Miracle-dz/UniFAR-FTUs huggingface dataset:
Antibiotic susceptibility Patterns against Upper Respiratory Tract Pathogens in Tertiary Care Hospitals of Lahore, Pakistan CURRENT STATUS: POSTED

Backgrounds In Pakistan, despite the surge in antibiotic consumption scanty of literature evidences exist regarding antibiotic susceptibility patterns in URTIs. Thus, we conducted the study to evaluate the antibiotic susceptibility patterns in URTIs. Methods A cross-sectional study was conducted by collecting 259 culture samples from tertiary care hospitals of Lahore, Pakistan. Using simple random sampling, culture reports of even numbered patient were included as per study inclusion criteria. Results Two hundred sixty samples were processed out of which only 144 (55.4%) samples yielded growth, i-e. , 42.7% males and 49% females. In males, the resistance was high against ceftazidime (19.3%), ampicillin (13.1%), ciprofloxacin (11.6%) and gentamicin (10.8%), while in female samples it was significant against cefuroxime (6.9%), ampicillin (5.4%), tobramycin (4.6%) and ciprofloxacin (6.5%). Besides, males were sensitive against imepenem (25.8%), amikacin (22%), ceftazidime (19.3%), ciprofloxacin (19.3%) and piptaz (16.2%), while females were sensitive against amikacin (9.2%), imepenem (9.2%) and ciprofloxacin (6.9%). Overall, carbepenems, imipenem (35%) and meropenem (30.8%), were found highly sensitive followed by aminoglycosides (amikacin; 31.9%), quinolones (ciprofloxacin; 26.3%), piptaz (19.2%) among penicillin and cephalosporin, while resistant was maximum against cephalosporin (ceftazidime; 25.4%) followed by penicillin (ampicillin, 18.5%) and quinolones. Conclusion These data suggested that P. , were
Molecular and biochemical characterisation of antagonistic mechanisms of the biocontrol agent Bacillus cereus B25 inhibiting the growth of the phytopathogen Fusarium verticillioides P03 during their direct interaction in vitro

ABSTRACT Fusarium verticillioides (Fv) is a mycotoxin-producing phytopathogen causing ear and root rot in maize. Bacillus cereus strain B25 is a maize endophyte and an effective biological control agent against Fv. The B25 genome contains several genes associated with fungal antagonism, including lytic enzymes (chitinases A and B, chitosanase and glycoside hydrolase), siderophores (petrobactin and bacillibactin), antibiotics (surfactin), and biofilm. This study aimed to elucidate which B25 antagonistic mechanisms are implicated in Fv biocontrol. The expression of twelve B25 genes was evaluated by qRT-PCR after 3–30 h of confrontation between B25 and Fv. All B25 genes tested were induced, mainly between 6 and 24 h, while none was induced at 3 h. Lytic enzyme genes were induced at different times, with three of them occurring at 12 h. Chitinase and chitosanase activities were induced after 6 and 12 h, respectively, and gradually increased until 30 h. Biofilm formation was detected only when B25 interacted with Fv. Images of the B25-Fv interaction and measurements at 24 and 30 h showed little branching or abnormal mycelial growth, suggesting cell wall damage. In conclusion, when B25 is confronted against Fv, all B25 antagonistic mechanisms tested appear to be involved in Fv growth control.
A stochastic mine planning approach to determine the optimal open pit to underground mining transition depth – case study at the Geita gold mine, Tanzania

Several of the world's largest open-pit mines are expected to consider making a transition to underground mining because of the opportunity to access an increased amount of reserves and extend a mine's life. A case study exploring the optimal transition depth from open pit to underground mining at AngloGold Ashanti's Geita gold mine in Tanzania is presented herein. The approach considered assesses the problem by evaluating the profits of a set of candidate transition depths, which have been identified by the mining operation as viable opportunities. An accurate valuation for each candidate's transition depth is derived by producing yearly mine plans based on uncertainty, which outline expected yearly cash flows. Compared with the conventional deterministic approach, the results of this study show a 23% net present value increase for the stochastic mine plans, as well as an improved production performance and the ability to meet mill requirements throughout the life-of-mine.
Unitarity of supersymmetric SL(2, )/U(1) and no-ghost theorem for fermionic strings in AdS 3 ×

: The unitarity of the NS supersymmetric coset SL(2 ; R ) = U(1) is studied for the discrete representations. The results are applied to the proof of the no-ghost theorem for fermionic strings in AdS 3 £ N in the NS sector. A no-ghost theorem is proved for states in (cid:176)owed discrete representations.
Effects of various components of artificial diets on survival, development and reproduction of Coccinella septempunctata L. (Coleoptera: Coccinellidae)

