Miracle-dz/UniFAR-FTUs huggingface dataset:
Sensitivity of methane emissions from wetlands to atmospheric impact in permafrost-covered regions

Model of methane emissions from wetlands [1] is implemented to the dynamic model of thermoand hydrological processes in soil [2]. Simulations with the combined model are performed for the 21 century forced by atmospheric impact from the ensemble of climate models: ECHAM5/MPI-OM, CCCMA-CGCM3, GISS-AOM, IPSL-CM4, and INM CM3. Simulations are analyzed for the region 65-70°N, 150-160°E in Eastern Siberia. Simulated thaw depths for that region rise by 0.4 m during the 21st century (Fig.1a). On average, simulated methane emissions ECH4 for that region increase from 1000 mgCH4/m/yr for the early 21st century to 2000 mgCH4/m/yr to the end of the century (Fig.1b). According to observational estimates [3], ECH4 equals to 250 mgCH4/m/yr for that region. In the climate model of intermediate complexity of the A.M. Obukhov Institute of Atmospheric Physics RAS (IAP RAS CM), methane emissions for the analyzed region increase from 120 to 930 mgCH4/m/yr during the 21st century [4]. Estimations of methane emissions obtained for ensemble of models show notable scatter, intermodal differences may be as large as 6000 mgCH4/m. To assess the sensitivity of combined model to input parameters a set of average parameters was constructed for selected site (65°N, 155°E). Simulations of methane emissions are performed for this site with climate forcing from the ensemble of models along with mean model forcing (Fig. 2). Also multiple simulations were made with the input from this “mean” model, when one of input variables is replaced with the same variable from one of the climate models (Table 1). It appears that the combined soil-methane emission model is most sensitive to the temperature at the surface. This work was supported by the Russian Foundation for Basic Research, by the programs of the Russian Academy of Sciences, and by the Russian President scientific grant.
The Effect of Organisational Climate on Eマヮノラ┞WWゲげ CヴW;デキ┗W Performance through Knowledge Sharing Behaviour

Malaysia has achieved significant industrial growth over the years due to the enterprising intervention of multinational companies (MNCs). The organisational climate in terms of its collaborative nature and innovative efforts has led to the enhancement of creativity among MNCs. The extent of knowledge sharing behaviour within MNCs, particularly in the Malaysian context, has not been thoroughly researched. A huge primary survey involving 20 MNCs with 155 respondents from both manufacturing and service sectors was included in this study. The findings of the study reveal that knowledge donating and knowledge collecting highly and positively influence creative performance. Interestingly, knowledge collecting mediates the relationship between an innovative climate and creative performance while a collaborative climate was found to highly and positively influence MNCsげ creative performance through knowledge donating. Thus, knowledge sharing behaviour is pivotal for the success of MNCs in terms of generating new ideas, promoting best practices, continuously improving and reducing the redundancy cost of learning to facilitate organisational effectiveness.
GREEN PRODUCT QUALITY, GREEN CORPORATE IMAGE, GREEN CUSTOMER SATISFACTION, DAN GREEN CUSTOMER LOYALTY THE BODY SHOP DI SURABAYA

Penelitian ini bertujuan untuk menguji Green Product Quality , Green Corporate Image, Green Customer Satisfaction, dan Green Customer Loyalty The Body Shop di Surabaya. Penelitian ini menggunakan pendekatan kuantitatif dengan model SEM (Structural Equation Modeling). Jumlah sampel yang digunakan dalam penelitian ini sebanyak 150 responden. Temuan penelitian menunjukkan bahwa Green Product Quality dan Green Corporate Image berpengaruh positif signifikan terhadap Green Customer Satisfaction, dan Green Customer Satisfaction berpengaruh positif signifikan terhadap Green Customer Loyalty The Body Shop di Surabaya. Sedangkan, Green Product Quality dan Green Corporate Image tidak berpengaruh signifikan terhadap Green Customer Loyalty The Body Shop di Surabaya secara langsung.
IPOMOEA PLATENSIS – MULTIPLICATION OF A NEW ORNAMENTAL SPECIES IN ROMANIA

