Miracle-dz/UniFAR-FTUs huggingface dataset:
Distribution and Biodiversity of Seed-Borne Pathogenic and Toxigenic Fungi of Maize in Egypt and Their Correlations with Weather Variables

Studies of the biodiversity of plant pathogenic and toxigenic fungi are attracting great attention to improve the predictability of their epidemics and the development of their control programs. Two hundred maize grain samples were gathered from 25 maize-growing governorates in Egypt and 189 samples were processed for the isolation and identification of seed-borne fungal microbiome. Twenty-six fungal genera comprising 42 species were identified according to their morphological characteristics and ITS DNA sequence analysis. Occurrence and biodiversity indicators of these fungal species were calculated. Ustilago maydis, Alternaria alternata, Aspergillus flavus, A. niger, Penicillium spp. , Cladosporium spp. and Fusarium verticillioides were the highly frequent (>90% for each), recording the highest relative abundance (˃50%). Al-Menia governorate showed the highest species diversity and richness, followed by Sohag, Al-Nobaria and New Valley governorates. Correlations of 18 fungal species with temperature, relative humidity, precipitation, wind speed, and solar radiation were analyzed using canonical correspondence analysis. Results showed that relative humidity, temperature, and wind speed, respectively, were the most impactful weather variables. However, the occurrence and distribution of these fungi were not clearly grouped into the distinctive climatic regions in which maize crops are grown. Monitoring the occurrence and distribution of the fungal pathogens of maize grains in Egypt will play an important role in predicting their outbreaks and developing appropriate future management strategies. The findings in this study may be useful to other maize-growing countries that have similar climatic conditions.
Machine learning-assisted 1 fluoroscopy of bladder function in 2 awake mice 3

16 Understanding the lower urinary tract (LUT) and development of highly needed novel 17 therapies to treat LUT disorders depends on accurate techniques to monitor LUT 18 (dys)function in preclinical models. We recently developed videocystometry in rodents, which 19 combines intravesical pressure measurements with X-ray-based fluoroscopy of the LUT, 20 allowing the in vivo analysis of the process of urine storage and voiding with unprecedented 21 detail. Videocystometry relies on the precise contrast-based determination of the bladder 22 volume at high temporal resolution, which can readily be achieved in anesthetized or 23 otherwise motion-restricted mice but not in awake and freely moving animals. To overcome 24 this limitation, we developed a machine-learning method, in which we trained a neural 25 network to automatically detect the bladder in fluoroscopic images, allowing the automatic 26 analysis of bladder filling and voiding cycles based on large sets of time-lapse fluoroscopic 27 images (>3 hours at 30 images/second) from behaving mice and in a non-invasive manner. 28 With this approach, we found that urethane, an injectable anesthetic that is commonly used 29 in preclinical urological research, has a profound, dose-dependent effect on urethral 30 relaxation and voiding duration. Moreover, both in awake and in anaesthetized mice, the 31 bladder capacity was decreased ~4-fold when cystometry was performed acutely after 32 surgical implantation of a suprapubic catheter. Our findings provide a paradigm for the non- 33 invasive, in vivo monitoring of a hollow organ in behaving animals and pinpoint important 34 limitations of the current gold standard techniques to study the LUT in mice. 50% at the highest voiding urethane- mice, the suppressive effect of urethane on voiding fatigue of the detrusor muscle in the course of the experiment Detailed analysis of individual voids allowed us to attribute the reduction in voiding efficiency to both shorter void durations and a reduction in maximal UFC. These results indicate that urethane reduces the duration and extent of urethral relaxation during a void, leading to a pronounced reduction in voiding efficiency. Throughout these experiments, we that animals the lowest dose urethane (0.3 g/kg) were awake and behaving, but displayed a more tranquil behavior than non-anesthetized animals. Likewise, both pressure and volume artefacts in these animals treated with 0.3 g/kg, and there was a trend for larger BC, longer ICI and increased UFR and UFC the analgesia
Maximum Subbarcode Matching and Subbarcode Distance