ABSTRACT The ladybird beetle, Coccinella septempunctata, is an important predator of soft-bodied insects. To further optimise an artificial diet for rearing the ladybird beetle, we investigated the effects of juvenile hormone (JH), honey, shrimp, rape pollen, lard, and other factors on the biological characteristics of C. septempunctata. Survival and pupation rates of larvae were decreased when JH and lard were added to the artificial diet; however, the addition of lard increased egg hatching to 73.70%, which was significantly higher than the control diet (50.56%). Adding honeybee pupae to the artificial diet shortened the preoviposition period to 7.64 d, compared to 10.36 d in the control diet. Adding honey, shrimp, and honeybee pupae to the diet resulted in 465.12, 452.35, and 423.01 eggs laid, respectively, which was significantly higher than the control diet. The pupation and emergence rates of C. septempunctata larvae fed an artificial diet without JH were significantly higher than those fed an artificial diet with JH; thus, JH and lard should not be added to artificial diets during the larval stage. During the adult stage, adding rape pollen, shrimp, honey, lard, and honeybee pupae to the diet could improve the fecundity of C. septempunctata. These results will be helpful for optimising artificial diets for the mass production of C. septempunctata.
New Approaches to Contrastive Linguistics: Empirical and Methodological Challenges

This volume is a selection of papers presented in Zürich reflecting on the worth and feasibility of theories, types of empirical data and advanced research methods in contrastive linguistics. It focuses on the nature of empirical data used in contrastive approaches and the advanced quantitative methods and procedures applied in contrastive research. It also explores the application of multivariate analytical techniques contributing to the quantitative contrastive toolbox. This volume, consisting of nine chapters, gives insights into how developments in theory and in the application of advanced research methods are making the field of contrastive linguistics more representative.
Platinum Plus Gemcitabine as the Most Effective Regimen in the First Line of Chemotherapy in Advanced Squamous Cell Lung Cancer

Purpose: Platinum-based doublet chemotherapy had been the standard first-line treatment for advanced NSCLC, regardless of histologic subtypes. We report overall survival (OS) and time to treatment failure (TTF) in patients with squamous cell lung cancer (SCC) receiving doublet of platinum. Patients and methods: Patients (N = 82) with advanced NSCLC received doublet of platinum. Sixty five (79,2%) patients were treated with a combination of platinum plus gemcitabine and 17 (20,7%) received microtubules inhibitor (3 patients were treated with vinorelbine, 3 patients with docetaxel and 11 patients with paclitaxel). Results: Median TTF was 2,53 months CI 95% [2,21 – 2,84] and median OS was 8,246 months CI 95% [5,8 –2,6]. Regarding doublet of chemotherapy, in patients in which gemcitabine was used there was an improvement in TTF of 1,2 months (p= 0,107; log rank) and 4,75 months in OS (p= 0,018; log rank). Conclusion: Gemcitabine plus platinum must be the chemotherapy of ghoice in advanced SCC. Randomized clinical trials with gemcitabine in advanced SCC are needed.
ATS-6 attenuation diversity measurements at 20 and 30 GHz

The results of data obtained at The University of Texas at Austin in conjunction with the ATS-6 millimeter wave experiment are presented. Attenuation measurements at 30 GHz and sky noise data at 20 GHz were obtained simultaneously at each of two sites separated by 11 km. Space diversity reduces outage time for a system in Austin, Texas with a 10 dB fade margin at 30 GHz from 15 hours to 16 minutes per year. The maximum cloud height shows a good correlation to the maximum attenuations measured.
Recursive deep learning for natural language processing and computer vision

As the amount of unstructured text data that humanity produces overall and on the Internet grows, so does the need to intelligently process it and extract different types of knowledge from it. My research goal in this thesis is to develop learning models that can automatically induce representations of human language, in particular its structure and meaning in order to solve multiple higher level language tasks. There has been great progress in delivering technologies in natural language processing such as extracting information, sentiment analysis or grammatical analysis. However, solutions are often based on different machine learning models. My goal is the development of general and scalable algorithms that can jointly solve such tasks and learn the necessary intermediate representations of the linguistic units involved. Furthermore, most standard approaches make strong simplifying language assumptions and require well designed feature representations. The models in this thesis address these two shortcomings. They provide effective and general representations for sentences without assuming word order independence. Furthermore, they provide state of the art performance with no, or few manually designed features. The new model family introduced in this thesis is summarized under the term Recursive Deep Learning. The models in this family are variations and extensions of unsupervised and supervised recursive neural networks (RNNs) which generalize deep and feature learning ideas to hierarchical structures. The RNN models of this thesis obtain state of the art performance on paraphrase detection, sentiment analysis, relation classification, parsing, image-sentence mapping and knowledge base completion, among other tasks. Chapter 2 is an introductory chapter that introduces general neural networks.
A Write-Related and Read-Related DRAM Allocation Strategy Inside Solid-State Drives (SSDs)

