Miracle-dz/UniFAR-FTUs huggingface dataset:
Bacterial pathogens and their susceptibility to antibiotics among mothers with premature rupture of membranes at a teaching hospital in western uganda

Background: Premature rupture of membranes (PROM) remains a great burden to mothers and their unborn children all over the world with several adverse maternal and fetal outcomes. This study aimed at determining common bacterial pathogens and their susceptibility patterns in women with PROM at Kampala International University Teaching Hospital (KIU-TH). Methods: This was a cross-sectional study conducted in the months of September 2019 to November 2019. A total of 334 pregnant mothers above 28 weeks of pregnancy admitted in maternity ward of KIU-TH were consecutively enrolled. Interviewer administered questionnaires and laboratory forms were used to collect data. Endocervical swabs were obtained from those with PROM and taken to the laboratory for culture and susceptibility tests. Descriptive statistics were used using STATA 14.2. Results: 46 (13.8%) mothers had PROM. Of these, the most common bacterial pathogens identified were S. aureus (29.6%), E. coli (25.9%) and N. gonorrhoeae (25.9%). Antibacterial susceptibility tests revealed highest sensitivity to imipenem (100%), nitrofurantoin (92.6%), cloxacillin (85.2%) and azithromycin (81.5%). Total resistance to amoxacillin, ceftriaxone and ampicillin was found. Conclusion: Women with PROM predominatly have Staphylococcus aureus, Escherichia coli and Neisseria gonorrhoeae. Imipenem, nitrofurantoin, cloxacillin and azithromycin are the most effective antibiotics among patients with PROM.
Complete plastome sequence of Aspidopterys obcordata (Malpighiaceae), a traditional Dai medicinal plant from Xishuangbanna, Yunnan, China

Abstract We reported the first complete plastid genome of Aspidopterys (Malpighiaceae) in this study. The complete plastome of Aspidopterys obcordata is 160,453 bp in length with a base composition of A (31.4%), G (18.5%), C (18.2%), and T (32.0%). Structurally, the genome contains two short inverted repeats (26,905 bp for each), which are separated by a large single copy region (88,491 bp) and a small single copy region (18,152 bp). The plastome contained 113 unique genes, including 79 protein-coding genes, 30 transfer RNAs, and 4 ribosomal RNAs. Phylogenetic analyses showed that A. obcordata was sister to Bunchosia argentea in the monophyletic Malpighiaceae. This study provided a high-quality plastome sequence for future studies in Aspidopterys, as well as Malpighiaceae.
The Impact of Major Events on Ongoing Noninferiority Trials, With Application to COVID-19

Abstract–The COVID-19 pandemic has impacted ongoing clinical trials. We consider particular impacts on noninferiority clinical trials, which aim to show that an investigational treatment is not markedly worse than an existing active control with known benefit. Because interpretation of noninferiority trials requires cross-trial validation involving untestable assumptions, it is vital that they be run to very high standards. The COVID-19 pandemic has introduced an unexpected impact on clinical trials, with subjects possibly missing treatment or assessments due to unforeseen intercurrent events. The resulting data must be carefully considered to ensure proper statistical inference. Missing data can often, but not always, be considered missing completely at random (MCAR). We discuss ways to ensure validity of the analyses through study conduct and data analysis, with focus on the hypothetical strategy for constructing estimands. We assess various analytic strategies of analyzing longitudinal binary data with dropouts where outcomes may be MCAR or missing at random (MAR). Simulations show that certain multiple imputation strategies control the Type I error rate and provide additional power over analysis of observed data when data are MCAR or MAR, with weaker assumptions about the missing data mechanism.
Problematic digital technology use of children and adolescents: Psychological impact