We investigate the maximum subbarcode matching problem which arises from the study of persistent homology and introduce the subbarcode distance on bar-codes. A barcode is a set of intervals which correspond to topological features in data and is the output of a persistent homology computation. A barcode A has a subbarcode matching to B if each interval in A matches to an interval in B which contains it. We present an algorithm which takes two barcodes, A and B , and returns a maximum subbarcode matching. The subbarcode matching algorithm we present is a generalization of the up-right matching algorithm given by Karp et al [11]. Our algorithm also works on multi-set input. It has O ( n log n ) runtime, where n is the number of distinct intervals in the barcodes. We show that the subbarcode relation is transitive and induces a partial order on barcodes. We introduce subbarcode distance and show that the subbarcode distance is a lower bound for bottleneck distance. We also give an algorithm to compute subbarcode distance, which has expected O ( n log 2 n ) runtime and uses O ( n ) space.
Minimum Enclosing Spherical/Cylindrical Shells in High-Dimensional Streams

Given a point set P in R d , the minimum enclosing spherical (resp., cylindrical) shell problem is to ﬁnd a sphere (resp., a cylinder) best ﬁtting P . We show that in the single-pass streaming model, any algorithm for the minimum enclosing spherical/cylindrical shell problem with an approximation factor better than d 1 / 3 / 4 requires a memory size exponential in d .
PACMem: Enforcing Spatial and Temporal Memory Safety via ARM Pointer Authentication

Memory safety is a key security property that stops memory corruption vulnerabilities. Different types of memory safety enforcement solutions have been proposed and adopted by sanitizers or mitigations to catch and stop such bugs, at the development or deployment phase. However, existing solutions either provide partial memory safety or have overwhelmingly high performance overheads. In this paper, we present a novel sanitizer PACMem to efficiently catch spatial and temporal memory safety bugs. PACMem removes the majority of the overheads by sealing metadata in pointers through the COTS hardware feature -- ARM PA (Pointer Authentication) and saving the overhead of pointer metadata tracking. We have developed a prototype of PACMem and systematically evaluated its security and performance on the Magma, Juliet, Nginx, and SPEC CPU2017 test suites. In our evaluation, PACMem shows no false positives together with negligible false negatives, while introducing stronger bug detection capabilities and lower performance overheads than state-of-the-art sanitizers, including HWASan, ASan, SoftBound+CETS, Memcheck, LowFat, and PTAuth. Compared to the widely deployed ASan, PACMem has no false positives and much fewer false negatives and reduces the runtime overheads by 15.80% and the memory overheads by 71.58%.
Measuring Welfare with Income E ff ects using Cross-Sectional Data

We show how to recover the money-metric utility function, which converts income at one point in time into equivalent income at another point in time, using repeated cross-sectional household level data. Our procedure allows unrestricted preferences, but requires that households’ preferences be the same in both the cross-section and the time-series. Our idea is to trace out Hicksian (or compensated) demand curves through time by matching households on the same indi ff erence curve at di ff erent points in time. Given Hicksian demand curves, we can construct ideal price indices and money-metric utility for every matched income level.
Statistical and SWAT Model-Based Performance Evaluation of RCMsinModelingStreamflowandSedimentYieldatUpperAwash Sub-Basin, Ethiopia

e focus of this study was to evaluate the performance of the regional climate models with regard to simulating streamow, sediment yield, precipitation, and temperatures. It is recognized that RCMs are not free of bias and uncertainty when simulating climate variables. e evaluation was about simulating annual climatology, annual cycles, and annual variability of climate variables by statistical tools and streamow and sediment yield by SWATmodel output. e study used observed and CORDEX Africa-44 meteorological data for RACMO22T, RCA4, CCLM4-8-17, and HIRHAM5 models using grid points. is analysis of the mean annual rainfall cycle in the summer season shows that all RCMs were underestimated. However, RACMO22Tand RCA4 are better suited for simulating climate variables. e higher errors were associated with the simulations of maximum and minimum temperatures in the highest terrain area of the catchment. e statistical analysis with climatology indicates that all RCMwas performed inmuch the same way, except for the seasonal perspective. In this case, RACMO22Twas best able to simulate streamow and sediment yield with PBIAS of 0.14, NSE of 0.91, R of 0.82, R of 0.72, NSE of 0.78, and PBIAS of −2.61%, respectively. RCA4 simulated streamow better, but it underestimated the simulated sediment yield. e result proved that RACMO22T and RCA4 performed better in the upper oodplain area. e performance of the climate model varied with catchments, locations, and terrains. e output of this statistical and SWATmodel shows that climate models do not accurately simulate hydro-climatological variables. Finally, this study showed that climate models were better at simulating the rainy season than the dry season. is integration of statistical tools and the SWAT model to analyze the RCM’s performance is a unique method to improve the quality of the output for its implementation in maintaining water balance and sediment load reduction.
Gallium nitride technology in server and telecom applications The promise of GaN in light of future requirements for power electronics