Although NAND flash memory has the advantages of small size, low-power consumption, shock resistance, and fast access speed, NAND flash memory still faces the problems of “out-of-place updates,” “garbage collection,” and “unbalanced execution time” due to its hardware limitations. Usually, a flash translation layer (FTL) can maintain the mapping cache (in limited DRAM space) to store the frequently accessed address mapping for “out-of-place updates” and maintain the read/write buffer (in limited DRAM space) to store the frequently accessed data for “garbage collection” and “unbalanced execution time”. In this article, we will propose a write-related and read-related DRAM allocation strategy inside solid-state drives (SSDs). The design idea behind the write-related DRAM allocation method is to calculate the suitable DRAM allocation for the write buffer and the write mapping cache by building a statistical model with a minimum expected value of writes for NAND flash memory. To further reduce reads in NAND flash memory, the design idea behind the read-related DRAM allocation method is to adopt a cost-benefit policy to reallocate the proper DRAM space from the write buffer and the write mapping cache to the read buffer and the read mapping cache, respectively. According to the experimental results, we can demonstrate that the proposed write-related and read-related DRAM allocation strategy can reduce more reads/writes in NAND flash memory than other methods to improve the response time.
The influence of body orientation relative to gravity on egocentric distance estimates in virtual reality

Virtual reality head mounted displays (VR-HMD) can immerse individuals into a variety of virtual environments while accounting for head orientation to update the virtual environment. VR-HMDs also allow users to explore environments while maintaining different body positions (e.g. sitting and laying down). How discrepancies between real world body position and the virtual environment impact the perception of virtual space or, additionally, how a visual upright with incongruent changes in head orientation affects space perception within VR has not been fully defined. In this study we sought to further understand how changes in head-on-body orientation (laying supine, laying prone, laying on left side and, being upright) while a steady visual virtual upright is maintained can affect the perception of distance. We used a new psychophysics perceptual matching based approach with two different probe configurations (“L” & “T” shape) to extract distance perception thresholds in the four previously mentioned positions at egocentric distances of 4, 5, and 6 virtual meters. Our results indicate that changes in observer orientation with respect to gravity impact the perception of distances with a virtual environment when it is maintained at a visual upright. Here we found significant differences between perceived distances in the upright condition compared to the prone and laying on left side positions. Additionally, we found that distance perception results were impacted by differences in probe configuration. Our results add to a body of work on how changes in head-on-body orientation can affect the perception of distance, while stressing that more research is still needed to fully understand how these changes with respect to gravity affect the perception of space within virtual environments.
Exploring the Use of Different Linguistic Phenomena for Sexism Identification in Social Networks

This paper presents the participation of the SINAI-TL team in the shared task sEXism Identification in Social neTworks at IberLEF 2022 for both English and Spanish. Our goal is to observe which interactional phenomena of sexism expression can help in the detection of this content. To transfer this idea to an automatic Natural Language Processing system, we developed a multi-task learning approach involving different linguistic phenomena, such as emotions, sentiments, sarcasm, insults, constructiveness and targets. We compared the results of this approach with a state-of-the-art benchmark model based on the BERT architecture. Our team ranked fourth in subtask 1 among the 44 runs submitted by the participants, achieving an accuracy score of 78.45%. presented our participation as SINAI-TL team in the second edition of the task sEXism Identification in Social neTworks at IberLEF 2022. We have explored whether different linguistic phenomena that might be related to sexist expression could help to detect this problem. The experiments have been conducted in two languages: English and Spanish. Our results show that there are two important factors to consider while addressing this task in both languages: the linguistic phenomena considered and the datasets selected. For Spanish, we found that taking into account emotions, sentiments, and sarcasm knowledge helps the detection of sexism. For English, the phenomena studied have not shown any improvement
The Riemann problem for the Chaplygin gas equations with a source term

The Riemann solutions for the one‐dimensional Chaplygin gas equations with a Coulomb‐like friction term are constructed explicitly. It is shown that the delta shock wave appears in the Riemann solutions in some certain situations. The generalized Rankine‐Hugoniot conditions of delta shock wave are established and the position, propagation speed and strength of delta shock wave are given, which enables us to see the influence of Coulomb‐like friction term on the Riemann solutions for the Chaplygin gas equations clearly. In addition, the relations connected with the area transportation are derived which include mass and momentum transportation.
Impact of radiative decay on cosmic string dynamics at small scales