Since the evolution of the internet in 1969 and the inception of the personal computer in the early 1970s, a significant body of research has emerged that highlights the impacts of digital technology on education, health and human development. This paper reviews research in this area and examines the physical, mental, and social health effects on children and adolescents (10- to 19-year-olds), as well as the impacts of digital technology on educational achievements. The aim of this literature review, to examine the psychological impact of digital technology, was prompted in part by the widespread use of digital technologies in schools including Bring Your Own Device (BYOD) policies. BYOD asks students to bring personal laptop or iPad/tablet computers to school. Outcomes of this study may be surprising in the quantity of research available that provides red flag alerts. This fact alone will be of interest to school leaders as policy makers. There is a need for trustworthy information on which to base reviews and revisions of school policy to reduce the risks from the use of digital technology.
Design rules for environmental biodegradability of phenylalanine alkyl ester linked ionic liquids

Ionic liquids (ILs) are perceived as a promising group of chemicals within the realm of green chemistry. They are increasingly of interest for open environmental applications. Rules for the design of biodegradable and preferably completely mineralizing ILs after their introduction into the environment are highly desirable. In this study, the impact of the length of the alkyl chain and of the cationic head group on the environmental biodegradability of L-phenylalanine ester (PheCn) derived ILs using the pyridinium (PyPheCn), imidazolium (ImPheCn) and cholinium (CholPheCn) head groups was systematically studied. This included high-resolution mass spectrometry monitoring of formed products of incomplete mineralization. Completely biodegradable ILs were only identified in the PyPheCn series. PyPheC2 and PyPheC4 were fully mineralizable within 42 days with no detectable transformation products (TPs), whereas mineralization of longer chain length PyPheCn ILs required more time. Our results show biodegradation by microorganisms was affected by an alkyl chain length of at least 10 carbon atoms. Biodegradation of the ILs started with biotic ester hydrolysis independent of the alkyl chain length or core scaffold. In contrast, the second step of microbial degradation was an amide bond cleavage which was only shown for ILs with a pyridinium or imidazolium core, even after a test prolongation up to 42 days. Hence, the nature of the cationic head group and the chain length impacted on the mineralization and biodegradability of the ILs. For ILs with an imidazolium core, amide bond cleavage resulted in the formation of recalcitrant 1-carboxymethylimidazolium (ImAc). Whereas for most ILs with a pyridinium core, amide bond cleavage resulted in 1-carboxymethylpyridinium (PyAc) which was mineralizable, although not readily biodegradable according to the test guideline 301D. In the case of cholinium ILs, no further degradation of cholinium phenylalanine amide TP was observed after the hydrolysis of the ester to the alkyl alcohol. The biodegradability of ILs decreased in the order PyPheCn > ImPheCn > CholPheCn, but a key finding is that ImPhe is degraded to ImAc but not further (cf. favourable PyAc mineralisation). These results can be used to design ILs with the property to be effectively biodegraded and mineralized in the environment.
Research on image feature matching algorithm based on feature optical flow and corner feature

Image feature matching is an important part of visual odometry. In order to improve the accuracy of feature point matching for visual odometry, an accurate algorithm combining the pyramid feature optical flow and corner features based on image feature matching is proposed. Firstly, the Oriented Features from Accelerated Segment Test and Rotated BRIEF (ORB) algorithm is used to extract the image feature points quickly. Secondly, the local feature window is utilised to calculate the displacement vector of the image feature points and the pyramid Lucas–Kanade feature optical flow is used to track feature points. Then, to solve the problem of matching alignment and feature loss, the K nearest neighbour radius search is used as feature filter to remove the confused matching. Finally, the Random Sample Consensus algorithm is introduced to eliminate redundant mismatch points and improved the matching rate. The comparison of experimental data shows that the proposed algorithm can get high matching rate. Compared with the traditional ORB feature matching algorithm, the algorithm had a significant improvement in real time and image feature matching accuracy.
Bitcoin price forecasting method based on CNN‐LSTM hybrid neural network model

In this study, aiming at the problem that the price of Bitcoin varies greatly and is difficult to predict, a hybrid neural network model based on convolutional neural network (CNN) and long short-term memory (LSTM) neural network is proposed. The transaction data of Bitcoin itself, as well as external information, such as macroeconomic variables and investor attention, are taken as input. Firstly, CNN is used for feature extraction. Then the feature vectors are input into LSTM for training and forecasting the short-term price of Bitcoin. The result shows that the CNN-LSTM hybrid neural network can effectively improve the accuracy of value prediction and direction prediction compared with the single structure neural network. The finding has important implications for researchers and investors in the digital currencies market.
DayCent Model Predictions of NPP and Grain Yields for Agricultural Lands in the Contiguous U.S.