This paper discusses the benefits of e-mode GaN HEMTs in high power applications such as server power supplies and telecom infrastructure. Compared to the next best silicon alternatives, we quantitatively show how much better systems based on GaN power devices can be. We also provide further insight into corresponding topologies, choice of magnetics, and switching frequencies to take the full benefit of the next generation of power devices.
The three-headed lecturer Perspectives on the lecturer’s role in co-activity in design, art, and craft education

This article discusses education in clay and embroidery and reflects on exercises used for these activities in the Teacher Training Programme in Design, Art, and Crafts at Oslo Metropolitan University, Norway. In the study, the students participated in a practice-based qualitative research project, during which they collaborated in material-based activities. Collaboration and productivity were important for the students’ learning outcomes. They worked with personal and unique artistic expressions. By using co-activity methods, their learning outcomes became enriched. This article includes the students’ reflections on the education and their experiences with co-activity in the practical work. In general, personal qualities, such as participant patience, manual skills, creativity, and artistic abilities, were stimulated through practical teaching and guidance. Furthermore, the discussion between the students, and with the lecturer, became significant for the results of the assignment. Adapting practical teaching is a challenge in academia. Limited time for training and large student groups influence and limit the academic level of learning attained. As lecturers , we experience these challenges. To uncover the lecturers’ distinct roles in progression and interaction in an education context, we use the a/r/tography methodology; artist, researcher, teacher, not only to reflect on and examine the three separate roles but also to understand the connection between these roles and the benefits of combining them.
Estimation of Hydroxyl Radical Exposure in a three-stage Countercurrent Ozone Contactor – Reduction in Musty Odor Compounds and Formation of Bromate

ABSTRACT The Hanshin Water Supply Authority is the first bulk water supplier in Japan that currently operates two drinking water treatment plants. Both plants employ an ozonation process for the reduction of musty odor compounds, 2-methylisoborneol and geosmin, and trihalomethanes. In this study, we aim to estimate hydroxyl radical (HO∙) exposure in a three-stage countercurrent ozone contactor applied at the Inagawa drinking water treatment plant. We estimated the HO∙ exposure as the product of the ozone exposure multiplied by the RCt value, that is, the ratio of the HO∙ exposure to the ozone exposure. The ozone exposure was estimated by a methodology we developed earlier, and the RCt values were experimentally evaluated in this study. The estimated HO∙ exposure ranged from 0.4 × 10−10 to 6.7 × 10−10 M·s across the contactor during our research period. The highest HO∙ exposure of 6.7 × 10−10 M·s indicated that the reduction ratio of musty odor compounds exceeded 95%. At these exposures, the detected concentration of bromate was 6 µg/L, which is equal to the 60% concentration level of Japan’s water quality standard for drinking water. Further, we attempt to balance the reduction in musty odor compounds with control of bromate formation.
Are Lung Ultrasound Features More Severe in Children Diagnosed with Bronchiolitis after the COVID-19 Lockdown Period?