Cosmic strings are topological defects appearing as extended solutions in many high energy physics scenarios. Observation of signatures expected due to the presence of cosmic string networks could provide critical evidence in distinguishing and constraining fundamental cosmological and particle physics theories. Large scale evolution of cosmic string is well understood but the dynamics influenced by small scale structure remains unclear. Radiation back-reaction is expected to smooth strings, setting the scale of small structure and the size of loops produced. We undertake an investigation of cosmic strings numerically simulated from their underlying field theories, in particular we use the U(1) gauge theory of the Abelian-Higgs model which radiates to massive modes and the global U(1) theory of the Goldstone model which additionally radiates into the massless mode of the Goldstone field. By comparison to the emission of Goldstone bosons we can infer the effects of gravitational radiation, a further important energy loss mechanism for cosmological string, but difficult to simulate. We analyse the scaling properties of the string tangent vector correlation function and loop number density distributions which are expected to follow related power law forms and compare the results for gauge and global strings with a view to deciphering the influence of a massless degree of freedom on these attributes of network evolution. We find that the change in correlation function due to a massless mode can be incorporated by an effective value for the exponent of time by which the scale factor evolves whereby the smoothing due to back-reaction behaves like additional causal damping. From long gauge strings we find no evidence for direct ‘core’-sized loop production, finding instead that our simulations favour radiation into the gauge and Higgs modes and fragmentation of horizon-sized loops
The impact of social isolation on health and behavior in Drosophila melanogaster and beyond

Many organisms, including humans, have evolved dynamic social behaviors to promote survival. Public health studies show that isolation from social groups is a major risk factor for adverse health outcomes in humans, but these studies lack mechanistic understanding. Animal models can provide insight into the molecular and neural mechanisms underlying how social isolation impacts health through investigations using genetic, genomic, molecular, and neuroscience methods. In this review, we discuss Drosophila melanogaster as a robust genetic model for studying the effects of social isolation and for developing a mechanistic understanding of the perception of social isolation and how it impacts health.
Uncovering the neural representation of multiple dimensions of object categorization in human visual cortex

We rely on vision more than on any other sensory modality to interact with and make sense of the world. Our behavior and culture, as well as the data we generate all rely strongly on visual information to index and capture salient relationships in the world. Within this realm, categorization is a fundamental building block of our visual experience. It is due to this marvelous generalization process that we take the problem of perceiving and understanding trillions of entities in our world (objects and scenes) and reduce it to a more manageable magnitude by binning virtually everything we see into a few tens of thousands of categories. Thus, it becomes a fundamental problem in understanding human vision to elucidate the mechanisms by which our visual cortices extract such complex information from a noisy sea of colored dots encoded by our retinas when we look out into the world. But what represents a ’good’ category and why do these distinctions emerge the way they do? Cognitively, useful distinctions between groups of items simultaneously maximize within-category similarity and between-category dissimilarity. The underlying hypothesis behind the work we put forward in this dissertation is that this key idea of similarity maximization also extends to the instantiation of neural patterns of representation in visual cortex. To this end, we use computational approaches in the context of several functional neuroimaging (fMRI) experiments to explore how behaviorally pervasive dimensions of object categorization, such as hierarchical organization and typicality, are represented in the brain and how they help us build a coherent picture of the world. Finally, we propose and test a model of neural object category processing based on the hypothesis that the cognitive utility of category structure partly drives information processing in visual cortex.
Systems of diagonal Diophantine inequalities

We treat systems of real diagonal forms F 1 (x), F 2 (x),. , F R (x) of degree k, in s variables. We give a lower bound s 0 (R, k), which depends only on R and k, such that if s > s 0 (R, k) holds, then, under certain conditions on the forms, and for any positive real number e, there is a nonzero integral simultaneous solution x ∈ Z s of the system of Diophantine inequalities |F i (x)| < e for I ≤ i < R. In particular, our result is one of the first to treat systems of inequalities of even degree. The result is an extension of earlier work by the author on quadratic forms. Also, a restriction in that work is removed, which enables us to now treat combined systems of Diophantine equations and inequalities.
Magnetic and electrical transport properties of Ge1−xMnx thin films

We report on preparation and systematic study of the structural, magnetic, and electrical transport properties of Ge1−xMnx (x=25%–42%) alloy thin films grown on GaAs (001) substrates by molecular beam epitaxy. Amorphous Ge1−xMnx, and coexistence of amorphous Ge1−xMnx, Ge crystallites, and high TC secondary phases (Mn11Ge8 and Mn5Ge3) are obtained at substrate temperatures of 160 and 200–300°C, respectively. The amorphous samples are found to consist of a low-temperature highly ordered spin-glass-like phase with an ordering temperature of TC∼20K (x∼0.39), increasing with the Mn composition, and a high-temperature “clustered dopant” phase with an ordering temperature of TC*∼104K (x∼0.39), increasing with both the Mn composition and applied external field. The magnetization of the low-temperature phase is found to be coupled antiferromagnetically with that of the high-temperature phase, leading to the appearance of a negative thermal remanent magnetization. Detailed magnetic and electrical measurement reveal.