Community perspectives on the effectiveness of watershed management institutions in the Himalayas

The sustainability of environmental management initiatives,such as watershed management programs,relies on the presence of effective institutions at the watershed level.However,there needs to be more empirical evidence from evaluating the effectiveness of watershed-level institutions.Therefore,this study presents a pioneering effort to evaluate the effectiveness of Nepal’s first watershed conservation committee at the watershed scale,focusing on the case of the Khageri Khola watershed in Central Nepal.The study involved conducting a household survey,key informant interviews,focus group discussions,and field observations to collect and analyze the data.Descriptive analysis,index value calculation,and chi-square statistics were then employed to summarize the results regarding local respondents’perceptions of twelve institutional characteristics,their rationalities,and their association with socio-demographic variables.The results reveal that the watershed conservation committee was perceived as performing well in managing the watershed.Specifically,good interaction,appropriate scale,technical,environmental,social,organizational,and government rationality were perceived as highly effective,with an average index value of less than 0.36.In contrast,clarity of objectives and economic rationality showed moderate effectiveness,with an average index value ranging from 0.36 to 0.65.However,the results suggested that adaptiveness,compliance capacity,and financial rationality merit increased attention,intending to improve their performance.Further,the results showed the association of socio-demographics with respondents’perceptions of various indicators of institutional characteristics and their rationalities.Therefore,the study provides valuable insights for policymakers,researchers,and development practitioners charged with designing sustainable and effective programs and institutions.To enhance the effectiveness and sustainability of watershed management programs,we recommend establishing a policy-guided institutional mechanism at the watershed scale.This mechanism should be based on various institutional characteristics and rationalities and should consider the extant variability in the socio-demographic and topographic characteristics of the watershed.

A HybridManufacturing ProcessMonitoringMethod Using Stacked Gated Recurrent Unit and Random Forest

This study proposed a new real-time manufacturing process monitoring method to monitor and detect process shifts in manufacturing operations.Since real-time production process monitoring is critical in today’s smart manufacturing.The more robust the monitoring model,the more reliable a process is to be under control.In the past,many researchers have developed real-time monitoring methods to detect process shifts early.However,thesemethods have limitations in detecting process shifts as quickly as possible and handling various data volumes and varieties.In this paper,a robust monitoring model combining Gated Recurrent Unit(GRU)and Random Forest(RF)with Real-Time Contrast(RTC)called GRU-RF-RTC was proposed to detect process shifts rapidly.The effectiveness of the proposed GRU-RF-RTC model is first evaluated using multivariate normal and nonnormal distribution datasets.Then,to prove the applicability of the proposed model in a realmanufacturing setting,the model was evaluated using real-world normal and non-normal problems.The results demonstrate that the proposed GRU-RF-RTC outperforms other methods in detecting process shifts quickly with the lowest average out-of-control run length(ARL1)in all synthesis and real-world problems under normal and non-normal cases.The experiment results on real-world problems highlight the significance of the proposed GRU-RF-RTC model in modern manufacturing process monitoring applications.The result reveals that the proposed method improves the shift detection capability by 42.14%in normal and 43.64%in gamma distribution problems.

Involvement of P53 and Bax/Bad triggering apoptosis in thioacetamide-induced hepatic epithelial cells

