Miracle-dz/UniFAR-FTUs huggingface dataset:
Endoscopic Assessment Prior to Bariatric Surgery in Saudi Arabia

Background: There are marked local inconsistencies in the Arabian Peninsula about the role of preoperative esophagogastroduodenoscopy (EGD) in bariatric surgery. Thus, this study was conducted to determine the frequency of endoscopic and histological findings in the Saudi population presenting for pre-bariatric surgery evaluation. Material and Methods: This was a retrospective study that included all the patients who were evaluated by EGD at Dammam Medical Complex, Dammam, Saudi Arabia, between 2018 and 2021 as a part of their pre-bariatric-surgery evaluation. Results: A total of 684 patients were included. They consisted of 250 male and 434 female patients (36.5% and 63.5%, respectively). The mean ± standard deviation for the patients' age and body mass index (BMI) were 36.4±10.6 years and 44.6±5.1 kg/m2, respectively. Significant endoscopic or histopathological findings as defined by the presence of large (≥ 2 cm) hiatus hernia, esophagitis, gastroesophageal reflux disease (GERD), Barrett esophagus, gastric ulcer, duodenal ulcer, or intestinal metaplasia were found in 143 patients (20.9%); 364 patients (53.2%) were diagnosed to have Helicobacter pylori infection. Conclusion: The high number of significant endoscopic and histopathological findings in our study supports the routine use of preoperative EGD in all bariatric surgery patients. However, omitting EGD before Roux-en-Y gastric bypass (RYGB) in asymptomatic patients is still reasonable as the most frequently found significant findings, esophagitis, and hiatus hernia, are less likely to impact the operative plans in RYGB. Similarly, active surveillance and treatment of H. pylori infections in obese patients are important but it is not clear whether H. pylori eradication should be done before bariatric surgery.
Fermented Total Mixed Ration Alters Rumen Fermentation Parameters and Microbiota in Dairy Cows

Simple Summary Fermented total mixed ration (FTMR) is an effective method of preserving high-moisture byproducts. However, few studies have investigated the effect of feeding FTMR on the rumen microbiota of dairy cows. This study aimed to determine changes and interactions of ruminal microbiota and chemical parameters in dairy cows fed FTMR. Compared with unfermented total mixed ration (TMR), FTMR improved bacterial and fungal richness and diversity. Meanwhile, the ruminal acetate and NH3-N concentration were increased. The prediction of the metabolic function of the flora showed that FTMR could increase lipid and amino acid metabolism. Abstract This study aimed to determine changes and interactions of ruminal microbiota and chemical parameters in dairy cows fed FTMR. Twelve multiparous Holstein dairy cows (Body weight = 616 ± 13.4 kg; day in milk = 106 ± 7.55 d; and parity = 2.31 ± 0.49; mean ± standard deviation) were divided randomly into two treatments depending on the day in milk, milk production, and parity. The two treatments were: (1) total mixed ration (TMR) and (2) FTMR. Illumina MiSeq sequencing was used to explore the changes in the ruminal microbiota. The results revealed that the bacterial and fungal diversity of the FTMR group were significantly higher than the TMR group. The predominant microbiota phyla in the bacteria and fungi showed significant differences between TMR and FTMR, as follows: Verrucomicrobia (p = 0.03) and Tenericutes (p = 0.01), Ascomycota (p = 0.04) and Basidiomycota (p = 0.04). The dominant bacterial genera in the bacteria, fungi, protozoan, and archaea that showed significant differences between TMR and FTMR were Unclassified_Bacteroidales (p = 0.02), Unclassified_RFP12 (p = 0.03), Candida (p = 0.0005), Bullera (p = 0.002), Cryptococcus (p = 0.007), and Ostracodinium (p = 0.01). LefSe analysis was performed to reveal the biomarker genera of the rumen microbiota community (bacteria, fungi, protozoan, and archaea) in the TMR and FTMR were the genera Shuttleworthia, Ruminococcus, Cryptococcus, Mycosphaerella, Bullera, Candida, and Ostracodinium. NH3-N concentration (p < 0.0001), total VFA concentration (p = 0.003), and molar proportion in total VFA of acetate (p = 0.01) were higher for the cows fed FTMR compared with the cows fed the TMR. Several bacterial genera showed significant correlations with rumen fermentation parameters. The genus Unclassified_Bacteroidales and Bullera were positively correlated with total volatile fatty acids (VFA) and acetate, whereas Candida and Ostracodinium showed negative correlations. Meanwhile, propionate was positively correlated with Candida and negatively correlated with Bullera. The PICRUSt functional profile prediction indicated that the xenobiotics biodegradation and metabolism, the lipid, amino acid, terpenoids, and polyketides metabolisms of the FTMR group were significantly higher than that of the TMR group. The results imply that FTMR can increase lipid and amino acid metabolism, and modulate the rumen microbiome and improve ruminal fermentation.
Video Relationship Detection Using Mixture of Experts