The Ipomoea platensis species belongs to the Convolvulaceae family. It grows as a wine and is widespread in tropical and subtropical areas. This morning glory is a caudiciform species, with tuberous roots, which also grow on the surface of the soil, thus having a good resistance to drought. In Romania’s climatic conditions this species is flowering if fertilized but the capsule (bud) aborts usually before seed maturation, therefore the vegetative propagation is the only way to multiply it. In this research we investigated its optimum vegetative multiplication (ex vivo and in vitro). For ex vivo multiplication the best results were obtained using tap water without growth hormones. For in vitro multiplication we used nodal segments and leaf fragments. The nodal segments used as explant produced shoots, while the leaf fragments developed only callus. The explants were placed on MS medium containing cytokinines (BAP, KIN and TDZ) and auxins (IAA and IBA) in different concentrations. Optimal proliferation was observed when shoots were cultivated on MS medium supplemented with 0.5 mg/l IBA and 0.2 mg/l KIN. The concentration and type of cytokinine had an influence on the multiplication of I. platensis species, from nodal segments. Thus, Kinetin in 0.2 mg/l concentration induces the formation of a higher number of shoots compared to the cytokinines BAP in 0.3 mg/l and TDZ in 0.1 mg/l concentration. Consequently, the easiest way to multiply this species is ex vivo, but the highest ratio of multiplication is obtained in vitro, from nodal segments.
A comparison of VLSI, MCM and WSI technologies

VLSI, MCM and WSI technologies are compared on the basis of silicon area, substrate size and power consumption. Theoretical estimates for these parameters are developed and then illustrated by examining the design of a radix-4 FFT butterfly processing element. The MCM implementation should cost the least in production, but it is the largest and consumes the most power.
Impacts of transboundary smoke haze from biomass burning in lower Southeast Asia on air quality in Southern Thailand

This study investigated the impact of transboundary smoke haze from Indonesia on air quality in Southern Thailand, with focus on Songkhla and Phuket provinces. Long-term PM10 (particulate matter whose size is no larger than 10 μm) and visibility data were considered. It was found that elevated PM10 tends to occur in the haze-prone period (May-November) and be more induced in strong El Nino years (here, 1997 and 2015), with PM10 degradation at Songkhla being more pronounced than at Phuket. The seasonality of monthly mean PM10 and VISd is not as apparent as that of the high-end and low-end percentiles respectively, suggesting a high degree of episodicity for the PM10 problem. Elevated PM10 episodes at Songkhla and Phuket were identified by examining daily PM10 time series. Kinematic back-trajectory results simulated for individual elevated PM10 episodes during the haze-prone period (42 and 4 episodes at Songkhla and Phuket, respectively) show that the majority of the episodes (63% at Songkhla and 100% at Phuket) have back-trajectories passing over fire cluster(s) located in Sumatra or Borneo and often associated with the warm (El Nino) or neutral phases of the El Nino-Southern Oscillation or ENSO. This evidently affirms the potential transboundary smoke haze from biomass burning in Indonesia, which induces elevated PM10 in Southern Thailand.
Performance Evaluation of Up-flow Anaerobic Sludge Blanket Reactor and Aerobic Digestor of Raj Brewery, Bhairahawa, Nepal