AIM： Thioacetamide （TAA） has been used in studying liver fibrosis and cirrhosis, however, the mechanisms of TAA-induced apoptosis in liver are still unclear. The hepatic epithelial cell line clone 9 was cultured and treated with TAA to investigate the causes of cell death. METHODS： The cell viability of TAA-induced clone 9 cells was determined using MTT assay. Total cellular GSH in TAA-induced clone 9 cells was measured using a slight modification of the Tietze assay. The activity of caspase 3 in TAA-induced clone 9 cells was monitored by the cleavage of DEVD-p-nitroanaline. TUNEL assay and flow cytometry were applied for the determination of DNA fragmentation and the proportion of apoptosis in TAA- induced clone 9 cells, respectively. The alterations of caspase 3, Bad, Bax and Phospho-P53 contents in TAA- induced clone 9 cells were measured by Western blot. RESULTS： The experimental data indicated that TAA caused rat hepatic epithelial cell line clone 9 cell death in a dose-and time-dependent manner; 60% of the cells died （MTT assay） within 24 h after 100 rag/1 TAA was applied. Apoptotic cell percentage （TUNE1 assay） and caspase 3 activities were highest after 100 rag/1 TAA was added for 8 h. The release of GSH and the elevation in caspase content after TAA treatment resulted in clone 9 cell apoptosis via oxidative stress and a caspasedependent mechanism. The phospho-p53, Bax and Bad protein expressions in clone 9 cells were increased after TAA treatment. CONCLUSION： These results reveal that TAA activates p53, increases caspase 3, Bax and Bad protein contents, perhaps causing the release of cytochrome c from mitochondria and the disintegration of membranes, leading to apoptosis of cells.

Machine learning to relate PM2.5 and PM10 concentrations to outpatient visits for upper respiratory tract infections in Taiwan:A nationwide analysis

AIM To examine the accuracy of machine learning to relate particulate matter(PM) 2.5 and PM10 concentrations to upper respiratory tract infections(URIs).METHODS Daily nationwide and regional outdoor PM2.5 and PM10 concentrations collected over 30 consecutive days obtained from the Taiwan Environment Protection Administration were the inputs for machine learning, using multilayer perceptron(MLP), to relate to the subsequent one-week outpatient visits for URIs. TheURI data were obtained from the Centers for Disease Control datasets in Taiwan between 2009 and 2016. The testing used the middle month dataset of each season(January, April, July and October), and the training used the other months' datasets. The weekly URI cases were classified by tertile as high, moderate, and low volumes.RESULTS Both PM concentrations and URI cases peak in winter and spring. In the nationwide data analysis, MLP machine learning can accurately relate the URI volumes of the elderly(89.05% and 88.32%, respectively) and the overall population(81.75% and 83.21%, respectively) with the PM2.5 and PM10 concentrations. In the regional data analyses, greater accuracy is found for PM2.5 than for PM10 for the elderly, particularly in the Central region(78.10% and 74.45%, respectively), whereas greater accuracy is found for PM10 than for PM2.5 for the overall population, particularly in the Northern region(73.19% and 63.04%, respectively).CONCLUSION Short-term PM2.5 and PM10 concentrations were accurately related to the subsequent occurrence of URIs by using machine learning. Our findings suggested that the effects of PM2.5 and PM10 on URI may differ by age, and the mechanism needs further evaluation.

Chronic hepatitis B, nonalcoholic steatohepatitis and physical fitness of military males: CHIEF study

AIM To investigate the association of chronic hepatitis B and nonalcoholic steatohepatitis with physical fitness in a Taiwan Residents military male cohort.METHODS We made a cross-sectional examination of this association using 3669 young adult military males according to cardiorespiratory fitness and hospitalization events recorded in the Taiwan Armed Forces study. Cases of chronic hepatitis B(n = 121) were defined by personal history and positive detection of hepatitis B surface antigen. Cases of nonalcoholic steatohepatitis(n = 129) were defined by alanine transaminase level > 60 U/L, liver ultrasound finding of steatosis, and absence of viral hepatitis A, B or C infection. All other study participants were defined as unaffected(n = 3419). Physical fitness was evaluated by performance in 3000-m run, 2-min sit-ups, and 2-min push-ups exercises, with all the procedures standardized by a computerized scoring system. Multiple linear regression analysis was used to determine the relationship.RESULTS Chronic hepatitis B negatively correlated with 2-min push-up numbers(β =-2.49, P = 0.019) after adjusting for age, service specialty, body mass index, systolic and diastolic blood pressures, current cigarette smoking, alcohol intake status, serum hemoglobin, and average weekly exercise times. Nonalcoholic steatohepatitis was borderline positively correlated with 3000-m running time(β = 11.96, P = 0.084) and negatively correlated with 2-min sit-up numbers(β =-1.47, P = 0.040). CONCLUSION Chronic hepatitis B viral infection and nonalcoholic steatohepatitis affects different physical performances in young adult military males, and future study should determine the underlying mechanism.