Accurate estimation of crop net primary production (NPP) and yields is fundamental for regional analyses of agroecosystem dynamics using process‐based models. In this study, we simulated croplands in the contiguous U.S. using the DayCent ecosystem model with new production algorithms. Crops were divided into crop variety groups based on regional varieties of three major crops (corn, soybeans, and winter wheat) and generic parameter values that were generated for each group. These varieties have been developed through crop breeding programs and enhance production of major crop types in different temperature and precipitation regimes. NPP and yields for the three major crops were evaluated at the county level with reported yields from the National Agricultural Statistics Service (NASS). The predictions of the multiyear average yields in all counties were more accurate than most other published results using process‐based models. DayCent predictions of yields produced an overall R2 of 0.54, 0.54, and 0.38 for corn, soybean, and winter wheat, respectively, with predictions for most counties within ±20% of the NASS reported yields. Our estimations of the total annual NPP for the three crops in the contiguous U.S. are 0.24, 0.09, and 0.06 Pg C yr−1 for corn, soybean, and winter wheat, respectively. Together, they contribute 7.3% to 14.8% of the total NPP for all vegetation in the contiguous U.S. We conclude that crop variety groups capture heterogeneity in NPP for major crop types and can improve biogeochemical model predictions of NPP for croplands.
A solid-phase fluorescent, quenching method for the determination of trace amounts of nitrite in foods with neutral red

A simple and sensitive solid-phase fluorescent quenching method for the determination of trace amounts of nitrite in food samples has been developed. The method is based on the reaction between nitrite and neutral red, which is used as an emission reagent, to form a non-fluorescent compound in 0.1 mol/L hydrochloric acid. The fluorescent intensity was measured in 5-mm quartz cells with excitation and emission wavelengths of 548 and 609 nm, respectively. The degree of fluorescent quenching showed good linearity at concentrations of nitrite between the ranges of 40-200 μg/L. The detection limit is 8.1 μg/L and the RSD is 1.7%. The general coexisting ions do not interfere with the reaction of neutral red with nitrite. The proposed method was applied to the determination of trace amounts of nitrite in food samples with satisfactory results. In addition, the mechanism involved in the reaction was discussed.
Systematic Detection of State Variable Corruptions in Discrete Event System Specification Based Simulation

SUMMARY In this letter, we propose a more secure modeling and simulation approach that can systematically detect state variable corruptions caused by bu ﬀ er overﬂows in simulation models. Using our approach, developers may not consider secure coding practices related to the corrup-tions. We have implemented a prototype of the approach based on a modeling and simulation formalism and an open source simulator. Through optimization, the prototype could show better performance, compared to the original simulator, and detect state variable corruptions.
Dominant factor of dry‐wet change in China since 1960s

The dry‐wet climate conditions of an area are mainly determined by the water input (e.g., precipitation, P) and output (e.g., potential evapotranspiration, PET). Based on three dry‐wet indices and the differential equation, this study designed a new attribution method to quantify the contributions of P and PET to the dry‐wet change, so as to determine the dominant factors of the dry‐wet change over whole China (CHINA) and various hydroclimate regions (i.e., arid region, AR; semi‐arid region, SAR; semi‐humid region, SHR; and humid region, HR) during 1960–2018 and six interdecadal periods. Results showed that the overall weak drying in CHINA was dominated by an increase in PET, while climate humidification in AR and HR was dominated by an increase in P, climate drying in SHR was dominated by the reduced P, and the weak drying in SAR was co‐dominated by P and PET during 1960–2018. The dominant factors of dry‐wet change over CHINA and each hydroclimate region varied in different decades. Briefly, climate humidification in CHINA and various hydroclimate regions was basically dominated by P in different decades, and the drying was mainly dominated by P in the 1960s–1980s, but the contribution of PET to climate drying began to become prominent after the 1980s. Besides, we found that P contributed more to dry‐wet change than PET on the station and regional scales, but the contribution of P to climate drying on a national scale was underestimated to some extent due to the regional offset effect of the increase/decrease in P during 1960–2018, as well as in the 1990s. These findings implied that the importance of research on the regional or local scale, and equal attention should be paid to the effects of P and PET changes in the future drought or dry‐wet change research.
Computer Vision for Industrial Safety and Productivity

