Miracle-dz/UniFAR-FTUs huggingface dataset:
Development and Assessment of Spatially Continuous Predictive Algorithms for Fine Particulate Matter in New York State

Health risks connected with fine particulate matter (PM2.5) pollutants are well documented; increased risks of asthma, heart attack and heart failure are a few of the effects associated with PM2.5. Accurately forecasting PM2.5 is crucial for state agencies directed to devise State Implementation Plans (SIPS) to deal with National Ambient Air Quality Standards (NAAQS) exceedances. In previous work, we explored the application of multi-temporal data-driven neural networks (NNs) to forecasting PM2.5. Our work showed that under different input conditions, the NN approach achieves higher forecasting scores for local (12 km) resolution when compared to the other Chemical Transport Model forecast models, such as the Community Multi-Scale Air Quality system (CMAQ). Critical to our approach was the inclusion of prior PM2.5 concentrations, retrieved from ground monitoring stations, as part of the input dataset for the NN. The NN approach can provide high-level forecasting accuracy; however, because of the dependency on ground monitoring stations, the forecast coverage is sparse. Here, we extend our previous station-specific efforts by forecasting hourly PM2.5 values that are spatially continuous through the use of a deep neural network (DNN). The DNN approach combines spatial Kriging with additional local source variables to interpolate the measured PM2.5 concentrations across non-station locations. These interpolated PM2.5 values are used as inputs in the original forecasting NN. Cross-validation testing, using all New York State AirNow PM2.5 stations, showed that this forecast approach achieves accurate results, with a regression coefficient (R2) of 0.59, and a root mean square error (RMSE) of 2. 22μgm3. Additionally, herein we demonstrate the usefulness of this approach on specific temporal events where significant dynamics of PM2.5 were observed; particularly, we show that even bias-corrected CMAQ forecasts do not track these transients and our NN method.
A Novel of Floating Tablet Delivery System as A Tool to Enhance Absorbtion of Drug: A Review

This assessment of a floating drug for a novel of new drug delivery system (NDDS) is written to elucidate FDDS based on existing literature. The most recent progresses of FDDS include the formulation and physiological variables that could affect gastric retention and formulations are discussed in detail. This review also summarizes method assessments for FDDS pharmaceutical dosage form and its classification. FDDS. FDDS is made to increase the absorption of the drug that is expected to dissolve in the stomach so that the drug enters the intestine in a dissolved state and the fraction of the absorbed drug increases. FDDS approach is the best way to deal with drugs with low solubility in the digestive tract.
DNA Sequencing Flow Cells and the Security of the Molecular-Digital Interface

Abstract DNA sequencing is the molecular-to-digital conversion of DNA molecules, which are made up of a linear sequence of bases (A,C,G,T), into digital information. Central to this conversion are specialized fluidic devices, called sequencing flow cells, that distribute DNA onto a surface where the molecules can be read. As more computing becomes integrated with physical systems, we set out to explore how sequencing flow cell architecture can affect the security and privacy of the sequencing process and downstream data analysis. In the course of our investigation, we found that the unusual nature of molecular processing and flow cell design contributes to two security and privacy issues. First, DNA molecules are ‘sticky’ and stable for long periods of time. In a manner analogous to data recovery from discarded hard drives, we hypothesized that residual DNA attached to used flow cells could be collected and re-sequenced to recover a significant portion of the previously sequenced data. In experiments we were able to recover over 23.4% of a previously sequenced genome sample and perfectly decode image files encoded in DNA, suggesting that flow cells may be at risk of data recovery attacks. Second, we hypothesized that methods used to simultaneously sequence separate DNA samples together to increase sequencing throughput (multiplex sequencing), which incidentally leaks small amounts of data between samples, could cause data corruption and allow samples to adversarially manipulate sequencing data. We find that a maliciously crafted synthetic DNA sample can be used to alter targeted genetic variants in other samples using this vulnerability. Such a sample could be used to corrupt sequencing data or even be spiked into tissue samples, whenever untrusted samples are sequenced together. Taken together, these results suggest that, like many computing boundaries, the molecular-to-digital interface raises potential issues that should be considered in future sequencing and molecular sensing systems, especially as they become more ubiquitous.
A Comparison of Artificial Neural Networks and Some Nonlinear Models of Leaf Area Estimation of Sugar Beet at Different Nitrogen Levels