The non-pharmacological measures implemented during the SARS-CoV-2 pandemic disrupted the usual bronchiolitis seasonality. Some authors have speculated that, after the lock down period, there would be an increase in the number and severity of respiratory infections due to the re-introduction of respiratory viruses. We collected clinical, microbiological and lung ultrasound data using the classification of the Italian Society of Thoracic Ultrasound (ADET) in children with bronchiolitis during the pandemic compared to the pre-pandemic period, with the aim of assessing whether the epidemic of bronchiolitis during the pandemic was characterized by a more severe lung involvement documented by lung ultrasound. We enrolled 108 children with bronchiolitis (52 pre-pandemic and 56 COVID-19 period), with a median age of 1.74 months (interquartile range, IQR 1–3.68) and 39.8% were females. Rhinovirus detection and high-flow nasal cannula usage were both increased during the COVID-19 period, although overall need of hospitalization and pediatric intensive care unit admissions did not change during the two periods. Lung ultrasound scores were similar in the two cohorts evaluated. Conclusions: our study suggests that, despite changes in microbiology and treatments performed, lung ultrasound severity scores were similar, suggesting that that bronchiolitis during the pandemic period was no more severe than pre-pandemic period, despite children diagnosed during the pandemic had a higher, but it was not statistically significant, probably, due to small sample size, probability of being admitted.
Machine learning applications in household-level demand prediction

ABSTRACT Machine learning (ML) is becoming one of the most anticipated methods in predicting consumer demand. However, it is still uncertain how ML methods perform relative to traditional econometric methods under different dataset scales. This study estimates and compares the out-of-sample predictive accuracy of household budget share for organic fresh produce using two parametric models and six ML methods under regular and large sample sizes. Results show that ML method, particularly Logistic Elastic Net, performs better than econometric models under regular sample size. Contrarily, when dealing with big data, econometric models reach to same accuracy level as ML methods whereas random forest presents a possible overfitting problem. This study illustrates the competence of ML methods in demand prediction, but choosing the optimal method needs to consider product specifics, sample sizes, and observable features.
The Path of a Cardiac Patient—From the First Symptoms to Diagnosis to Treatment: Experiences from the Tertiary Care Center in Poland

Cardiovascular diseases (CVDs) are major concerns in the healthcare system. An individual diagnostic approach and personalized therapy are key areas of an effective therapeutic process. The major aims of this study were: (1) to assess leading patient problems related to symptoms, diagnosis, and treatment of CVDs, (2) to examine patients’ opinions about the healthcare system in Poland, and (3) to provide a proposal of practical solutions. The 27-point author’s questionnaire was distributed in the Cardiology Department of the Tertiary Care Centre between 2nd September–13th November 2021. A total of 132 patients were recruited, and 82 (62.12%; nmale = 37, 45.12%; nfemale = 45, 54.88%) was finally included. The most common CVDs were arrhythmias and hypertension (both n = 43, 52.44%). 23 (28.05%) patients had an online appointment. Of the patients, 66 (80.49%) positively assessed and obtained treatment, while 11 (13.41%) patients declared they received a missed therapy. The participants identified: (1) waiting time (n = 31; 37.80%), (2) diagnostic process (n = 18; 21.95%), and (3) high price with limited availability of drugs (n = 12; 14.63%) as the areas that needed the strongest improvement. Younger patients more often negatively assessed doctor visits (30–40 yr.; p = 0.02) and hospital interventions (40–50 yr.; p = 0.008). Older patients (50–60 years old) less often negatively assessed the therapeutic process (p = 0.01). The knowledge of the factors determining patient adherence to treatment and satisfaction by Medical Professionals is crucial in providing effective treatment. Areas that require the strongest improvement are: (1) waiting time for an appointment and diagnosis, (2) limited availability and price of drugs, and (3) prolonged, complicated diagnostic process. Providing practical solutions is a crucial aspect of improving CVDs therapy.
Numerical models for Halley dust environments

The algebra, parameter values, and results of a reference model for the dust environment of Comet P/Halley are presented. The model employs simplified treatments of the icy conglomerate nucleus and of the hydrodynamic outflow of gas and dust. The model includes a gas production rate derived from observations of Halley's visual magnitude in 1910, gas and dust flux nonuniformly distributed over the nuclear surface, a dust distribution function consistent with large particle inferences from comet antitails, dust density variable with mass, and an approximation to the distribution of particles near the dust envelope. Many parameter values are derived by analogy with the results for other comets. The features are incorporated in a computer program which calculates the concentration, flux, and fluence of dust particles as functions of time, position and particle mass.
Validation of StepTest4all for Assessing Cardiovascular Capacity in Young Adults