The growing deployment of computer vision in industrial processes significantly contributes to strengthening the manufacturing sector in terms of productivity and safety of the workers. Manufacturing workers are often working in hazardous environments handling different dangerous equipment putting their life on the line every day. Work accidents are reminders for which companies must make efforts to reduce its occurrence and their adverse impact on the lives of workers. In case of an active accident, the computer vision system can send an alert to managers and staff about location and the intensity of the accident so the production process can be halted in that specific area and proactively ensure the safety of employees. The deployment of computer vision-powered systems operating 24/7 accelerates manufacturing cycles increasing productivity. Computer vision applications have a major role in product and component assembly in the manufacturing space. They also aid in defect detection with increased accuracy and precision. Manufacturers conduct constant monitoring of equipment used for production manually. To improve the safety and working conditions for the workers and increase productivity in the manufacturing sector, this project aims to implement computer vision as a monitoring method to assure the security measures are followed and analyze the productivity in the organization. The object recognition algorithm, YOLOv3, is trained and tested using data that is gathered from industrial facilities in the form of images.
Mothers’ perceptions of the quality of maternity services at Finnish maternity units: A cross-sectional study

Knowledge about mothers’ perceptions of the quality of Finnish maternity services is limited. The aim of this cross-sectional study was to describe mothers’ perceptions of the quality of Finnish maternity services, and to identify background factors associated with them. The data were collected from 1,760 mothers in autumn 2016. Descriptive statistics were used. This study is reported in accordance with STROBE. Most mothers (84%) considered the quality of the maternity services good. The mean response values for the quality of patient education (3.9), staff knowledge and skills (4.3), and hospital environment (4.3) were good. Parity and mode of childbirth were associated with perceptions of the quality of maternity services. Based on the results, development of midwifery and nursing practices should focus on sufficient pain relief, adequate duration of skin-to-skin contact, breastfeeding counselling and opportunities for mothers to reflect on their birth experience afterwards. Moreover, the study results can be used for education. Challenges for future research are presented.
An Adaptive Control Scheme for Variable Speed Wind Turbines Providing Frequency Regulation in Isolated Power Systems with Thermal Generation

The lack of synchronous inertia, associated with the relevant penetration of variable speed wind turbines (VSWTs) into isolated power systems, has increased their vulnerability to strong frequency deviations. In fact, the activation of load shedding schemes is a common practice when an incident occurs, i.e., the outage of a conventional unit. Under this framework, wind power plants should actively contribute to frequency stability and grid reliability. However, the contribution of VSWTs to frequency regulation involves several drawbacks related to their efficiency and equipment wear due to electrical power requirements, rotational speed changes, and subsequently, shaft torque oscillations. As a result, wind energy producers are not usually willing to offer such frequency regulation. In this paper, a new control technique is proposed to optimize the frequency response of wind power plants after a power imbalanced situation. The proposed frequency controller depends on different power system parameters through a linear regression to determine the contribution of wind power plants for each imbalance condition. As a consequence, VSWTs frequency contribution is estimated to minimize their mechanical and electrical efforts, thus reducing their equipment wear. A group of sixty supply-side and imbalance scenarios are simulated and analyzed. Results of the case study are compared to previous proposals. The proposed adaptive control reduces the maximum torque and rotational speed variations while at the same time maintaining similar values of the load shedding program. Extensive results and discussion are included in the paper.
Impact of Si and Al on Microstructural Evolution and Mechanical Properties of Lean Medium Manganese Quenching and Partitioning Steels