Machine comprehension of visual information from images and videos by neural networks suffers from two limitations: (1) the computational and inference gap in vision and language to accurately determine which object a given agent acts on and then to represent it by language, and (2) the shortcoming in stability and generalization of the classifier trained by a single, monolithic neural network. To address these limitations, we propose MoE-VRD, a novel approach to visual relationship detection via a mixture of experts. MoE-VRD recognizes language triplets in the form of a < subject, predicate, object > tuple to extract the relationship between subject, predicate, and object from visual processing. Since detecting a relationship between a subject (acting) and the object(s) (being acted upon) requires that the action be recognized, we base our network on recent work in visual relationship detection. To address the limitations associated with single monolithic networks, our mixture of experts is based on multiple small models, whose outputs are aggregated. That is, each expert in MoE-VRD is a visual relationship learner capable of detecting and tagging objects. MoE-VRD employs an ensemble of networks while preserving the complexity and computational cost of the original underlying visual relationship model by applying a sparsely-gated mixture of experts, which allows for conditional computation and a significant gain in neural network capacity. We show that the conditional computation capabilities and massive ability to scale the mixture-of-experts leads to an approach to the visual relationship detection problem which outperforms the state-of-the-art.
A Dozen Hat Problems

H at problems are all the rage these days, proliferating on various web sites and generating a great deal of conversation-and research-among mathematicians and students. But they have been around for quite a while in different forms. For example, a variant of Problem 3 shows up in Puzzle-Math by George Gamow and Marvin Stern (The Viking Press, 1958; pp. 77-78) as a question about three travelers with dirty faces. (This was EB's introduction to the field.) Martin Gardner also wrote about them in Aha! Insight (W.H.Freeman & Co., 1978). In all these problems hats of specified colors are placed on players' heads. Each can see the colors of some or all of the other player's hats, but not his own, and the goal of the problem is to provide a strategy players' can agree on before the play of the game that will allow some maximal number of players to correctly guess the colors of their hats. Incorrect guesses might be ignored, or might lead to severe punishments! Players are not allowed to communicate with each other during play of the game and may only speak a single word-a guess as to the color of one's own hat-if a game permits any speaking at all! Some of these problems are psychological or philosophical and many are deeply mathematical. At the very least, they are fun to think about. Enjoy!
New fast response photofragment fluorescence hygrometer for use on the NASA ER‐2 and the Perseus remotely piloted aircraft

We have developed an in situ instrument to measure water vapor on the NASA ER‐2 as a prototype for use on the Perseus remotely piloted aircraft. It utilizes photofragment fluorescence throughout the stratosphere and the upper to middle troposphere (mixing ratios from 2 to 300 ppmv) with simultaneous absorption measurements in the middle troposphere (water vapor concentrations ≳5×1014 mol/cc). The instrument flew successfully on the NASA ER‐2 aircraft during the 1993 CEPEX and SPADE campaigns. The 2σ measurement precision for a 10 s integration time, limited by variation in the background from scattered solar radiation, is ±6% and the data were tightly correlated with other long‐lived stratospheric tracers throughout the SPADE mission. Its accuracy is estimated to be ±10%, based on laboratory calibrations using a range of water vapor concentrations independently determined by both standard gas addition techniques and by absorption. This accuracy is confirmed by in‐flight absorption measurements in the trop.
Asympotic study of the multivariate functional model. application to the metric choice in principal component analysis

