Natural compounds are emerging as promising alternatives to conventional hair loss treatments. This review examines various natural ingredients, including green tea (EGCG), pea sprout extract, red ginseng, pumpkin seed oil, rosemary oil, chia seeds, and micronutrients. It summarizes their mechanisms of action, clinical evidence, and safety profiles. These compounds target pathways related to androgenetic alopecia, dihydrotestosterone (DHT), oxidative stress, and inflammation. Clinical and animal studies indicate benefits such as stimulating hair growth, preserving hair follicles, and exhibiting anti-apoptotic and anti-inflammatory effects, with increasing evidence supporting their use among patients with hair loss disorders.

강화학습은 지속적으로 변화하는 환경에서 최적의 해결책을 제시할 수 있도록 구현되는 머신러닝 알고리즘으로 시간 및 조건에 따라 변화하는 시스템의 최적화에 우수한 성능을 보이는 장점을 가지고 있다. 따라서, 최근 운영 조건과 시간에 따라 변화하는 상하수도 시설 및 취수원 등 현장 물환경 관리 최적화에 강화학습을 적용하기 위한 연구에 대한 관심이 높아지고 있다. 본 연구에서는 강화학습이 상하수도 시설 및 물환경 관리에 적용된 사례를 분석하였다. 상하수도 시설의 운영시 시설 운영의 목적에 맞는 처리수 수질을 유지하면서 운영에 필요한 에너지 소비 및 비용을 최소화하는 노력이 중요하다. 강화학습은 데이터에 기반한 반복적인 분석을 통해 시스템 운영의 최적 조건을 학습할 수 있으며, 다양한 연구 사례에서 강화학습의 적용을 통해 상하수도 시설 등의 운영 효율 개선이 가능함을 보여주었다. 하수처리 시설의 경우 강화학습을 활용하여 운영비의 많은 부분을 차지하는 폭기조 산소 공급과 내부 반송 펌프 운전을 최적화할 수 있으며, 정수장의 경우 약품 투입량 절감 등을 통해 운영비 절감 효과를 달성할 수 있음을 확인하였다. 또한, 용수 공급망과 저류조 운영의 최적화를 통해 상수도 및 하천 현장의 오염 발생을 저감할 수 있음을 알 수 있었다. 본 연구를 통해 강화학습을 활용하여 기존의 경험에 기반한 시설 운영 방식의 한계를 개선하고 상하수도 시설 운영 및 물환경 관리 효율 향상에 기여할 수 있음을 확인하였다

While potatoes are a representative crop in Bolivia, their cultivation requires a significant amount of chemical pesticides. Some seed treatment chemicals used for seed potatoes in Bolivia can be highly toxic. Additionally, farmers face financial constraints that make it difficult to use these pesticides. In this paper, we investigated the potential of applying plant ash to seed potatoes as an eco-friendly alternative for seed potato disinfection. We also examined the effects of seed tuber cutting in combination with the ash treatment. The potato variety used was “Jatun Puka,” a new variety developed in Peru that has been studied at the Bolivian National Institute of Agricultural and Forestry Innovation (INIAF). The experiment was conducted using a Randomized Complete Block Design (RCBD) with four repetitions in Sipe Sipe and Sapanani o f Cochab amb a, and Mairana of S anta Cruz. The r esults s howed that the e ffects of the ash treatment and tuber cutting were significantly influenced by the local environment of each region in Bolivia. The ash treatment was more effective than the others only in the Sapanani region, where the soil pH was low enough to fall within the optimal range for potatoes after the ash treatment. Generally, cutting seed potatoes had a negative effect on yield across all three regions, with the negative impact increasing in proportion to the humidity or precipitation of each area. However, considering the cost of seed potatoes per unit area, cutting them remains an adoptable option under certain circumstances. We hope this research will serve as an important reference for future studies on eco-friendly potato cultivation in Bolivia.

The prediction of satisfactory orthodontic treatment outcomes can be very challenging owing to the subjectivity of orthodontists’ judgment, along with the inherent difficulties when considering numerous factors. Therefore, this study introduced a deep learning-based method for predicting orthodontic treatment outcomes based on the image-to-image translation of dental radiographs using the Pix2Pix model. This proposed method addresses the aforementioned issues using a Pix2Pix-based prediction model constructed from adversarial deep learning. Patient datasets and prediction models were separated and developed for extraction and non-extraction treatments, respectively. The patients’ radiographs were pre-processed and standardized for training, testing, and applying the Pix2Pix models by uniformly adjusting the degree of blackness for the region of interest. A comparison of actual with Pix2Pix-predicted images revealed high accuracy, with correlation coefficients of 0.8767 for extraction orthodontic treatments and 0.8686 for non-extraction treatments. The proposed method establishes a robust clinical and practical framework for digital dentistry, offering both quantitative and qualitative insights for orthodontists and patients.

