Miracle-dz/UniFAR-FTUs huggingface dataset:
Laboratory strains of Bacillus anthracis exhibit pervasive alteration in expression of proteins related to sporulation under laboratory conditions relative to genetically related wild strains

The spore forming pathogen Bacillus anthracis is the etiologic agent of anthrax in humans and animals. It cycles through infected hosts as vegetative cells and is eventually introduced into the environment where it generates an endospore resistant to many harsh conditions. The endospores are subsequently taken up by another host to begin the next cycle. Outbreaks of anthrax occur regularly worldwide in wildlife and livestock, and the potential for human infection exists whenever humans encounter infected animals. It is also possible to encounter intentional releases of anthrax spores, as was the case in October 2001. Consequently, it is important to be able to rapidly establish the provenance of infectious strains of B. anthracis. Here, we compare protein expression in seven low-passage wild isolates and four laboratory strains of B. anthracis grown under identical conditions using LC-MS/MS proteomic analysis. Of the 1,023 total identified proteins, 96 had significant abundance differences between wild and laboratory strains. Of those, 28 proteins directly related to sporulation were upregulated in wild isolates, with expression driven by Spo0A, CodY, and AbrB/ScoC. In addition, we observed evidence of changes in cell division and fatty acid biosynthesis between the two classes of strains, despite being grown under identical experimental conditions. These results suggest wild B. anthracis cells are more highly tuned to sporulate than their laboratory cousins, and this difference should be exploited as a method to differentiate between laboratory and low passage wild strains isolated during an anthrax outbreak. This knowledge should distinguish between intentional releases and exposure to strains in nature, providing a basis for the type of response by public health officials and investigators.
Centrally Managed Storage Facilities in Small Non-Interconnected Island Systems

In this paper the operation of small isolated island grids is investigated with the presence of centrally managed battery energy storage (BES) facilities. A mixed integer linear programming (MILP) unit commitment and economic dispatch (UC-ED) method is utilized to evaluate the impact from the introduction of BES on system operation. Two small non-interconnected island (NII) power systems with diversified characteristics are examined under high renewable energy source (RES) penetration conditions and the anticipated benefits for the system from the presence of storage are quantified in terms of security, economics and achievable renewable energy penetration levels in each case.
STEM Experiences in Primary and Lower Secondary Schools

This contribution informs about the importance of STEM education and our experiences at Matej Bel University and Ján Bakoss primary and lower secondary school. We chose Computer Science as an appropriate subject where STEM education can be suitably added. Tangible technological devices such as Parrot Jumping Sumo drone or Airblock drone were used among students aged 8 - 12. We were observing two focus groups and their motivation between highly motivated students in Computer Science and “ordinary” students.
N-Terminal Pro-Brain Natriuretic Peptide Predicts Long-Term Technique Failure in Patients Undergoing Peritoneal Dialysis

It is unclear whether N-terminal pro-brain type natriuretic peptide (NT-proBNP) level can be a biomarker for technique failure among long-term peritoneal dialysis (PD) patients. We prospectively included end-stage renal disease patients undergoing PD from a single center between December 2011 and December 2017. We divided the cohort into high or low NT-proBNP groups and analyzed the risk factors associated with the incidence of technique failure using Cox proportional hazard regression analysis. A total of 258 chronic PD patients (serum NT-proBNP, 582 ± 1216 ng/mL) were included. After a mean follow-up of 3.6 years, 49.6% of PD patients developed technique failure and switched to hemodialysis, while 15.5% died. Cox proportional hazard regression analyses accounting for age, gender, diabetes, renal clearance, C-reactive protein, and hydration status, showed that higher natural log transformed NT-proBNP levels (hazard ratio [HR] 1.13, p < 0.01) were predictive of an increased risk of technique failure, and were also predictive of an increased risk of mortality (HR 1.56, p < 0.01). Consequently, NT-proBNP might be an under-recognized biomarker for estimating the risk of technique failure, and regular monitoring NT-proBNP levels among PD patients may assist in their care.
Association and biomarker potential of elevated serum adiponectin with nephropathy among type 1 and type 2 diabetics: A meta-analysis

