Miracle-dz/UniFAR-FTUs huggingface dataset:
Choosing a Gate Dielectric for Graphene Based Transistors

Much attention has recently been focused on graphene as an alternative semiconductor to silicon. Transistors with graphene conduction channels have only recently been fabricated and their performance remains to be optimized. In this thesis, different candidate gate dielectric materials are examined for use in graphene transistors. Evaporated HfO2 is ultimately used as the gate dielectric for graphene field effect transistors (FETs) on six different graphene samples. Two types of graphene were used: graphene made from the sublimation of SiC and epitaxial graphene synthesized by chemical vapor deposition (CVD) onto nickel. Electrical performance of the graphene transistors were found to vary significantly depending on the local graphene microstructure. The gate dielectric was found to crack on thick regions of graphene but stay intact on thin regions. Dielectric charging resulted in hysteretic effects in device performance. As consistent with HfO2 used in silicon CMOS devices, electron mobilities were lower than hole mobilities in the fabricated graphene FETs. Thesis Supervisor: Jing Kong Title: Assistant Professor, Department of Electrical Engineering and Computer Science Thesis Supervisor: Jakub Kedzierski Title: Assistant Group Leader, MIT Lincoln Laboratory Group 88
Optimizing Rhabdomyosarcoma Treatment in Adolescents and Young Adults

Simple Summary Due to their rarity, we still know comparatively little about rhabdomyosarcomas (RMS) in adolescents and young adults (AYA). Factors responsible for the significantly poor outcomes in AYA-RMS are tumor biology, physiological factors specific to the age group concerned, refractoriness to multimodal treatments, and various psychosocial and medical care issues. The present review aims to examine these issues and offers possible solutions based on integrating new developments and findings with older, fundamental evidence regarding pediatric RMS. Abstract Rhabdomyosarcoma (RMS) is the most common form of soft tissue sarcoma in children, but can also develop in adolescents and young adults (AYA). The mainstay of treatment is multi-agent chemotherapy, ideally with concomitant local treatment, including surgical resection and/or radiation therapy. Although most treatment decisions for RMS in AYA are based on scientific evidence accumulated through clinical studies of pediatric RMS, treatment outcomes are significantly inferior in AYA patients than in children. Factors responsible for the significantly poor outcomes in AYA are tumor biology, the physiology specific to the age group concerned, refractoriness to multimodal treatments, and various psychosocial and medical care issues. The present review aims to examine the various issues involved in the treatment and care of AYA patients with RMS, discuss possible solutions, and provide an overview of the literature on the topic with several observations from the author’s own experience. Clinical trials for RMS in AYA are the best way to develop an optimal treatment. However, a well-designed clinical trial requires a great deal of time and resources, especially when targeting such a rare population. Until clinical trials are designed and implemented, and their findings duly analyzed, we must provide the best possible practice for RMS treatment in AYA patients based on our own expertise in manipulating the dosage schedules of various chemotherapeutic agents and administering local treatments in a manner appropriate for each patient. Precision medicine based on state-of-the-art cancer genomics will also form an integral part of this personalized approach. In the current situation, the only way to realize such a holistic treatment approach is to integrate new developments and findings, such as gene-based diagnostics and treatments, with older, fundamental evidence that can be selectively applied to individual cases.
Evaluation of bactericidal potential and catalytic dye degradation of multiple morphology based chitosan/polyvinylpyrrolidone-doped bismuth oxide nanostructures

In this study, 0.02 and 0.04 wt% of chitosan (CS) were successfully incorporated in a fixed amount of polyvinylpyrrolidone (PVP)-doped Bi2O3 nanostructures (NSs) via a co-precipitation approach. The purpose of this research was to degrade hazardous methylene blue dye and assess antimicrobial potential of the prepared CS/PVP-doped Bi2O3 nanostructures. In addition, optical characteristics, charge recombination rate, elemental composition, phase formation, surface morphology, functional groups, d-spacing, and crystallinity of the obtained nanostructures were investigated. CS/PVP-doped Bi2O3 nanostructures exhibited efficient catalytic activity (measured as 99%) in a neutral medium for dopant-free nanostructures while the inhibition zone was measured using a Vernier caliper against pathogens Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) at low and high doses to check antimicrobial activity. Strong bactericidal action was recorded against S. aureus bacteria such that a significant inhibition zone was measured at 3.09 mm.
Biometric Identification System Based on Contactless Palm-Vein Using Residual Attention Network