Herein, the investigation of the tensile behavior of lean medium Mn Quenching and Partitioning (Q&P) steels containing 0.2 wt% C, 4.5 wt% Mn, and additions of 1.5 wt% Si or 1.3 wt% Al is concentrated upon. By the variation of the quenching temperature (TQ), different volume fractions of primary martensite (α′prim) are adjusted, influencing the subsequent microstructural evolution during Q&P processing. Using scanning electron microscopy (SEM), the final microstructure consisting of tempered martensite (α″), retained austenite (RA), partially bainitic ferrite (αB), and final martensite (α′final) is characterized. Furthermore, interrupted tensile tests at gradually increased strains are conducted to investigate the stability of RA against strain‐induced martensite transformation (SIMT) and overall tensile behavior of lean medium Mn Q&P steels. The investigations manifest the formation of larger amounts of αB and consequently lower RA contents, when Si is substituted by Al. As an aftermath, the tendency to form α′final is significantly lower, compared with the Si‐alloyed composition, reflected in the overall stress–strain behavior. Especially in case of the Si‐alloyed samples containing RA fractions exceeding 15 vol%, an over‐accelerated SIMT is observed, inducing failures occurring prior to necking, whereas for the Al‐alloyed samples, a wider process window is obtained.
The phonological Mismatch Negativity and P300 as diagnostic tools in stroke-related aphasia recovery: a longitudinal multiple case study

ABSTRACT Background Recovery from stroke-related aphasia follows different stages, evolving from the acute and subacute phase (< 6 months post stroke) into the chronic phase (> 6 months post stroke). In general, phonology remains tenaciously disturbed, making it a relevant language marker to assess in every stage of recovery. The classical behavioural evaluation of phonological abilities in patients with aphasia can be extended with a registration of event-related potentials (ERPs), for example, the Mismatch Negativity (MMN) and the P300. ERPs have been suggested (1) to contain indications towards the language recovery progress (Nolfe et al. 2006. The role of P300 in the recovery of post-stroke global aphasia. European Journal of Neurology, 13(4), 377–384. https://doi.org/10.1111/j.1468-1331.2006. 01237.x) and (2) to provide additional and (more) sensitive information along with the behavioural results (Aerts, Batens et al. 2015. Aphasia therapy early after stroke: Behavioural and neurophysiological changes in the acute and post-acute phases. Aphasiology, 29(7), 845–871. https://doi.org/10.1080/02687038.2014. 996520). In this longitudinal study, we aimed to corroborate these previous findings. Methods and procedures In four patients with aphasia after a first-ever stroke, we administered behavioural language tasks as well as phonological ERPs in the (sub)acute and in the chronic stage of recovery. Outcomes and results The results demonstrate that the early presence of a P300 could be considered as an indicator of better recovery of language comprehension over time. For the MMN, such an indicative value remains to be confirmed. Moreover, abnormal ERP amplitudes or latencies accompanied behavioural ceiling effects in the chronic stage, suggesting a sensitivity of phonological ERPs for subtle language deficits that could not be detected by the established behavioural instruments. Conclusions The added values of phonological ERPs advocate their implementation in aphasia rehabilitation.
SmartSSD: FPGA Accelerated Near-Storage Data Analytics on SSD

Faced with the increasing disparity between SSD throughput and CPU-based compute capabilities, there have been growing interests to move compute closer to storage and accelerate the data analytic workloads. In this letter, we propose SmartSSD, an SSD with onboard FPGA, which enables offloading computation within SSD. We perform a detailed model-based evaluation to evaluate the end-to-end performance and energy benefit of SmartSSD for the representative data analytic workloads with Spark SQL and Parquet columnar data format. Our evaluation shows that SmartSSD has the potential to have a transformative impact when building a high performance data analytic system, which enables 3.04x performance improvement and consuming only 45.8 percent of energy compared to the conventional CPU-based approach.