Background Managing nephropathy associated with diabetes mellitus warrant investigation of relevant biomarkers in predicting this condition. Adiponectin (ADP) may hold promise as a biomarker for diabetic nephropathy (DN). In this study, we examine associations of ADP with DN by meta-analyzing relevant literature. We also examined the predictive potential of ADP and estimate progression of DN. Methods Multi-database literature searches and serial omissions of articles yielded 13 studies for inclusion in the meta-analysis. We compared ADP levels between controls/ normoalbuminuria and cases with micro- and macroalbuminuria (MI and MA, respectively) as well as MI versus MA using standardized mean differences (SMD). Associations of ADP with DN were indicated with the P-value considered significant at ≤ 0.05. Subgrouping was based on diabetes type (1 and 2). Predictive potential of ADP was explored with AUC (area under the curve) derived from Receiver Operating Characteristic curve analysis. Results and conclusion At high P-values of <10−5, overall and subgroup outcomes indicated ADP associations with DN (up to SMD = 1.89–2.26, respectively). However, heterogeneity of the initial SMD effects (up to I2 = 99%) warranted examination of their sources which with the Galbraith plot method, either eliminated or reduced their heterogeneity, signifying combinability of the studies. This feature along with consistency of significant associations, robust outcomes and significant AUC values provide good evidence of the associative and predictive roles of ADP in DN.
Prototype for estimation and forecasting of the future demand and generation from households in selected European countries

New smart grid technologies, such as solar panels and electric vehicles, are increasing in popularity, but there is uncertain how this will affect the load profile for households, and how the Distribution System Operators should incorporate these changes in their grid planning. In this paper, a prototype for estimation and forecasting of the electricity demand (active power) for households is presented. The tool uses hourly data for load, temperature and irradiation as input to create a 24-hour load profile based on season and day type, as seen from the connection point to the grid. It is possible to add a solar panel, charging of electric vehicles or demand response, to see how these smart grid technologies may alter the profile. The tool is, in addition to Norwegian data, further tested on data from Germany and the UK. The results show the calculated profiles for households with solar panels in Norway, Germany and the UK, in both winter and summer time. Further, it becomes obvious that charging of electric vehicles has a profound impact on the load profile of a household.
Overview of Cloud Computing Standards

This paper deals with standardization in Cloud Computing (CC). Cloud is being widely used, but is not standardized yet. There are several organizations that try to standardize basic functions of Cloud Computing, such as NIST or lTV - T. In the first part, we made overview of standards dealing witch basic definition of CC and deployment models. Next, there is list of cloud services and types of roles in CC. In the last section, there are reference architectures of CC.
Simulation-Based Body Motion Classifier Using Radio Channel Characteristics

Human motion classification is emerging technology which can improve healthcare system and to realize context-aware body area network (BAN). This paper focused the fact that the radio channel characteristics between sensor devices and coordinator may have stronger potential for motion classification than the conventional methods using accelerometer and the video sensor. Due to extremely large variety of possible combination of the channel components it is actually very difficult to obtain the accurate motion classifier based on measurement. Therefore, this study proposed a simulation-based classifier that is generated by large amount of data from the combination of individual channel components in computer simulation. This paper presented the current development that included only the free-space path loss variation by body motion. The automatic motion classification for 6 motion scenarios by using the radio channel between four sensor devices and coordinator was evaluated. From the results, it was seen that the method using radio channel entirely outperforms the method using acceleration, particularly in static motion scenarios.
Tunable Frequency-Division Duplex RF Front End Using Electrical Balance and Active Cancellation