Enhancing Partnership Between Rural Schools and Communities for Geoheritage Conservation—A Case Study of Taiwan

Academics in Taiwan have been working on geo-conservation for 20 years.Numerous studies focus on investigation,assessment,monitoring and education of special scientific important geoheritages. However,few researches have been done on the issues of local stakeholder participation and community development.The authors choose one of the national-level geoheritages,the Lichi Badland

High‑accuracy measurement of Compton scattering in germanium for dark matter searches

Compton scattering with bound electrons contributes to a significant atomic effect in low-momentum transfer,yielding background structures in direct light dark matter searches as well as low-energy rare event experiments.We report the measurement of Compton scattering in low-momentum transfer by implementing a 10-g germanium detector bombarded by a^(137)Cs source with a radioactivity of 8.7 mCi and a scatter photon captured by a cylindrical NaI(Tl)detector.A fully relativistic impulse approximation combined with multi-configuration Dirac–Fock wavefunctions was evaluated,and the scattering function of Geant4 software was replaced by our calculation results.Our measurements show that the Livermore model with the modified scattering function in Geant4 is in good agreement with the experimental data.It is also revealed that atomic many-body effects significantly influence Compton scattering for low-momentum transfer(sub-keV energy transfer).

An Event Alarm System Based on Single and Group Human Behavior Analysis

Due to the increasing demand for security, the development of intelligent surveillance systems has attracted considerable attention in recent years. This study aims to develop a system that is able to identify whether or not the people need help in a public place. Different from previous work, our work considers not only the behaviors of the target person but also the interaction between him and nearby people. In the paper, we propose an event alarm system which can detect the human behaviors and recognize the happening event through integrating the results generated from the single and group behavior analysis. Several new effective features are proposed in the study. Besides, a mechanism capable of extracting one-to-one and multiple-to-one relations is also developed. Experimental results show that the proposed approach can correctly detect human behaviors and provide the alarm messages when emergency events occur.

Utilization of Swertia chirayita Plant Extracts for Management of Diabetes and Associated Disorders: Present Status, Future Prospects and Limitations

Diabetes mellitus is referred as common metabolic abnormalities characterized as hyperglycemia,mainly caused due to insufficient production of insulin at cellular level or/and defects in insulin action.Such an endocrine disorder is responsible for serious health problems and its worldwide prevalence is rapidly increasing.Common management of diabetes by oral administration of drugs without creating any side effects is still considered a challenging task and increasing cost of con-ventional medicine in developing countries is another matter of concern.To address these issues,traditional preparations of herbal plant extracts in the form of medicines already gained immense attention.Swertia chirayita is one among such plants which is known for its hypoglycemic potential.Numerous chemical constituents with promising pharmacological properties have been identified from such plant extracts but still,such compounds have not been well characterized,specifically against human application.Hence,more research efforts are necessitated to understand exact mechanism of such compounds and to develop overall safety of such plant formulations.Present review clearly represents antidiabetic properties of Swertia chirayita extract,strategies to be taken to strengthen its safety application on humans and biotechnological interventions that ensure conservation of such endangered species to promote its future application in modern medicine.