The least squares estimation of the parameters of the functional models in ( , M) where M is a symmetric positive definite p × p matrix that defines a quadratic metric on ( , amounts to a Principal Component Analysis (PCA) of order qin ( , M. We assume that the errors are independent and have identical moments up to order 6. We study the almost sure convergence of the estimators and prove that they are consistent if and only if M = kΓ-1 (k > 0) where Γ is the known covariance matrix of the errors. This result is a property of a Gauss-Markov type for PCA and give insight into the choice of metric in PCA. We study the asymptotic distributions of these estimators. When M = Γ-1 and the errors are elliptical, in particular Gaussian, we give explicitly the covariance operators of the Gaussian limiting distributions and show applications to statistical inference.
On a mixed finite element formulation of a second‐order quasilinear problem in the plane

We analyze a mixed finite element discretization of a second‐order quasilinear problem based on the Raviart‐Thomas space. We prove that the discrete problem is solvable and provide a local uniqueness result for the solution. We also obtain optimal order L2‐error estimates for both the scalar variable and the associated flux. The main feature of our method is that it is free from the boundness conditions required in previous works on the coefficients of the quasilinear operator. © 2003 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 20: 90–103, 2004.
Economic freedom influences economic growth and unemployment: an analysis of the Eurozone

Lack of economic growth and a high unemployment rate imply poverty and inequality. Economic freedom is considered a relevant explanatory factor for growth, employment and the distribution of income. The present research work addresses how policy makers should take into account economic freedom aspects to effectively enhance a country ’ s economic growth and lower its unemployment rate. This study analyses the effect of four components of economic freedom (business freedom, labour freedom, government integrity, tax burden) on the mean GDP growth of the last 5years, and also on unemployment. A cross-national analysis, based on data from the 23 Eurozone3 (Eurozone and part of its enlargement) Member Countries, examines the causal configurations of GDP and unemployment by a fuzzy-set qualitative comparative analysis. The results suggest that the combination of high levels of business freedom, labour freedom and government integrity triggers high levels of economic growth and lowers the unemployment rate.
Investigation of cluster growth in MR fluids using ultrasonic wave propagation

This research reports the experimental results of a study on cluster growth in Magneto-rheological (MR) fluid. The experiments were conducted by applying different magnetic field (M/F) sweep rates to MR fluid. A magnetic field was swept from 0 to 400 mT at different times. Since the MR fluid is opaque, an ultrasonic measurement method was applied. Ultrasonic propagation velocity (V) in MR fluid is dependent on magnetic field and is strongly related to cluster formation in this fluid. Therefore, ultrasonic propagation velocity was measured and the change of ultrasonic propagation velocity (ΔV/V0) was calculated. Based on the experimental results, cluster growth in MR fluids can be analyzed experimentally. Effect of volume fraction in MR fluid on cluster growth is presented. Furthermore, the relation between the change of ultrasonic propagation velocity and M/F sweep rate is discussed.
Acoustic resonances in a high-lift configuration

Low- and high-frequency acoustic resonances are computed numerically via a high-order finite-element code for a generic two-dimensional high-lift configuration with a leading-edge slat. Zero mean flow is assumed, approximating the low-Mach-number situation at aircraft landing and approach. To avoid unphysical reflections at the boundaries of the truncated computational domain, perfectly matched layer absorbing boundary conditions are implemented in the form of the complex scaling method of atomic and molecular physics. It is shown that two types of resonance exist: resonances of surface waves which scale with the total airfoil length and longitudinal cavity-type resonances which scale with the slat cove length. Minima exist in the temporal decay rate which can be associated with the slat cove resonances and depend on the slat cove geometry. All resonances are damped owing to radiation losses. However, if coherent noise sources exist, as observed in low-Reynolds-number experiments, these sources can be enhanced acoustically by the above resonances if the source frequency is close to a resonant frequency.
Criticality-Aware Negotiation-Driven Scrubbing Scheduling for Reliability Maximization in SRAM-Based FPGAs