Leaf area is related to many physiological and agronomic studies including growth, photosynthesis, transpiration, and energy balance. The study aimed to determine the leaf area estimation of sugar beet (Beta vulgaris L.) at different nitrogen levels under field conditions. The study was conducted out in split plots in randomized complete blocks with three replications in 2012-2013, and measurements were taken from leaf parameters, such as length (L) and width (W), petiole length, and the total number of leaf per a sugar beet. The artificial neural networks and such non-linear methods as the Logistic, Richards, and Gompertz were compared to estimate the leaf area measurements. As a result, all models have shown the highest identification success in the level of third fertilization. While the ANN model in the first three fertilizer doses showed a higher definition of success compared to other models, the Richards model in the fourth fertilizer dose has been more successful. An increase in the nitrogen level has accelerated the plant growth. While the ANN model remained insufficient for very rapid growth identification, the Richards model is defined in more successful rapid growth.
Time Wavelength Interleaving Perceptron at 12 Giga-Ops/s with a Kerr Soliton Crystal Microcomb for Optical Neural Networks

Optical artificial neural networks (ONNs) have significant potential for ultra-high computing speed and energy efficiency. We report a novel approach to ONNs that uses integrated Kerr optical micro-combs. This approach is programmable and scalable and is capable of reaching ultra-high speeds. We demonstrate the basic building block ONNs — a single neuron perceptron — by mapping synapses onto 49 wavelengths to achieve an operating speed of 11.9 x 10 operations per second, or Giga-OPS, at 8 bits per operation, which equates to 95.2 gigabits/s (Gbps). We test the perceptron on handwritten-digit recognition and cancer-cell detection — achieving over 90% and 85% accuracy, respectively. By scaling the perceptron to a deep learning network using off-the-shelf telecom technology we can achieve high throughput operation for matrix multiplication for real-time massive data processing.
Treatment Failure in Cutaneous Leishmaniasis Patients Referred to the School of Public Health, Tehran University of Medical Sciences during 2008–2017

Background: Cutaneous leishmaniasis (CL) is a vector borne disease predominantly found in tropical and subtropical countries, including Iran. For more than 6 decades, pentavalent antimonials have been used successfully worldwide for the treatment of leishmaniasis, but over the past few years, clinical resistance to these medications has increased. In this study, we evaluated CL patients who did not show any desirable responses to the anti-leishmanial treatment within a 10-year period (2008 to 2017). Methods: All patients from different parts of Iran suspected of having cutaneous leishmaniasis, who were referred to the laboratory of leishmaniosis in Tehran University of Medical Sciences from 2008–2017 were parasitological examined. Results: During this period, a total of 1480 suspected CL patients were referred to the laboratory of leishmaniosis. Samples from 655 patients (70.8%) suspected of having CL were positive microscopically. The failure rate in patients treated with anti-leishmaniasis medications for a minimum of three complete treatment periods was 1.83% (12 cases). There was no association between the number and size of skin lesions and patient characteristics. Also, the route of drug administration had no significant effect on the number and size of lesions. Conclusion: In the present study, treatment failure was found in some confirmed CL patients treated with meglumine antimoniate. Over the past few years, it seems that had been increased in resistance to these medications. So, a review of the correct implementation of the treatment protocol and/or a combination therapy may be helpful in preventing an increase in the rate of treatment failure.
Platelet to Lymphocyte Ratio as a Potential In�ammatory Marker Predicting the Effect of Adjuvant Chemotherapy in Stage II Colorectal Cancer Patients

