and intellectually participating in the diagnostic process, may lead to deep positive public health and societal repercussions.

HISTORY OF NIGERIA LAND USE ACT (AN OVERVIEW)

The 1978 Land Use Act has a provision that vests ownership of Nigerian land in state/public sector management (LUA). Injustice, loss of land market, lack of fairness, transparency, and inaccessibility of land to the urban/rural poor have all plagued the LUA's implementation over the years. As a result, the critiques vary from an insufficient payment of compensation to the State's improper application of the LUA's requirements, as well as the isolation of LG councils and the urban poor in the execution of the LUA. These comments are supported by the physical inspection and contact with stakeholders in the studied area's land rights. These comments are supported by the physical inspection and contact with stakeholders in the studied area's land rights. The LUA has been proven to be too complicated for the average person to understand, to be exceedingly expensive and oppressive, and to be geared toward governmental needs. The study's goal is to examine present methods in public sector land management in Minna, Nigeria's Niger State, and to come up with a feasible and effective solution to the problems. Respect for existing property rights, access to financing markets, and a favorable policy climate are all recommended for success. The fiscal feasibility of the current government's land reform agenda in Nigeria must be considered.

Exploring Small and Medium Scale Manufacturing Firms and Quality Management of Medicinal Material Supply in a Developing Economy: The Ghanaian Perspective

The quality of herbs used to make herbal medicinal products largely influences the safety and effectiveness of these herbal treatments. It is therefore important to investigate the extent to which manufacturers are ensuring the quality supply of herbal medicine used in production of herbal medicine. This study examines how small and medium scale manufacturers assure the quality and continual improvement of the raw materials (raw materials) used for production of medicinal products in a developing economy, the state of Ghana, and the methods used by the company. The study adopted exploratory research design. Using interview quide with open ended questions, data was collected from 88 respondents (small and medium scale manufacturers and their representatives). The data was analysed using NVivo 11. Findings of the study indicated that herbs were collected from the wild (forest), physical inspection of the herbs and best manufacturing practices, good relationship management or collaboration were measures used to promote quality of raw material supply. Also, proper documentation or recording of processes and quality measures do not have much attention or acceptance among Traditional Medicine Practitioners (TMPs).

Novel Face Mask Detection Technique using Machine Learning to control COVID’19 pandemic

The COVID-19 pandemic has been scattering speedily around the world since 2019. Due to this pandemic, human life is becoming increasingly involutes and complex. Many people have died because of this virus. The lack of antiviral drugs is one of the reasons for the spreading of COVID-19 virus. This disease is spreading continuously and easily due to some common mistakes by people, like breathing, coughing and sneezing by infected persons. The main symptom is the normal flu. Therefore, in the present condition, the best precaution for this disease is the face mask, which covers both areas of mouth & nose. According to the government and the World Health Organization, everyone should wear a face mask in busy places like hospitals and marketplaces. In today's environment, it's difficult to tell if someone is wearing a mask or not, and physical inspection is impractical since it adds to labour costs. In this research, we present a mask detector that uses a machine learning facial categorization system to determine whether a person is wearing a mask or not, so that it may be connected to a CCTV system to verify that only persons wearing masks are allowed in.

Efficacy of an Anti-Cellulite Herbal Emgel: A Randomized Clinical Trial.

Cellulite describes unsightly skin overlying subcutaneous fat around thighs and buttocks of post-pubescent females. A herbal ‘emgel’ containing volatile oils and extracts of A traditional Thai herbal compress was tested in a double-blind, placebo-controlled trial with 18 women aged 20–50 year with severe cellulite. Appearance of cellulite (primary outcome), thigh circumferences, skin firmness, and cutaneous blood flow (secondary outcomes) were assessed at baseline, 2, 4, 8 and 12 weeks with a 2-week follow-up. Herbal emgel applied onto the thigh skin twice daily reduced cellulite severity scores in every time point. The score was reduced from 13.4 ± 0.3 (baseline) to 12.1 ± 0.3 (week 2) and 9.9 ± 0.6 (week 12). All secondary outcomes improved with both placebo and herbal emgels suggesting that ingredients in the base-formulation might be responsible. Querying of participants, analysis of their diaries, and physical monthly inspections found no adverse events. The herbal emgel safely improved the appearance of cellulite, while the base emgel may play a role for other endpoints. Further studies on the active constituents and their mechanism of action are needed to further explore these factors.