This study analyzes the heterogeneous treatment effects of the COVID-19 pandemic on regional tourism demand in South Korea, focusing on the role of geographic distance from the metropolitan area to tourist destinations and the spatial characteristics of tourist destinations. Since a substantial portion of the population resides in the capital region, it can be expected that regional tourism demand is largely driven by residents of the capital region. In addition, the pandemic has particularly discouraged visits to indoor and densely populated areas due to increased perception of infection risk. To estimate these effects, we use a causal machine learning approach using double machine learning, analyzing monthly visitor data from 994 major tourist sites between the years 2019 and 2020. Tourist destinations are classified by spatial characteristics, including indoor, outdoor, and mixed settings as well as by tourism type. The analysis reveals that the impact of COVID-19 was more pronounced for indoor destinations located closer to the metropolitan center, whereas outdoor and mixed destinations showed little variation in treatment effects by distance. These findings highlight the importance of adopting distance-sensitive and space-specific policy measures in tourism planning during pandemics. Our study also demonstrates the practical utility of causal machine learning in tourism analytics, suggesting its potential for enhancing policy precision and resilience against future public health crises.

This study evaluated the field-scale performance of an amorphous iron hydroxide (Fe(OH)3)-based desulfurizing agent for the removal of sulfur-based odorous compounds emitted from wastewater treatment facilities, including equalization tanks and sludge dewatering unit facilities. Hydrogen sulfide (H2S), methyl mercaptan (MM), dimethyl sulfide (DMS), and dimethyl disulfide (DMDS), which account for over 60~80% of total odor impact in such facilities, were targeted in this research. A drytype adsorption system packed with porous amorphous Fe(OH)3 was installed at a wastewater treatment plant and operated continuously for 45 days. Odorous gas concentrations were measured before and after treatment using portable analyzers and gas chromatography-pulsed flame photometric detector (GC-PFPD). The desulfurizing agent demonstrated a high H2S removal efficiency of over 99.9%, even under high inlet concentrations exceeding 500 ppm. Physicochemical analyses including XRD, XRF, EDS and BET confirmed that the material was amorphous, possessed a high surface area (243.4 m2/g), and exhibited a mesoporous structure favorable for gas adsorption. Hysteresis observed in nitrogen adsorption isotherms indicated a bottleneck-shaped pore structure, which enhances adsorption of odorous gases and removal efficiency. Notably, the system maintained stable performance under varying humidity without significant degradation.

During the operation of Pressurized Heavy Water Reactor (PHWR), corrosion oxide layers are formed on the surface of carbon steel SA 106 Grade B (GR.B), primary coolant system material. These oxide layers can be effectively removed using the common chemical decontaminant, oxalic acid (OA). However, the base metal of the structural material may also undergo corrosion, increasing the concentration of metal ions, such as ferrous ions, in the decontamination solution. The increased concentration of metal ions leads to an increased use of cation exchange resins in wastewater treatment, thereby increasing the amount of secondary wastes. Therefore, minimizing the corrosion of the base metal during chemical decontamination is crucial. In this study, imidazole (IM) and 1-butyl-3-methylimidazolium chloride ([BMIM]Cl) were selected for their effectiveness in reducing carbon steel corrosion in acidic environments. Their efficiency as corrosion inhibitors was evaluated under actual decontamination conditions in OA solution. When [BMIM]Cl was added to OA, the corrosion depth of carbon steel decreased from 0.641 μm to 0.406 μm, and the corrosion rate decreased from 1.924 μm/h to 1.218 μm/h, both representing a reduction of 36.7%. In conclusion, this study suggests that [BMIM]Cl is a good candidate as a corrosion inhibitor to be further evaluated under chemical decontamination process.

활성슬러지 생물반응기 내 핵심 미생물군은 하수처리장에서 미생물 군집이 수행하는 생태학적 역할을 이해하는 데 중요한 기반이 된다. 본 연구에서는 이러한 핵심 미생물군의 생태학적 중요성을 규명하기 위해, 한국과 중국에 위치한 6개의 실규모 하수처리장에서 채취한 총 39개의 시료를 대상으로 고효율 염기서열 분석 기반의 미생물 군집 분석을 수행하였다. 분석 결과, 각각의 하수처리장에서 관찰된 미생물 군집 변동성은 하수처리장 간의 변동성보다 낮은 패치 동역학이 관찰되었다. 이 결과는 핵심 미생물군이 공간적 스케일보다는 시간적 스케일에서 정의될 수 있음을 보여준다. 또한, 미생물의 기능적 동역학을 비교한 결과, 하수처리장 전반에 걸쳐 통계적으로 유사한 기능적 대사경로가 관찰되었으며, 이는 활성슬러지 생물반응기 내 미생물 군집이 분류학적으로 상이하더라도 유사한 기능을 수행하고 있음을 시사한다. 종합적으로, 본 연구는 하수처리장 미생물 군집의 기능적 중복성에 대한 통찰력을 제공한다.