Background: Cardiovascular capacity, expressed as maximal oxygen uptake (VO2max), is a strong predictor of health and fitness and is considered a key measure of physiological function in the healthy adult population. The purpose of this study was to validate a specific step test (StepTest4all) as an adequate procedure to estimate cardiovascular capacity in young adults. Methods: The sample was composed of 56 participants, including 19 women (aged 21.05 ± 2.39 years, body mass = 57.50 ± 6.64 kg, height = 1.62 ± 0.05 m, body mass index = 22.00 ± 2.92 kg/m2) and 37 men (aged 22.05 ± 3.14 years, body mass = 72.50 ± 7.73 kg, height = 1.76 ± 0.07 m, body mass index = 23.34 ± 2.17 kg/m2). Participants were included in one of the following groups: (i) the group used to predict the VO2max, and (ii) the group used to validate the prediction model. All participants performed the StepTest4all protocol. The step height and the intensity of the effort was determined individually. Heart rate and oxygen uptake were measured continuously during rest, effort, and recovery phases. The validation process included the following three stages: (i) mean data comparison, (ii) simple linear regression, and (iii) Bland–Altman analysis. Results: The linear regression retained, as significant predictors of the VO2max, sex (p < 0.001) and heart rate recovery for one minute (p = 0.003). The prediction equation revealed a high relationship between measurements (R2 = 63.0%, SEE = 5.58). The validation procedure revealed non-significant differences (p > 0.05) between the measured and estimated maximal oxygen uptake, high relationship (R2 = 63.3%), and high agreement with Bland–Altman plots. Thus, VO2max can be estimated with the formula: VO2max = 22 + 0.3 · (HRR1min) + 12 · (sex), where HRR1min is the magnitude of the HR decrease (bpm) in one minute immediately after the step was stopped, and sex: men = 1, women = 0. Conclusions: The StepTest4all is an adequate procedure to estimate cardiovascular capacity, expressed as VO2max, in young adults. In addition, it is possible to determine the qualitative level of cardiovascular capacity from the heart rate recovery for one minute, more specifically, poor: <20, moderate: 20 to 34, good: 35 to 49, and excellent: ≥50. This procedure has the benefit of being simple to apply and can be used by everyone, even at home, without specialist supervision.
Varied Bulk Powder Properties of Micro-Sized API within Size Specifications as a Result of Particle Engineering Methods

Micronized particles are commonly used to improve the content uniformity (CU), dissolution performance, and bioavailability of active pharmaceutical ingredients (API). Different particle engineering routes have been developed to prepare micron-sized API in a specific size range to deliver desirable biopharmaceutical performance. However, such API particles still risk varying bulk powder properties critical to successful manufacturing of quality drug products due to different particle shapes, size distribution, and surface energetics, arising from the anisotropy of API crystals. In this work, we systematically investigated key bulk properties of 10 different batches of Odanacatib prepared through either jet milling or fast precipitation, all of which meet the particle size specification established to ensure equivalent biopharmaceutical performance. However, they exhibited significantly different powder properties, solid-state properties, dissolution, and tablet CU. Among the 10 batches, a directly precipitated sample exhibited overall best performance, considering tabletability, dissolution, and CU. This work highlights the measurable impact of processing route on API properties and the importance of selecting a suitable processing route for preparing fine particles with optimal properties and performance.
Dream fusion in octahedral spherical hohlraum

The octahedral spherical hohlraum provides an ideal and practical approach for indirect-drive toward a dream fusion with predictable and reproducible gain and opens a route to the development of a laser drive system for multiple laser fusion schemes. This paper addresses a number of issues that have arisen with regard to octahedral spherical hohlraums, such as how to naturally generate a highly symmetric radiation drive at all times and for all spectra without the use of symmetry tuning technology, how to determine the three-dimensional, temporal, and spectral characteristics of the real radiation drive on a capsule in experiments, and the relative energy efficiency of an octahedral spherical hohlraum compared with a cylindrical hohlraum. A design island for an octahedral spherical hohlraum is presented. Finally, the challenges and future tasks for the path forward are presented.