Large amount of wastewater is produced from brewery plants which must be treated before discharging into the environment. This research aims to study the chemical oxygen demand removal efficiency of the UASB technology and the aerobic digestor and estimate the biomethane potential that could be generated from the brewery wastewater by using UASB reactor. During the study, it was found that an average of 11.0 Nm3 methane was generated daily by the UASB plant at 48 hours hydraulic retention time and at volumetric loading rate of 84 m3. The methane yield was found to be around 0.14-0.16 m3/kg COD removed. The chemical oxygen demand (COD) value at the influent ranged from 165 to 3950 mg/l and the COD value at the effluent ranged from 121 to 2230 mg/l after digestion in the UASB reactor. During the observation period, the overall efficiency of the UASB reactor in terms of COD removal was found to be 52.5%. The efficiency of the UASB reactor in terms of COD removal fluctuated from 4% to 83.64 %. The concentration of volatile fatty acid (VFA) was found to range from 85.71 to 874.28 mg/l. The alkalinity was found to range from 575 to 872 mg/l. The VFA to alkalinity ratio was found to range from 0.14 to 2.46. The VFA/ alkalinity ratio was found comparatively higher during observation period, which hindered the operation of plant at optimal level. The COD removal efficiency of the aerobic treatment plant ranged from 22 % to 95 % during the observation period the average efficiency was found to be 78.5%. The average pH, BOD, COD and TSS value of treated wastewater from the effluent treatment plant were found to be 7.82, 37.94 mg/l, 100.93 mg/l and 21.33 mg/l respectively and within the disposal guidelines set by Government of Nepal. UASB technology appears to be environmentally friendly and promising technology for treating brewery wastewater, which produces large amount of wastewater and contains high organic materials.
Risk Management and Combinatorial Optimization for Large-Scale Demand Response and Renewable Energy Integration

To decarbonize the electric power grid, there have been increased efforts to utilize clean renewable energy sources, as well as demand-side resources such as electric loads. This utilization is challenging because of uncertain renewable generation and inelastic demand. Furthermore, the interdependencies between system states of power networks or interconnected loads complicate several decision-making problems. Growing interactions between power and energy systems and human agents with advances in sensing, computing and communication technologies also increase the need for personalized operations.In this dissertation, we present three control and optimization tools to help to overcome these challenges and improve the sustainability of electric power systems. The first tool is a new dynamic contract approach for direct load control that can manage the financial risks of utilities and customers, where the risks are generated by uncertain renewable generation. The key feature of the proposed contract method is its risk-limiting capability, which is achieved by formulating the contract design problem as mean-variance constrained risk-sensitive control. To design a globally optimal contract, we develop a dynamic programming solution method based on a novel dynamical system approach to track and limit risks. The performance of the proposed contract framework is demonstrated using data from the Electricity Reliability Council of Texas. The second tool is developed for combinatorial decision-making under system interdependencies, which are inherent in interconnected loads and power networks. For such decision-making problems, which can be formulated as optimization of combinatorial dynamical systems, we develop a linear approximation method that is scalable and has a provable suboptimality bound. The performance of the approximation algorithm is illustrated in ON/OFF control of interconnected supermarket refrigeration systems. The last tool seeks to provide a personalized control mechanism for electric loads, which can play an important role in demand-side management. We integrate Gaussian progress regression into a model predictive control framework to learn the customer's preference online and automatically customize the controller of electric loads that directly affect the customer's comfort. Finally, we discuss several future research directions in the operation of sustainable cyber-physical systems, including a unified risk management framework for electricity markets, a selective optimal control mechanism for resilient power grids, and contract-based modular management of cyber-physical infrastructure networks.
Analysis and modelling of circulating current in two parallel-connected inverters

Parallel-connected inverters are gaining attention for high power applications because of the limited power handling capability of the power modules. Moreover, the parallel-connected inverters may have low total harmonic distortion of the ac current if they are operated with the interleaved pulse-width modulation (PWM). However, the interleaved PWM causes a circulating current between the inverters, which in turn causes additional losses. A model describing the dynamics of the circulating current is presented in this study which shows that the circulating current depends on the common-mode voltage. Using this model, the circulating current between two parallel-connected inverters is analysed in this study. The peak and root mean square (rms) values of the normalised circulating current are calculated for different PWM methods, which makes this analysis a valuable tool to design a filter for the circulating current. The peak and rms values of the circulating current are plotted for different PWM methods, and a discontinuous PWM is identified which offers the minimum peak and rms value of the circulating current. Experimental results are presented to verify the analysis.
Effects of ethanolic leave extract of soursop (Annona muricata L.) on human colorectal cancer line: cell viability and in silico study to cyclin d1 protein