This paper presents a novel, tunable, frequency-division duplexing radio frequency (RF) front end that combines passive and active self-interference (SI) cancellation. An electrical-balance duplexer is used to passively cancel transmitter noise in the receive band, and an active canceller is employed to suppress SI in the transmit (Tx)-band. Subsystem specifications are developed, and a system-level analysis of noise and SI powers in this novel architecture is provided, thereby illustrating its operation. A proof-of-concept demonstrator, built from a software-defined radio and discrete RF components, has been characterized across a range of duplex configurations in the 700–950-MHz range and also at 1900 (Long-Term Evolution (LTE) band 3) and 2600 MHz (LTE band 7). The prototype achieves an impressive 6.0–7.4-dB noise figure in the presence of a +27-dBm LTE uplink Tx blocker for duplex separations of 47.5 MHz and above. The duplexer has also been tested against reference sensitivity test cases defined in the 3GPP LTE specification, demonstrating specification compliant sensitivity in LTE bands 28 (700 MHz), 3, and 7.
Relationship between Progressive Changes in Lamina Cribrosa Depth and Deterioration of Visual Field Loss in Glaucomatous Eyes

Purpose To investigate the relationship between the progression of visual field (VF) loss and changes in lamina cribrosa depth (LCD) as determined by spectral-domain optical coherence tomography (SD-OCT) enhanced depth imaging in patients with primary open angle glaucoma (POAG). Methods Data from 60 POAG patients (mean follow-up, 3.5 ± 0.7 years) were included in this retrospective study. The LCD was measured in the optic disc image using SD-OCT enhanced depth imaging scanning at each visit. Change in the LCD was considered to either ‘increase’ or ‘decrease’ when the differences between baseline and the latest two consecutive follow-up visits were greater than the corresponding reproducibility coefficient value (23.08 µm, as determined in a preliminary reproducibility study). All participants were divided into three groups: increased LCD (ILCD), decreased LCD (DLCD), and no LCD change (NLCD). The Early Manifest Glaucoma Trial criteria were used to define VF deterioration. Kaplan-Meier survival analysis and Cox's proportional hazard models were performed to explore the relationship between VF progression and LCD change. Results Of the 60 eyes examined, 35.0% (21 eyes), 28.3% (17 eyes), and 36.7% (22 eyes) were classified as the ILCD, DLCD, and NLCD groups, respectively. Kaplan-Meier survival analysis showed a greater cumulative probability of VF progression in the ILCD group than in the NLCD (p < 0.001) or DLCD groups (p = 0.018). Increased LCD was identified as the only risk factor for VF progression in the Cox proportional hazard models (hazard ratio, 1.008; 95% confidence interval, 1.000 to 1.015; p = 0.047). Conclusions Increased LCD was associated with a greater possibility of VF progression. The quantitative measurement of LCD changes, determined by SD-OCT, is a potential biomarker for the prediction of VF deterioration in patients with POAG.
Cyber Security Challenges in Autonomous Vehicle: Their Impact on RF Sensor and Wireless Technologies

Connected and Autonomous Vehicles (CAVs) will play a crucial role in nextgeneration and intelligence cars. Autonomous Vehicles (AV) are equipped with the advanced RF and wireless communication and sensor infrastructure for supporting vehicular network. AVs not only help to empower aging populations, but also they provide a powerful, noninvasive, non-threatening modality by which to monitor, interact with, and respond to their passengers’ state of being. Ten million AVs or self-driving cars will be on the road by 2020, according to an indepth report recently. Proponents of AVs say that the technology has the potential to benefit society in a range of ways, from boosting economic productivity to reducing urban congestion. However, others including some potential consumers and corporate risk managers have expressed serious concerns over the cybersecurity of the so-called fleet of the future. In this research, we will describe how to develop and implement such functionalities highly secure, trust, reliable and accurate sensors. RF sensors like radars and multitude of other types of RF sensors arrays (IoT based) are an instrumental part of the general sensor configuration required for implementing a robust cyber-security strategy and enhancing privacy in addition to the other autonomous features. There are some challenges and threats such as:•What is a new and important threat in AV and what is the difference between it and the other threat occurred in cyber space? •How can AV be attacked? •What is the difference between security and privacy mechanisms for AV? •Could the risk management be ridable to define, control, and mitigate the risk in an AV? •Could cyber-criminals remotely hijack an autonomous car’s electronics with the intention of causing a crash? •Could terrorists command the vehicles similar to the weapons? •Could data stored on-board be unlocked? •Could the AV privacy and passengers be considered? •Is there any secure channel in V2V connection for AV?
Polypharmacology Browser PPB2: Target Prediction Combining Nearest Neighbors with Machine Learning