Memory scrubbing is a resource-efficient technique to ensure the high reliability of SRAM-based FPGAs by refreshing the configuration memory just before its execution. To maximize reliability, a scrubbing scheduling algorithm is expected to scrub as many tasks as possible. Unfortunately, contemporary scheduling algorithms either suboptimally handle scrubbing conflicts under bursty requests from multiple user tasks or discriminate against low-criticality tasks by giving them very low scrubbing opportunities. Besides, exploring the architectural support for scrubbing problems may bring considerable potential for reliability improvements. However, this direction of scheduling-architecture co-optimization has not been well studied so far. In this article, we propose a negotiation-based dynamic scrubbing framework, which addresses the above-mentioned issues in three phases: 1) we propose a negotiation-driven scrubbing scheduling algorithm, which temporarily allows and iteratively reduces the conflicts of scrubbing tasks in order to accommodate more scrubbing tasks to be scheduled; 2) we develop a logistic probability model to prevent scheduling starvation of a set of mix-criticality tasks by dynamically legalizing conflicting ones, considering both the criticality and schedulability of each task; and 3) we develop a dynamic voltage/frequency scaling-based multi-ICAPs allocation algorithm to co-optimize with FPGA architectural features for reliability maximization. Compared to the state-of-the-art, experimental results show that our work achieves up to 31.46% improvement in terms of reliability for contemporary SRAM-based FPGAs.
Exploring the Potential of Gaofen-1/6 for Crop Monitoring: Generating Daily Decametric-Resolution Leaf Area Index Time Series

High spatiotemporal resolution time series of leaf area index (LAI) are essential for monitoring crop dynamics and validating coarse-resolution LAI products. The optical satellite sensors at decametric resolution have historically suffered from a long revisit cycle and cloud contamination issues that hampered the acquisition of frequent and high-quality observations. The 16-m/four-day resolution of the new-generation Gaofen-1 (GF-1) and Gaofen-6 (GF-6) satellites provide an unprecedented opportunity to address these limitations. Here, we developed an effective strategy to generate daily 16-m LAI maps combining GF-1/6 data and ground LAINet measurements. All high-quality GF-1/6 observations were utilized first to derive smoothed time series of vegetation indices (VIs). Second, a random forest regression (RF-r) model was trained to link the VIs with corresponding field LAI measurements. The trained RF-r was finally employed to generate the LAI maps. Results demonstrated the reliability of the reconstructed daily VIs (relative error (RE) < 1%) and the derived LAI time series, which greatly benefited from GF-1/6 high-frequency observations. The direct comparison with field LAI measurements by LAI-2200/LI-3000 showed the good performance of retrieved LAI maps, with bias, root mean square error (RMSE), and $R^{\mathbf {2}}$ of 0.05, 0.59, and 0.75, respectively. The LAI time series well captured the spatiotemporal variation of crop growth. Furthermore, the continuous GF-1/6 LAI maps outperformed Sentinel-2 LAI estimates both in terms of temporal frequency and accuracy. Our study indicates the potential of GF-1/6 to generate continuous decametric-resolution LAI maps for fine-scale agricultural monitoring.
Bovine progressive degenerative myeloencephalopathy ('weaver') of Brown Swiss cattle I

An epidemiological survey of this nervous disorder of the Brown Swiss breed in the USA did not implicate any geographical or environmental factors. There was no sex predilection. The number of recorded cases increased from four in 1972-76 to 46 in 1977-81. There were 32 cases in 1982-83. Breeding records from over half the cases indicated a familial pattern involving five sires. Studies on 32 affected purebred Brown Swiss cattle obtained from dairy farms throughout the USA are described. Owners supplied histories and breeding records, and blood typing was carried out to confirm parentage. The criteria used to establish a clinical diagnosis were: onset of bilateral hind leg weakness and ataxia between 5 and 8 months of age; deficient proprioceptive reflexes, normal motor and sensory reflexes, with no other clinically detectable neurological abnormality; and absence of clinically significant skeletal or muscular abnormality. Familial relationship was also taken into account. Laboratory studies included at least one blood count, routine serum chemistry, serum enzyme levels, and analysis of CSF, and selected cattle were screened for toxicological abnormalities. Three sires were incriminated in 48.6% of the cases, and one was incriminated in 31.4%. Laboratory analyses revealed no abnormal haematological parameters. Although increased activities of certain serum enzymes were found, these were not considered specific. CSF samples from two cases showed CPK activity. Toxicological analyses of cholinesterase activity and blood Cu levels were not significant.
Low-noise hybrid integrated frequency-agile laser and soliton microcomb for FMCW LiDAR