Palm vein recognition technology is a one of the most effective biometric technologies for personal identification. Palm acquisition techniques are either contact-based or contactless-based. The contactless-based palm vein system is considered more accurate and efficient when used in modern applications, but it may suffer from problems like pose variations and the delay in the matching process. This paper proposes a contactless-based identification system for palm vein that involves two main steps; First, the central region of the palm is cropped using fast extract region of interest algorithm, then the features are extracted and classified using altered structure of Residual Attention Network, which is a developed version of convolutional neural network that uses an attention mechanism. The altered structure is constructed by stacking multiple attention modules and pre-activation residual unit with additional down sampling layers in between. The proposed system was tested on contactless CASIA multispectral palm vein databases that contains palm images with obvious pose variations taken from 100 persons. The results show that our system has outperformed other state-of-the-art systems with 95.55% accuracy and fast identification process of 0.06 second per person.
VdotO2max as Physical Load Indicator Unit in Forest Work Operation

Most of forestry work has burdened forest workers with heavy workload, which is often exceeding their allowable workload. This workload has been widely measured through energy expenditure-based workload assessment (expressed in kcal/kg/min). However, this calculation method excluded physical characteristic of individual into its calculation, meanwhile it may greatly influenced metabolism system of an individual. Thus, there is a big possibility that the use of kcal/kg/min workload unit in comparing workload among different individuals conducting the same physical work had ended in an erroneous reading. Therefore, a study on alternative workload measurement that provides a fair assessment when the assessment is conducted among different individuals performing same physical activity is significantly important. This study proposed an alternative workload calculation approach, in which the workload unit was expressed in %VdotO2max. The results showed that alternative workload measurement provided excellent accurateness similar to that provided by conventional workload assessment method. Further analysis showed that the proposed unit showed a fair reading when the analysis was carried out to more than one individual. This was because the proposed unit considered maximum physical work capacity (short term) of each individual in its calculation.
Effects of Methanol Extract on Bioactive Property and in Vitro Antioxidant Activity of Palma Christi (Anthocleista nobilis G. Don.) Root

Background: Plants have diverse phytochemicals with different solubility levels and medicinal efficacy. This study aimed to determine the presence of phytochemical constituents and in vitro antioxidant activity of methanol root extract of Anthocleista nobilis. Objectives: Determining the bioactive principles and free radical scavenging properties of A. nobilis root Methods: The preliminary phytochemical investigations were performed using standard analytical procedures. The in vitro antioxidant properties were assessed by 2,2-diphenyl-1- picrylhydrazyl (DPPH) free radical scavenging assay, nitric oxide (NO) scavenging activity, ferric reducing antioxidant power (FRAP) assay, total antioxidant capacity (TAC), and hydrogen peroxide (H2 O2 ) scavenging activity. Results: The phytochemical analyses revealed the presence of several compounds: saponins, reducing sugar, alkaloids, tannins, flavonoids, cardiac glycosides, and mucilages. The concentrations of these compounds were different. A considerable quantity of phytochemicals was found in the methanol extract. The impact of the extract on DPPH, NO, FRAP, TAC, H2 O2 radicals were dependently and ascendingly concentrated. Solvent extract demonstrated better antioxidant activity, with DPPH and NO showing maximum antioxidant capability in conjunction with IC50 values of 5.45 µg/mL. Conclusion: The study results prove that A. nobilis is a possible source of natural antioxidants, justifying its use in indigenous medicine.
The Relationship between Obesity and Pre-Eclampsia: Incidental Risks and Identification of Potential Biomarkers for Pre-Eclampsia

Obesity has been steadily increasing over the past decade in the US and worldwide. Since 1975, the prevalence of obesity has increased by 2% per decade, unabated despite new and more stringent guidelines set by WHO, CDC, and other public health organizations. Likewise, maternal obesity has also increased worldwide over the past several years. In the United States, pre-pregnancy rates have increased proportionally across all racial groups. Obesity during pregnancy has been directly linked to obstetric complications including gestational diabetes, HTN, hematomas, pre-eclampsia, and congenital defects. In the particular case of pre-eclampsia, the incidence rate across the globe is 2.16%, but the condition accounts for 30% of maternal deaths, and a robust body of evidence underscored the relationship between obesity and pre-eclampsia. More recently, attention has focused on the identification of reliable biomarkers predictive of an elevated risk for pre-eclampsia. The aim of this literature review is to elucidate the relationship between obesity and these predictive biomarkers for future prediction and prevention of pre-eclampsia condition in women at risk.
The Effect of Social and Personal Norm on Intention to Patronize Green Hotels: Extension of Theory of Planned Behavior