Here we report PPB2 as a target prediction tool assigning targets to a query molecule based on ChEMBL data. PPB2 computes ligand similarities using molecular fingerprints encoding composition (MQN), molecular shape and pharmacophores (Xfp), and substructures (ECfp4) and features an unprecedented combination of nearest neighbor (NN) searches and Naı̈ve Bayes (NB) machine learning, together with simple NN searches, NB and Deep Neural Network (DNN) machine learning models as further options. Although NN(ECfp4) gives the best results in terms of recall in a 10-fold cross-validation study, combining NN searches with NB machine learning provides superior precision statistics, as well as better results in a case study predicting off-targets of a recently reported TRPV6 calcium channel inhibitor, illustrating the value of this combined approach. PPB2 is available to assess possible off-targets of small molecule drug-like compounds by public access at http://gdb.unibe. ch .
The Effect of Gates-Glidden Drills on the Quality of Root Canal Treatment by Pre-Clinical Dental Students

AIM: This study was conducted to investigate the effect of applying Gates-Glidden (GG) drill by pre-clinical dental students on root canal treatment quality. METHOD: A total of 56 first molars consisting of 168 canals were selected in this study. For this purpose, 56 students who had been formerly trained by two methods of root canal preparation were randomly divided into two groups (n = 28). Group 1: the step-down method by GG and Group 2: step-back technique without GG. The prepared teeth were filled with gutta-percha/ZOE sealer using lateral condensation. Periapical radiographs were taken before and the following treatment to survey occurrence of preparation errors and CBCT images to determine residual dentine at furcation region. RESULTS: The findings showed that among 10 error types in specimens prepared by students, the occurrence of underfilling, overfilling, inappropriate, ledge formation, and single cone was more common without GG. There were no significant differences in residual dentine amount at furcation region between preparation with and without using GG (P > 0.05). CONCLUSION: Using GG for root canal preparation by dental students resulted in low errors and not an increased dentine removal risk.
Research on stock trading strategy based on deep neural network

Deep neural network is widely concerned with the concept of deep learning. However, there are few researches focus on the application of deep neural network for stock trading strategy. Excellent trading strategies can not only help investors get high profit, but also effectively reduce the income risk. This paper studies 7 trading strategies based on a deep neural network, and uses the 2009–2015 years historical data of Shanghai Composite Index for experiments through sliding window approach, and adopts the accuracy, rate of excess return, volatility of yield and information ratio to measure the advantages and disadvantages of different trading strategies. According to the experimental results, a trading strategy suitable for the deep neural network is found. This trading strategy can not only achieve a high predictive accuracy but also have a low volatility, which can help investors reduce the risk of loss effectively while obtaining satisfactory returns.
Invalid Data-Aware Coding to Enhance the Read Performance of High-Density Flash Memories