We demonstrate a fully packaged hybrid integrated laser and a soliton microcomb with frequency actuation bandwidth of more than 10 MHz and ultra-low laser frequency noise. The flat frequency response in the range of >1 MHz and the optical laser frequency chirp range of >1 GHz are compatible with high-resolution continuous wave frequency modulated distance ranging and distributed fiber optic sensing without any linearization or pre-distortion. The features of a novel laser system assembled in 14-pin butterfly package are enabled by the ultra-low loss silicon nitride platform and monolithically integrated piezo-electric actuators.
Eurypsychrophilic acidophiles: From (meta)genomes to low-temperature biotechnologies

Low temperature and acidic environments encompass natural milieus such as acid rock drainage in Antarctica and anthropogenic sites including drained sulfidic sediments in Scandinavia. The microorganisms inhabiting these environments include polyextremophiles that are both extreme acidophiles (defined as having an optimum growth pH < 3), and eurypsychrophiles that grow at low temperatures down to approximately 4°C but have an optimum temperature for growth above 15°C. Eurypsychrophilic acidophiles have important roles in natural biogeochemical cycling on earth and potentially on other planetary bodies and moons along with biotechnological applications in, for instance, low-temperature metal dissolution from metal sulfides. Five low-temperature acidophiles are characterized, namely, Acidithiobacillus ferriphilus, Acidithiobacillus ferrivorans, Acidithiobacillus ferrooxidans, “Ferrovum myxofaciens,” and Alicyclobacillus disulfidooxidans, and their characteristics are reviewed. Our understanding of characterized and environmental eurypsychrophilic acidophiles has been accelerated by the application of “omics” techniques that have aided in revealing adaptations to low pH and temperature that can be synergistic, while other adaptations are potentially antagonistic. The lack of known acidophiles that exclusively grow below 15°C may be due to the antagonistic nature of adaptations in this polyextremophile. In conclusion, this review summarizes the knowledge of eurypsychrophilic acidophiles and places the information in evolutionary, environmental, biotechnological, and exobiology perspectives.
Adaptive optimal decompositions with hybrid DCT-subband coding

A generalization of the discrete wavelet transform, i.e., the hybrid subband coding decomposition is introduced. It consists of the application of adequate invertible operators at each level of decomposition (inner-and inter-subbands) before application of the next level of decomposition. An important application is hybrid discrete cosine-transform (DCT)-subband coding, which produces optimal local (in time or frequency) decorrelation of the coefficients of decomposition. <<ETX>>
A Tiny Accelerator for Mixed-Bit Sparse CNN Based on Efficient Fetch Method of SIMO SPad

Convolution neural networks (CNNs) have been implemented with custom hardware on edge devices since its algorithms were successful in many artificial intelligence applications. Although lots of unstructured pruning and mix-bit quantization algorithms have been proposed to successfully compress CNNs, there are few hardware accelerators which can support both sparse and mix-bit CNNs. Besides, sparse matrix computation consumes lots of hardware resources such as registers or BRAM to fetch the needed input activations into processing element (PE). This brief presents a tiny accelerator for mixed-bit sparse CNNs featuring a novel scheme of single vector-based compressed sparse filter (CSF) method and single input multiple output scratch pad (SIMO SPad) to effectively compress weight and fetch the needed input activation. SIMO SPad is shared by multiple PEs, which saves 13.34% CLB LUTs, 46.24% CLB Registers. Furthermore, the accelerator supports mixed-bit sparse computation to obtain better accuracy and performance. When tested on VGG16, compared with 8-bit non-sparsity baselines, the performance of mixed-bit sparsity on Cifar10 and ImageNet improved by <inline-formula> <tex-math notation="LaTeX">$4.85\times $ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$3.33\times $ </tex-math></inline-formula>, respectively, with small accuracy decrease degradation. Compared to state-of-the-art accelerators, the accelerator achieves <inline-formula> <tex-math notation="LaTeX">$1.40\times $ </tex-math></inline-formula> to <inline-formula> <tex-math notation="LaTeX">$2.98\times $ </tex-math></inline-formula> greater DSP efficiency, and offers <inline-formula> <tex-math notation="LaTeX">$1.91\times $ </tex-math></inline-formula> greater energy efficiency.