Object Tracking Using a Particle Filter with SURF Feature

In this paper, a novel object tracking based on a particle filter and speeded up robust feature （SURF） is proposed, which uses both color and SURF features. The SURF feature makes the tracking result more robust. On the other hand, the particle selection can lead to save time. In addition, we also consider the matched particle applicable to calculating the SURF weight. Owing to the color, spatial, and SURF features being adopted, this method is more robust than the traditional color-based appearance model. Experimental results demonstrate the robustness and accurate tracking results with challenging sequences. Besides, the proposed method outperforms other methods during the intersection of similar color and object＇s partial occlusion.

Instance Retrieval Using Region of Interest Based CNN Features

Recently, image representations derived by convolutional neural networks(CNN) have achieved promising performance for instance retrieval, and they outperformthe traditional hand-crafted image features. However, most of existing CNN-based featuresare proposed to describe the entire images, and thus they are less robust to backgroundclutter. This paper proposes a region of interest (RoI)-based deep convolutionalrepresentation for instance retrieval. It first detects the region of interests (RoIs) from animage, and then extracts a set of RoI-based CNN features from the fully-connected layerof CNN. The proposed RoI-based CNN feature describes the patterns of the detected RoIs,so that the visual matching can be implemented at image region-level to effectively identifytarget objects from cluttered backgrounds. Moreover, we test the performance of theproposed RoI-based CNN feature, when it is extracted from different convolutional layersor fully-connected layers. Also, we compare the performance of RoI-based CNN featurewith those of the state-of-the-art CNN features on two instance retrieval benchmarks.Experimental results show that the proposed RoI-based CNN feature provides superiorperformance than the state-of-the-art CNN features for in-stance retrieval.

Inductively Coupling Plasma(ICP) Treatment of Propylene(PP) Surface and Adhesion Improvement

Study on increasing the roughness of the polymer substrate surface to enhance the adhesion with the copper layer in an inductively coupling plasma （ICP） process was carried out. The microstructure of the polymer substrate surfaces, which were exposed to different kinds of plasma treatment, was identified by scanning electron microscopy（SEM） analysis, peel strength of the copper coating and water surface contact angle. The adhesion of the substrate was largely enhanced by plasma treatment and the copper deposited coating reached a value of 7.68 kgf/m in verifying the adhesion of the copper coating with polymer material. The quality of the line/space 50/50 μm produced in the laboratory was examined by the pressure cooker test and proved to meet the requirement.

Construction of General (k, n) Probabilistic Visual Cryptography Scheme

Visual cryptography scheme （VCS） is a secure method that encrypts a secret image by subdividing it into shadow images. Due to the nature of encryption VCS is categorized into two types： the deterministic VCS （DVCS） and the probabilistie VCS （PVCS）. For the DVCS, we use m （known as the pixel expansion） subpixels to represent a secret pixel. The PVCS uses only one subpixel to represent a secret pixel, while the quality of reconstructed image is degraded. A well-known construction of （k, n）-PVCS is obtained from the （k, n）-DVCS. In this paper, we show another construction of （k, n）-PVCS by extending the （k, k）-PVCS.

Technology Sub-diffusions:Consumptive Motivations for Mobile Phone Calls and Digital Services

Digital services interfaced with mobile phone lines are gradually being regarded as a core product in this modern age due to the high transmission speed of mobile technology.The research in this paper is based on the concept of product inter-dependence and actively explores the different consumptive motivations between the consumers' behavior of phone-call users and those who use digital services.This study also attempts to use a modifi ed diffusion model to estimate the consumers' collective behavior with a longitudinal approach.In this study,it can be inferred that psychological consumer motivations should dominate marketing policies.Thus,it was found that digital service users have more self-motivation and autonomy when adopting a new product because they have significantly higher innovative at-tributes than the segment of phone-call users.With these findings,we claim that we have discovered an unprec-edented concept for marketing managers who welcome the challenges of mobile digital services in the future.