Background: The effect of adjuvant chemotherapy in stage II colorectal cancer (CRC) patients has been in controversy for a long time. Our study aimed to investigate the ability of several common in�ammatory markers to predict the effect of chemotherapy in stage II CRC patients, �nding an effective method for clinicians to distinguish chemotherapy-effective population. Methods: A total of 708 stage II CRC patients who underwent radical resection (R0) were included. The Subpopulation Treatment Effect Pattern Plot (STEPP) analysis was used to determine the optimal in�ammatory marker and cut-off value. Propensity Score Matching (PSM) was performed to balance discrepancy of the characteristics between the chemotherapy and non-chemotherapy group. Kaplan-Meier method with the log-rank test was used to calculate the restricted mean survival time (RMST) and compare survival difference between chemotherapy and non-chemotherapy patients. Univariate Cox proportional hazard regression analysis was used to calculate Hazard Ratio (HR). Multivariate Cox proportional hazard regression analysis was used to investigate the interaction between the effect of chemotherapy and the clinicopathological characteristics. Results: Platelet to Lymphocyte Ratio (PLR) was chosen as the predictive marker with a cut-off value of 130 according to STEPP. For all the 708 patients, chemotherapy patients had a better OS than non-chemotherapy patients (p=0.007). Besides, the results of subgroup analysis interpreted that PLR was strongly associated with the effect of chemotherapy. In the high-PLR subgroup (PLR>130), chemotherapy patients obtained a signi�cantly better survival bene�t than non-chemotherapy patients (p (cid:0) 0.001). However, in the low PLR subgroup (PLR ≤ 130), such difference of survival bene�t between chemotherapy and non-chemotherapy patients was not found (p=0.956). Multivariate Cox survival analysis also found that PLR was the only characteristic associated with the effect of chemotherapy (p interaction=0.027) among all the 11 clinicopathological characteristics. After PSM, no signi�cant difference in OS was found between the chemotherapy group and the non-chemotherapy group (p=0.058). PLR was still the only characteristic associated with the effect of
Polyaniline: Synthesis Methods, Doping and Conduction Mechanism

Among all the conducting polymers, polyaniline holds a special position, due to its unique properties such as low cost of monomers (aniline), distinguishable electrical properties, excellent redox reversibility, high environmental stability and can be easily polymerized in labs either by chemical or electrochemical methods. The electrical properties of polyaniline pretty much depend upon the doping agents, protonation of the constituent units in the chain backbone, and water content. Conductive nature of polyaniline makes it a versatile conducting polymer for variety of applications such as gas sensors, supercapacitors, lithium ion batteries and photovoltaic cells. The objective of this chapter is to provide basic concept of polyaniline synthesis and its doping mechanism. We hope that this chapter will be useful for academic as well as for research on polyaniline.
Distance-based Indoor Localization System Utilizing General Path Loss Model and RSSI

— Wireless sensor networks (WSNs) have a vital role in indoor localization development. As today, there are more demands in location-based service (LBS), mainly indoor environments, which put the researches on indoor localization massive attention. As the global-positioning-system (GPS) is unreliable indoor, some methods in WSNs-based indoor localization have been developed. Path loss model-based can be useful for providing the power-distance relationship the distance-based indoor localization. Received signal strength indicator (RSSI) has been commonly utilized and proven to be a reliable yet straightforward metric in the distance-based method. We face issues related to the complexity of indoor localization to be deployed in a real situation. Hence, it motivates us to propose a simple yet having acceptable accuracy results. In this research, we applied the standard distance-based methods, which are is trilateration and min-max or bounding box algorithm. We used the RSSI values as the localization parameter from the ZigBee standard. We utilized the general path loss model to estimate the traveling distance between the transmitter (TX) and receiver (RX) based on the RSSI values. We conducted measurements in a simple indoor lobby environment to validate the performance of our proposed localization system. The results show that the min-max algorithm performs better accuracy compared to the trilateration, which yields an error distance of up to 3m. By these results, we conclude that the distance-based method using ZigBee standard working on 2.4 GHz center frequency can be reliable in the range of 1-3m. This small range is affected by the existence of interference objects (IOs) lead to signal multipath, causing the unreliability of RSSI values. These results can be the first step for building the indoor localization system, which low-cost, low-complexity, and can be applied in many fields, especially indoor robots and small devices in internet-of-things (IoT) world’s today.
Laparoscopic Surgical Management of Symptomatic Anastomotic Ulcers after Gastric Bypass: A 10-Year Single-Center Experience