ABSTRACT Despite most previous studies investigated the relationship between consumers’ attitude and behavior gap by adopting the theory of planned behavior (TPB). However, patronizing green hotels is still considered to be one of the most persistent challenges in behavioral transformation agenda. This paper aims to contribute to the TPB by investigating the role of personal norm (PN) in explaining consumers’ intention to patronize green hotels. This study also argues that consumers’ social norms (SN) can influence their attitudes, perceived behavioral control (PBC) and PN toward intention, and attitude can influence their PBC. A total of 399 valid questionnaires were collected to empirically test the generated hypotheses using SPSS and AMOS. The findings indicated that SN positively influenced PN, attitude, PBC and intention, respectively. PN, attitude, and PBC were shown to positively influence intention. Furthermore, PN shown a mediating effect on the relationship between SN and intention, attitude displayed a mediating effect on the relationship between SN and intention, and PBC mediated the relationship between attitude and intention. This study expanded the TPB which incorporated PN as an antecedent to provide a better understanding on consumers’ intention to patronize green hotels. The theoretical contributions, practical implications and limitation are discussed accordingly. 社会规范和个人规范对消费者光顾绿色酒店意愿的影响:计划行为理论的延伸
The State of the Art of Metadata Managements in Large-Scale Distributed File Systems Scalability, Performance and Availability

File system metadata is the data in charge of maintaining namespace, permission semantics and location of file data blocks. Operations on the metadata can account for up to 80% of total file system operations. As such, the performance of metadata services significantly impacts the overall performance of file systems. A large-scale distributed file system (DFS) is a storage system that is composed of multiple storage devices spreading across different sites to accommodate data files, and in most cases, to provide users with location independent access interfaces. Large-scale DFSs have been widely deployed as a substrate to a plethora of computing systems, and thus their metadata management efficiency is crucial to a massive number of applications, especially with the advent of the big data age, which poses tremendous pressure on underlying storage systems. This paper reports the state-of-the-art research on metadata services in large-scale distributed file systems, which is conducted from three indicative perspectives that are always used to characterize DFSs: high-scalability, high-performance, and high-availability, with special focus on their respective major challenges as well as their developed mainstream technologies. Additionally, the paper also identifies and analyzes several existing problems in the research, which could be used as a reference for related studies.
Maintenance of time standards in the Department of Reference Standards in Zielonka. Contribution into the creation of the Polish Atomic Time Scale TA (PL)

The article includes information about time standards in the Department of Reference Standards in Zielonka. The department is part of the Central Military Calibration Laboratory, which performs tasks related to the calibration standards of the other military calibration laboratories in Poland. The first part discusses components of a time standards station, which is involved in the creation of an Independent Polish Atomic Time Scale TA (PL), and its maintenance process. The second part is related to the analysis of the benefits of the inclusion of standard time calibration laboratory into the TA (PL). Last part presents the method of determining the parameters of the Relative Frequency Deviation (RFD), the prediction and uncertainly estimate of RFD
Long Live Hermes! Mercury Retrograde and Equity Prices

This paper examines the effect of Mercury Retrograde on stock market returns. Focusing on market indexes in 48 countries, we find that the average market returns in Mercury Retrograde periods are about 3.22% annually lower than those in other periods. Our additional tests offer supporting evidence that a belief channel explains the return prediction of Mercury Retrograde: investors who hold an astrological belief that Mercury Retrograde can destroy their decision-making will stay away from the market. This effect results in a higher risk premium required by remaining investors in sharing more risk. We further confirm that this belief channel is about a belief in ancient Greek culture, highlighting the importance of the ancient culture in the market returns. Collectively, our findings suggest that for some artificial cultures, investors may deem them important, and behave accordingly.
A Rabbit Farm Environmental Monitoring System based on Internet of Things

On account of the low degree of automation in a rabbit farm, this paper proposes a rabbit farm environmental monitoring system based on internet of things. First, this paper designs a rabbit farm environmental monitoring system according to the three-tier architecture of the internet of things. Then it chooses a wireless transmission module as required by the system in addition to the proposal of a new gateway initialization flow for the internet of things. After that, it analyzes the flow to query the farm monitoring data and the flow of reverse control on the environmental parameters to verify finally the feasibility of the system through the experiment.
Microbial community composition and function in an urban waterway with combined sewer overflows before and after implementation of a stormwater storage pipe

When the wastewater volume exceeds the sewer pipe capacity during extreme rainfall events, untreated sewage discharges directly into rivers as combined sewer overflow (CSO). To compare the impacts of CSOs and stormwater on urban waterways, we assessed physicochemical water quality, the 16S rRNA gene-based bacterial community structure, and EcoPlate-based microbial functions during rainfall periods in an urban waterway before and after a stormwater storage pipe was commissioned. A temporal variation analysis showed that CSOs have significant impacts on microbial function and bacterial community structure, while their contributions to physicochemical parameters, bacterial abundance, and chlorophyll a were not confirmed. Heat map analysis showed that the impact of CSO on the waterway bacterial community structure was temporal and the bacterial community composition in CSO is distinct from that in sewers. Hierarchical clustering analysis revealed that the waterway physicochemical water qualities, bacterial community composition, and microbial community function were distinguishable from the upper reach of the river, rather than between CSO and stormwater. Changes in the relative abundance of tetracycline resistance (tet) genes—especially tet(M)—were observed after CSOs but did not coincide with changes in the microbial community composition, suggesting that the parameters affecting the microbial community composition and relative abundance of tet genes differ. After pipe implementation, however, stormwater did not contribute to the abundance of tet genes in the waterway. These results indicate that CSO-induced acute microbial disturbances in the urban waterway were alleviated by the implementation of a stormwater storage pipe and will support the efficiency of storage pipe operation for waterway management in urban areas.
Assesment of the CMIP6 models to study interseasonal SSTvariabilities in the BoB