A Characterization of Besov Spaces of Para-Accretive Type and Its Application

There are two folds in this article. One fold is to characterize the Besov spaces of para-accretive type , which reduces to the classical Besov spaces when the para-accretive function is constant, by using a discrete Calderón-type reproducing formula and Plancherel-P?lya-type inequality associated to a para-accretive function b in Rn. The other is to show that a generalized singular integral operator T with extends to be bounded from for and , where ε is the regularity exponent of the kernel of T.

Vision-Based Learning Status Monitoring on Color and Depth Live Facial Videos

This study analyzes live facial videos for recognizing nonverbal learning-related facial movements and head poses to discover the learning status of students. First, color and depth facial videos captured by a Kinect are analyzed for face tracking using a three-dimensional （3D） active appearance model （AAM）. Second, the facial feature vector sequences are used to train hidden Markov models （HMMs） to recognize seven learning-related facial movements （smile, blink, frown, shake, nod, yawn, and talk）. The final stage involves the analysis of the facial movement vector sequence to evaluate three status scores （understanding, interaction, and consciousness）, each represents the learning status of a student and is helpful to both teachers and students for improving teaching and learning. Five teaching activities demonstrate that the proposed learning status analysis system promotes the interpersonal communication between teachers and students.

An Entire View on Research Trends in the Technology Evolution of Mobile Telecommunications

＂Without an appropriate research setting, a study cannot be qualified as a reasonable piece＂, this notion is manifested in the methodological polices. In this research, we attempt to examine previous studies within the scope of technology evolution and market perception in telecommunication industry through extracting research structures, methodologies, corresponding variables, and processing methods. A general process of social scientific research is adopted to analyze eighty-four selected papers; and simultaneously, the framework for doing this analysis is established, as well. In this manner, we inspect the subjects and the issues in these papers according to product types, academic domains, and divisions of technological evolution （from 1G to 4G）. Then, their research designs are anatomized into the key dimensions of general research conventions. This research eventually provides an entire picture of a research scenario for mobile telecommunication industry; and apparently, this framewbrk can help scholars to establish specific tendencies for academic scenarios in future research plans. Also, we propose the main streams and emerging issues can be expected to engage in the future within both theacademic and the operational fields.

An Evaluation for the Probability Density of the First Hitting Time

Let h(t) be a smooth function, Bt a standard Brownian motion and th=inf{t;Bt=h(t)} the first hitting time. In this paper, new formulations are derived to evaluate the probability density of the first hitting time. If u(x, t) denotes the density function of x=Bt for t th, then uxx=2ut and u(h(t),t)=0. Moreover, the hitting time density dh(t) is 1/2ux(h(t),t). Applying some partial differential equation techniques, we derive a simple integral equation for dh(t). Two examples are demonstrated in this article.

Near is more:learning efficiency in research and development innovation among interlocking firms

Research question/issue:This study examines whether geographic proximity produces a proximity preference as interlocking firms observe each other and learn innovative behaviors through information transmission among interlocking directors.Research findings/insights:We study the performance of A-share-listed companies in China from 2007 to 2017 on the basis of resource dependence theory,agglomeration effect theory,and Porter’s competitive theory.When target firms learn about research and development–related innovation behaviors from interlocking firms closer to them,they experience more efficient learning effects and have improved convergent traits.Moreover,this proximity advantage increases the willingness of the target firm to communicate with and learn from interlocking firms closer to them.Highly developed areas and research and development–intensive industries positively affect the learning efficiency of interlocking firms.Theoretical/academic implications:Our conclusion is consistent with resource dependence theory;target firms in highly developed areas are more willing to imitate and study nearby interlocking firms to maintain their peer relations,innovation potential,and competitiveness.Our conclusion is also consistent with competition theory,which states that the exchange of information between target firms in highly research and development–intensive industries and distant interlocking firms increases innovation differentiation,innovation potential,and competitiveness,even when such exchange has a high cost.Practitioner/policy implications:The results support resource dependence theory and peers’effects.The information obtained by interlocking directorates through external social relations guides firm decision-making,and closer distances reveal more obvious effects.