Introduction: Colorectal cancer is a pathological transformation of normal colon and rectum epithelial that becomes an abnormal tissue mass, due to the overexpression of cyclin D1 protein that inducing the high proliferation of colorectal cell. Treatment and prevention of colorectal cancer could be done naturally by consuming leave extract of Annona muricata L. (soursop). Soursop is known for many phytochemical components such as alkaloid, annonaceous acetogenin, phenol, and flavonol that serve as an anti-cancer. Method: The research was used HT-29 colorectal cell that given ethanolic leave extract of soursop with 278 μg/mL concentration, 5-Fluorourasil (5-FU) with 88 μg/mL concentration as positive control, solvent control, dan cells control as negative control. The parameters are cell viability with MTT Assay and analysis of molecular docking from ethanolic leave extract of soursop to cyclin D1 protein with molecular operating environment (MOE) 2013.08 software. Result: Percentage of viable HT-29 cell line decrease in accordance with increasing concentration and the lowest percentage of viable cell is 2 x cytotoxicity concentration 50 (CC50) after ethanolic leave extract of soursop treatment (40,4±1,3%) was compared to 5-FU (30,68±0,93%), solvent control (97,2±1,4%), and cells control (100%). Analysis of molecular docking to cyclin D1 protein was obtained N-hexadecanoic acid and phytol molecules that have the lowest free energy (ΔG), i.e 9,7755 kkal/mol and -7,2147 kkal/mol. Conclusion: Ethanolic leave extract of soursop causes decreasing cell viability of HT-29 cell line on 2 x CC50 concentration was compared to 5-FU, solvent control, dan cells control. N-hexadecanoic acid and phytol molecules have ability to inhibit cyclin D1 protein.
Experimental Analysis of Injection Attacks of Various Recommendation Systems using Real Data

Recommendation systems play an important role in modern applications such as Netﬂix, Amazon, and e-commerce applications. Although the research for improving the accuracy of the recommendation system is increasing because of this importance, the risks in the latest recommendation system have not been sufﬁciently studied, and the importance of the recommendation system is increasing, and the attack to the improper system of the recommendation by the posting of the false review becomes a problem. The economic impact of the attack on the recommendation system is very large, and it is said that the purchase number of the item ﬂuctuates by 5 to 9% depending on the increase and decrease of one star for the item evaluated by 5 stages. However, in a simple recommendation system, it is difﬁcult to distinguish between a fake user and a normal user, and an algorithm to prevent attacks is required. In this paper, we focus on “injection attacks” among attacks on recommendation systems. An overview of the injection attack is shown in Figure 1. In the injection attack, an attacker creates a proﬁle of a fake user from the data and injects it into a data set, and the data set is learned by the recommendation system. Learning without knowing the attack affects the recommendation function, and there is a risk of recommending different items. Although various studies have been conducted to verify the characteristics of such attacks, in the process of creating false data, the effects of optimization algorithms on attack performance have not been well studied. In this paper. In this paper, we investigate the attack performance of Bi-Level Optimization.
Adult life-course trajectories of psychological distress and economic outcomes in midlife during the COVID-19 pandemic

This study used two British birth cohorts to examine whether pre-pandemic trajectories of psychological distress were associated with a greater risk of changes in financial and employment situation during the pandemic, as well as increased need for government support and use of other methods to mitigate their economic situation. We identified 5 differential life-course trajectories of psychological distress from adolescence to midlife and explored their relation to changes in financial and employment circumstances at different stages during the pandemic from May 2020 to March 2021, applying multinomial logistic regression and controlling for numerous early life covariates. In addition, we ran modified Poisson models with robust standard errors to identify whether different trajectories were more likely to have been supported by the benefit system, payment holidays, borrowing and other methods of mitigating the economic shock. We found that despite the UK governments economic response package economic inequalities for pre-pandemic psychological distress trajectories with differential onset, severity and chronicity across the life-course were exacerbated by the COVID-19 economic shock. Furthermore, the subsequent cut in government support, alongside increases in the cost of living may widen economic inequalities for differential pre-pandemic psychological distress trajectories, which in turn may also worsen mental health. This work highlights, different pre-pandemic trajectories of psychological distress were more vulnerable to economic shock.
Microarray-Based Detection of Antibodies against SARS-CoV-2 Proteins, Common Respiratory Viruses and Type I Interferons