ABSTRACT The Coupled Model Intercomparison Project (CMIP) of the World Climate Research Program (WCRP) has provided a large number of AOGCMs, publicly available through CMIP6, for a better understanding of global and regional-scale ocean dynamics. This study analyzes the SST outputs of 22 models in CMIP6 with AVHRR database for the NorthWest Bay of Bengal and gives the individual model performances in terms of performance indices and skill scores. It is shown that the CAMS-CSM1, which was designed for the East Asian region, has the best performance at a skill score of 0.95, whereas NorCPM1 has the worst performance with a skill score of 0.55 for the interseasonal timescales in the Bay of Bengal. Correlations of the net heat flux (with a correlation of 0.5) and solar insolation (with a correlation of 0.9) with SST are carried out as they are the primary drivers of SST variability interseasonally. Finally, a case study is conducted to study the seasonal features of upwelling in NorthWest BoB, which shows that only a few models are capable of adequately reproducing the upwelling, and conclude that the CAMS-CSM1 is most suitable for the BoB.
Distributed Adaptive-MPC Type Optimal PMS for PV-Battery Based Isolated Microgrid

In the absence of an external grid, supplying quality power to critical loads in renewables, i.e., solar photovoltaics (PV)-battery-based self-sustained isolated microgrid (MG) system is quite troublesome. Because of involved generation arbitrage and variable load conditions, a robust power management scheme is essential. In this article, a distributed strategy with an adaptive model predictive control (MPC) principle is proposed. It considers all possible uncertainties, viz., intermittent generation as time-varying solar irradiance, variable load profile, alongside maintaining smooth charging/discharging cycle of storage units and shedding of noncritical loads. For this purpose, a novel comprehensive small-signal state-space model of MG with PV-battery systems having dedicated parallel RLC loads and a low-voltage network is considered, which accounts for inverter dc-bus link dynamics. The controller tracks the maximum power point of PV and keeps the MG power balance intact for both active and reactive powers by considering interconnected bus dynamics. The viability of the proposed scheme is verified by performing extensive testing, viz., variable solar irradiance profile, continuous small and large variations of loads, shedding of the noncritical loads, multiple topology subsystems, comparative study with state-of-art MPC, and smooth transition of battery charging/discharging cycles using MATLAB platform over 24 and 48 h duration.
Anomaly detection model based on few-shot learning and memory modules

Abstract. Anomaly detection is a key issue in public security. Its accuracy is essential to identify abnormalities and take corresponding actions to ensure the safety of relevant objects, which have a broad application space. The traditional anomaly detection method based on deep learning has too strong generalization ability. At the same time, it lacks recognition ability because it only uses normal data for training. To this end, we propose an anomaly detection model based on few-shot learning, guided by memory modules and trained by a large number of normal samples combined with a small number of observed abnormalities. We introduce memory modules to record normal features, which has the function of updating and reading. When training modules, feature compactness, and separateness loss are utilized, it successfully weakens the strong generalization of CNN and improves the memory module to identify normal samples. Then, based on the few-shot learning approach, we learn a more compact normal data distribution and expand the margin between normal and anomalous events to improve the discriminant ability. Many experimental results demonstrate that our method is practical and feasible, and its performance is better than the existing detection methods.
Prediction of Compaction and Strength Properties of Amended Soil Using Machine Learning

In the current work, a systematic approach is exercised to monitor amended soil reliability for a housing development program to holistically understand the targeted material mixture and the building input derived, focusing on the three governing parameters: (i) optimum moisture content (OMC), (ii) maximum dry density (MDD), and (iii) unconfined compressive strength (UCS). It is in essence the selection of machine learning algorithms that could optimally show the true relation of these factors in the best possible way. Thus, among the machine learning approaches, the optimizable ensemble and artificial neural networks were focused on. The data sources were those compiled from wide-ranging literature sources distributed over the five continents and twelve countries of origin. After a rigorous manipulation, synthesis, and results analyses, it was found that the selected algorithms performed well to better approximate OMC and UCS, whereas that of the MDD result falls short of the established threshold of the set limits referring to the MSE statistical performance evaluation metrics.