Marginal ulceration has a reported incidence up to 34% following Roux-en-y gastric bypass. Bleeding or perforation may be a medical emergency and can be managed via a wide range of techniques. Traditional laparoscopy or robotically assisted laparoscopy offer minimally invasive approaches. We reviewed the experience at a Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program (MBSAQIP) Center of Excellence.
A REVIEW OF CRYPTOGRAPHIC PRIMITIVES FOR SECURITY OF ELECTRONIC VOTING SYSTEMS

: Security around electronic systems is not only sensitive, but also remains contentious among key election stake-holders. Various cryptographic primitives have been adopted in e-voting systems to infuse confidentiality, integrity and availability, in order to entrench trust among to all stakeholders. However, the cryptographic techniques have not been well understood by the voters, candidates as well as other key election stake-holders. Presenting the mode of operation, the extent of providing security as well as the limitations of individual cryptographic primitive goes a long way to ensure that the security techniques are well understood by all stakeholders. This review looked into various cryptographic primitives applied in e-voting systems, how they achieve security, their strengths and limitations.
EPIDEMIOLOGY OF MDR GRAM-NEGATIVE IN LIGURIA

INTRODUCTION Multidrug-resistant Gram negative bacilli are serious problem in healthcare facilities. These organisms rapresent difficult treatment challenges, and limiting their dissemination is an important public health objective. In 2010, infections caused by multidrug-resistant bacteria simultaneously resistant to at least tree different classes of antimicrobial agents, MDR continue to challenge physicians and endanger their patients’lives (7). There are a number of different methods in which Gram-negative organisms develop resistance to antibiotics: β-lactamase production is the most important. Extended spectrum β-lactamase (ESBLs) are most often found in Klebsiella pneumoniae and Escherichia coli; however, other Gram negative bacilli including Enterobacter spp. , Pseudomonas aeruginosa, Citrobacter freundii, Morganella morganii and Serratia marcescens have also been found to produce these enzymes as well as AmpC cephalosporines (4). Carbapenems are the preferred antimicrobial EPIDEMIOLOGY OF MDR GRAM-NEGATIVE IN LIGURIA
Anticancer Properties of Fluorinated Aminophenylhydrazines on A549 Lung Carcinoma Cell Line

Background: Non-small cell lung cancer (NSCLC) is responsible for up to 85% of deaths associated with lung cancer. Chemotherapy is still an important treatment method on the treatment of inoperable cases. In this study, the anticancer properties of a series of Schiff bases were tested on the A549 cell line representing NSCLC. Methods: Fluorinated Schiff bases (compounds 1–6) were synthesized based on 2-amino phenylhydrazines and benzaldehydes containing fluorine were used. The cytotoxic effects of the compounds on the A549 cell line were determined by colorimetric MTT assay and the antiproliferative effects of the compounds on the A549 cell line by the CFSE method. To demonstrate the development of apoptosis, cleaved caspase-3 expression in cells was tested using the immunofluorescence method. Morphological changes indicating apoptosis in cells were determined by histopathological staining methods (H & E, giemza, PAP). Results: The strongest cytotoxic effect on A549 lung cancer cells was obtained with compound 6 (IC50: 0.64 μM) containing 5 fluorine atoms. The strongest antiproliferative effect on A549 cells was achieved with compound 5 (PI: 4.95) carrying 2 fluorine atoms. Apoptosis induction was effective in cell death. In addition to cleaved caspase-3 expression, chromatin condensation, marginalization, and apoptotic bodies were observed in the cells. Conclusion: Some of the compounds tested showed high cytotoxic and antiproliferative effects, indicating that these compounds could be potential chemotherapeutic agent candidates for lung cancer. The result of immunofluorescence and immunohistochemical analysis showing that the cytotoxic effects have been induced by apoptosis is an important advantage.
Everyday (In)Security: An Autoethnography of Student Life in the UK