A microarray-based assay to detect IgG and IgM antibodies against betacoronaviruses (SARS-CoV-2, SARS, MERS, OC43, and HKU1), other respiratory viruses and type I interferons (IFN-Is) was developed. This multiplex assay was applied to track antibody cross-reactivity due to previous contact with similar viruses and to identify antibodies against IFN-Is as the markers for severe COVID-19. In total, 278 serum samples from convalescent plasma donors, COVID-19 pa-tients in the intensive care unit (ICU) and patients who recovered from mild/moderate COVID-19, vaccine recipients, prepandemic and pandemic patients with autoimmune endocrine disorders, and a heterogeneous prepandemic cohort including healthy individuals and chronically ill patients were analyzed. The anti-SARS-CoV-2 microarray results agreed well with the ELISA results. Regarding ICU patients, autoantibodies against IFN-Is were detected in 10.5% of samples, and 10.5% of samples were found to simultaneously contain IgM antibodies against more than two different viruses. Cross-reactivity between IgG against the SARS-CoV-2 nucleocapsid and IgG against the OC43 and HKU1 spike proteins was observed, resulting in positive signals for the SARS-CoV-2 nucleocapsid in prepandemic samples from patients with autoimmune endocrine disorders. The presence of IgG against the SARS-CoV-2 nucleocapsid in the absence of IgG against the SARS-CoV-2 spike RBD should be interpreted with caution.
Searching Locally and Globally Applying

Daniel A. Levinthal has made several important contributions to the fields of strategy and management. His research has been pivotal in enhancing our understanding of interactions between the internal and external contexts that organizations face as well as the roles of experience, search, and learning processes. Despite substantial overlap between the core issues in international business (IB) and Levinthal’s work, the IB field has yet to fully embrace key tenets of his research. We aim to bridge this gap by providing a number of concrete suggestions for areas in which IB research may benefit from Levinthal’s work and vice versa.
Robust attitude control of micro-satellite based on Generation Adversarial Networks fault detection and Cerebellar Model Articulation Controller fault tolerant control

This paper proposes a new robust attitude control architecture for microsatellites. Based on deep learning fault detection method, Cerebellar Model Articulation Controller (CMAC) is used as fault-tolerant control. Using the image recognition function of Generation Adversarial Networks (GAN), the microsatellite actuator fault wavelet spectrum is used as the basis of training generator and discriminator for real-time fault diagnosis and classification. When the system fault diagnosis determines that the fault occurs, the cerebellar neural network participates in the fault-tolerant control. Using the Gan learning ability of generating confrontation network, the problems of insufficient sample data and insufficient sample labeling are solved respectively. As a kind of local learning network, CMAC has the advantages of strong generalization ability, fast convergence speed and simple hardware and software implementation. The simulation results show that, compared with the traditional methods, the fault detection and fault-tolerant control of GAN method combined with CMAC has higher accuracy and robustness.
A low‐cost passive optical network for television broadcasting and high‐speed bidirectional communications in intelligent buildings

Abstract In this paper, a low‐cost passive optical network scheme is presented for intelligent buildings located in areas having difficulty with wireless signal reception. The network can simultaneously broadcast digital‐video‐broadcasting‐terrestrial (DVB‐T) signals and can transmit high‐speed data bidirectionally using a Fabry‐Pérot laser diode (FP‐LD) injection‐locked by a vertical cavity surface‐emitting laser (VCSEL). Results are shown for the broadcast of DVB‐T signals over an 1‐km multimode fiber (MMF) and for non‐return‐to‐zero (NRZ) data over a 25‐km single mode fiber (SMF). Downstream and upstream transmission bit rates are 10 Gbps and 1.25 Gbps, respectively. Maintaining TV signal quality at 40%, receiver sensitivities are ‐20.2 dBm and ‐22.58 dBm for downstream and upstream transmissions, respectively. In addition, the constraint of injection‐locking and the limitation of optical power are also analyzed.