High bit-density flash memories such as Multi-Level Cell (MLC) and Triple-Level Cell (TLC) flash have become a norm, since doubling the cell bit-density can increase the storage capacity by 2X using the same number of cells. However, these high bit-density flash memories suffer from the read variation problem - e.g., the three kinds of bits (i.e., lower, middle, and upper bits) in a TLC cell have different read latencies; reading an upper bit takes a longer time than reading a middle bit, and reading a lower bit takes the minimum time. In this paper, we note that, in the conventional coding, the long read latencies of the middle and upper bits are not reduced even after the lower bit value is invalidated (i.e., no longer used). Motivated by this problem with the traditional coding, we propose a new coding technique, called Invalid Data-Aware (IDA) coding, which reduces the upper and middle bit read latencies close to the lower bit read latency when the lower bit becomes invalid. The main strategy the IDA coding employs is to merge the duplicated voltage states coming from the bit invalidation and reduce the number of (read) trials to identify the voltage state of a cell. To hide the performance and reliability degradation caused by the application of the IDA coding, we also propose to implement it as a part of the data refresh function, which is a fundamental operation in modern SSDs to keep its data safer and longer. With an extensive analysis of a TLC-based SSD using a variety of read-intensive workloads, we report that our IDA coding improves the read response times by 28%, on average; it is also quite effective in devices with different bit densities and timing parameters.
Battery Energy Storage Requirements for Mitigating PV Output Fluctuations

While the number of distribution-connected PV units has been on the rise in recent years in the United States, the short-term fluctuation of PV output remains a challenge to continued growth and adoption. This paper explores the battery energy storage requirements for mitigating PV output fluctuations. The behavior of irradiance fluctuations is examined for a full year to determine the power rating, capacity, and cycling requirements of the battery energy storage system. Several sensitivity analyses are performed on solar ramp rate limits and battery power rating to uncover the characteristics of solar irradiance fluctuations and identify the potential solutions for reducing the battery energy storage system requirements.
Optimized Recovery Algorithms for RDP $(p, 3)$  Code

RDP<inline-formula> <tex-math notation="LaTeX">$(p,3)$ </tex-math></inline-formula>, which can tolerate up to three concurrent disk failures. For single-disk failure recovery, we derive a lower bound on disk reads. To approach the derived lower bound, we propose an algorithm that aims at maximizing the overlapping symbols among different types of parity set. For double-disk failure recovery, we propose an algorithm to accelerate the recovery process by shortening the recovery chains with the help of the extra parities. Numerical results for <inline-formula> <tex-math notation="LaTeX">$p \leq 47$ </tex-math></inline-formula> show that the proposed algorithm can further reduce by approximately 10% disk reads for single-disk recovery.
Conservation implications of primate trade in China over 18 years based on web news reports of confiscations

Primate species have been increasingly threatened by legal and illegal trade in China, mainly for biomedical research or as pets and traditional medicine, yet most reports on trade from China regard international trade. To assess a proxy for amount of national primate trades, we quantified the number of reports of native primate species featuring in unique web news reports from 2000 to 2017, including accuracy of their identification, location where they were confiscated or rescued, and their condition upon rescue. To measure temporal trends across these categories, the time span was divided into three sections: 2000–2005, 2006–2011 and 2012–2017. A total of 735 individuals of 14 species were reported in 372 news reports, mostly rhesus macaques (n = 165, 22.5%, Macaca mulatta) and two species of slow lorises (n = 487, 66.3%, Nycticebus spp.). During the same period, live individuals of rhesus macaques were recorded 206 times (70,949 individuals) in the Convention on International Trade in Endangered Species of Wild Fauna and Flora Trade Database, whereas slow lorises were only recorded four times (nine individuals), indicating that the species originated illegally from China or were illegally imported into China. Due to their rescued locations in residential areas (n = 211, 56.7%), most primates appeared to be housed privately as pets. A higher proportion of ‘market’ rescues during 2006–2011 (χ2 = 8.485, df = 2, p = 0.014), could be partly attributed to an intensive management on wildlife markets since the outbreak of severe acute respiratory syndrome (SARS) in 2003. More than half (68.3%, 502 individuals) of the primate individuals were unhealthy, injured or dead when rescued. Thus, identification and welfare training and capacity-building should be provided to husbandry and veterinary professionals, as well as education to the public through awareness initiatives. The increase in presence of some species, especially slow lorises, with a declining population in restricted areas, also suggests the urgent need for public awareness about the illegal nature of keeping these taxa as pets.