Responding to the question ‘Why did you go to university? ’ users of The Student Room (TSR) – a website which claims annual usership of 70% of all students – largely expressed their desire to acquire a degree, access better opportunities and ensure a more secure financial situation (replies include, for instance: ‘I want to be educated to get a better job, and just so I have the qualification’ or ‘To get a better job in the future and earn money’). I too was driven by this logic when choosing to go to university, as I felt it would provide me with a direct pathway to a successful professional life. However, through my own experience and conversations with my peers, I started questioning universities’ capacity to produce this feeling of security. I observed a high level of anxiety amongst students as preoccupations such as “What will you do next? How many applications have you sent? How much do they pay graduates? Will you be able to pay off the debt? ” highlighted the risks which come with fees-based university degrees. Universities’ answer to such anxiety seems to always be that higher education (HE) is a way of securing yourself – particularly your economic self (Bialostok and Whitman 2012, 12 & 20).
Protein Associates with the Development of Arthritis

High titers of antibodies to caprine arthritis-encephalitis virus (CAEV) envelope (Env) glycoproteins are found in infected goats developing a progressive arthritis. In order to identify linear B epitopes of the CAEV Env, which may be involved in the immunopathology of arthritis, we constructed a Agtll Env expression library. By combining library screening with sera from naturally infected Swiss goats with an enzyme immunoassay with overlapping peptides (pepscan), four group-specific epitopes could be precisely defined in the transmembrane envelope proteins: TM1 to TM4, including a conserved structure (TM3) that corresponds to the immunodominant epitope ofhuman immunodeficiency virus type 1 and other lentiviruses. A panel of 190 CAEV naturally infected goat serum samples, obtained from animals with defined clinical status, was tested for reactivity to synthetic peptides corresponding to the TM epitopes in an enzyme-linked immunosorbent assay. Antibody reactivity to two epitopes was highly associated (TM3, P = 0.002, and TM4, P < 0.001) with the presence of clinically detectable arthritis. Such an association is absent for anti-Gag antibody. Antibodies to the immunodominant structures of the TM glycoprotein could thus have an important role in the immunopathogenic process leading to disease.
Debt‐relief programs and money left on the table: Evidence from Canada's response to COVID‐19

Abstract This paper analyzes the effectiveness of debt‐relief programs targeting short‐run household liquidity constraints implemented in Canada in response to the COVID‐19 pandemic. These programs allowed individuals to push off mortgage and credit card payments and cut in half interest rates on credit card debt. Using credit bureau data, we document that, despite potential savings above $4 billion, enrolment was limited: 24% for mortgages and 7% for credit cards. By exploiting the richness of our data set, we provide evidence that close to 80% of individuals were unaware of the credit card relief program while others faced important fixed non‐monetary costs preventing uptake.
S0025315420000442jra 517..528

Knowledge of bio-physicochemical variables is essential to better understand the functioning of tropical marine ecosystems, which are rich in biodiversity and provide nutrition and livelihoods to billions of people in the developing countries. This study analysed the spatial and temporal variability of phytoplankton and zooplankton with chlorophyll, primary productivity, temperature, salinity, oxygen and nutrients in the Bay of Bengal (BoB), collecting data from the World Ocean, and COPEPOD and Aqua MODIS records. The results indicated a strong gradient in bio-physicochemical conditions of the BoB, from the coast to the open sea. Specifically, the spatial variability in chlorophyll was negatively correlated (R = 0.59) with temperature and zooplankton, while a positive correlation (R = 0.70) was noted between chlorophyll and silicate, nitrate, phosphate, dissolved oxygen and salinity. All the variables exhibited a strong vertical gradient at depths up to 500 m. Temperature, nutrients, zooplankton and to a lesser extent salinity and rainfall had an influence on the annual abundance of phytoplankton. Over the long term, a significant positive trend in temperature and a significant negative trend in primary productivity were observed in the BoB. The findings of this study will be useful to draw insights on the state of fisheries habitats and the overall environmental conditions of the BoB in response to future climate changes.