Miracle-dz/UniFAR-FTUs huggingface dataset:
The panE Gene, Encoding Ketopantoate Reductase, Maps at 10 Minutes and Is Allelic to apbA inSalmonella typhimurium

ABSTRACT In Salmonella typhimurium, precursors to the pyrimidine moiety of thiamine are synthesized de novo by the purine biosynthetic pathway or the alternative pyrimidine biosynthetic (APB) pathway. TheapbA gene was the first locus defined as required for function of the APB pathway (D. M. Downs and L. Petersen, J. Bacteriol. 176:4858–4864, 1994). Recent work showed the ApbA protein catalyzes the NADPH-specific reduction of ketopantoic acid to pantoic acid. This activity had previously been associated with the pantothenate biosynthetic gene panE. Although previous reports placed panE at 87 min on the Escherichia coli chromosome, we show herein that apbA andpanE are allelic and map to 10 min on both the S. typhimurium and E. coli chromosomes. Results presented here suggest that the role of ApbA in thiamine synthesis is indirect since in vivo labeling studies showed that pantoic acid, the product of the ApbA-catalyzed reaction, is not a direct precursor to thiamine via the APB pathway.
Learning to Tell Tales: A Data-driven Approach to Story Generation

Computational story telling has sparked great interest in artificial intelligence, partly because of its relevance to educational and gaming applications. Traditionally, story generators rely on a large repository of background knowledge containing information about the story plot and its characters. This information is detailed and usually hand crafted. In this paper we propose a data-driven approach for generating short children's stories that does not require extensive manual involvement. We create an end-to-end system that realizes the various components of the generation pipeline stochastically. Our system follows a generate-and-and-rank approach where the space of multiple candidate stories is pruned by considering whether they are plausible, interesting, and coherent.
Burden and psychological effects: caregiver experiences in a psychiatric outpatient unit in Lagos, Nigeria.

OBJECTIVE Worldwide, research into experiences of care givers are gradually increasing and their central role in community care is being acknowledged. Caregivers experience a multidimensional range of problems, often associated with their caregiving role. It becomes important to identify these areas of burden and provide necessary support. The study sought to determine the prevalence of psychological distress and experience of burden of care among the caregivers of mentally ill patients. METHOD A cross sectional descriptive study. Eligible consecutive subjects were recruited to the study over a 6 month period. Fifty three caregiver relatives of patients diagnosed with a psychiatric illness were assessed using the General Health questionnaire version 12, an Adapted Burden of Care (BOC) Schedule and a Sociodemographic questionnaire. RESULTS The caregivers were 51% male and 49% female. Most were above 35years in age (66.1%). They were either parents (38.8%), siblings (18.4%), uncle/aunt (14.3%), first cousin (12.2%) or other extended relatives (16.3%). Almost half of the relatives had psychological distress (43.8%) and most of which (63%) had more burden. The mean score on the BOC among the caregivers was 41 (±18.68SD), with scores ranging from 0.00-89.00, and 45.3% of relatives experiencing more than average burden of care. CONCLUSION There is a significant level of burden and psychological distress experienced by caregivers in this study location. It is recommended that effectively planned interventions are targeted at alleviating this burden and at improving the ability of caregivers to cope, within the Nigerian mental health service delivery system.
Task variation during simulated, repetitive, low-intensity work – influence on manifestation of shoulder muscle fatigue, perceived discomfort and upper-body postures

Work-related musculoskeletal disorders are increasing due to industrialisation of work processes. Task variation has been suggested as potential intervention. The objectives of this study were to investigate, first, the influence of task variation on electromyographic (EMG) manifestations of shoulder muscle fatigue and discomfort; second, noticeable postural shoulder changes over time; third, if the association between task variation and EMG might be biased by postural changes. Outcome parameters were recorded using multichannel EMG, Optotrak and the Borg scale. Fourteen participants performed a one-hour repetitive Pegboard task in one continuous and two interrupted conditions with rest and a pick-and-place task, respectively. Manifestations of shoulder muscle fatigue and discomfort feelings were observed throughout the conditions but these were not significantly influenced by task variation. After correction for joint angles, the relation between task variation and EMG was significantly biased but significant effects of task variation remained absent. Practitioner Summary: Comparing a one-hour continuous, repetitive Pegboard task with two interrupted conditions revealed no significant influences of task variation. We did observe that the relation between task variation and EMG was biased by posture and therefore advise taking account for posture when investigating manifestations of muscle fatigue in assembly tasks.
Assessment: Botulinum neurotoxin for the treatment of spasticity (an evidence-based review): Report of the Therapeutics and Technology Assessment Subcommittee of the American Academy of NeurologySYMBOL

Objective:To perform an evidence-based review of the safety and efficacy of botulinum neurotoxin (BoNT) in the treatment of adult and childhood spasticity. Methods:A literature search was performed including MEDLINE and Current Contents for therapeutic articles relevant to BoNT and spasticity. Authors reviewed, abstracted, and classified articles based on American Academy of Neurology criteria (Class I–IV). Results:The highest quality literature available for the respective indications was as follows: adult spasticity (14 Class I studies); spastic equinus and adductor spasticity in pediatric cerebral palsy (six Class I studies). Recommendations:Botulinum neurotoxin should be offered as a treatment option for the treatment of spasticity in adults and children (Level A). GLOSSARYBoNT = botulinum neurotoxin; CP = cerebral palsy; FDA = Food and Drug Administration; SNAP = synaptosomal-associated protein; VAMP = vesicle-associated membrane protein.
A Monte Carlo Based Analysis of Optimal Design Criteria

Abstract : Optimal design methods (designed to choose optimal sampling distributions through minimization of a specific cost function related to the resulting error in parameter estimates) for inverse or parameter estimation problems are considered. We compare a recent design criteria SE-optimal design (standard error optimal design) with the more traditional D-optimal and E-optimal designs. The optimal sampling distributions from each design are used to compute and compare standard errors; here the standard errors for parameters are computed using the optimal mesh along with Monte Carlo simulations as compared to asymptotic theory based standard errors. We illustrate ideas with two examples: the Verhulst-Pearl logistic population model and the standard harmonic oscillator model.
The Maximum Communication Complexity of Multi-Party Pointer Jumping

We study the one-way number-on-the-forhead (NOF) communication complexity of the $k$-layer pointer jumping problem. Strong lower bounds for this problem would have important implications in circuit complexity. All of our results apply to myopic protocols (where players see only one layer ahead, but can still see arbitrarily far behind them.) Furthermore, our results apply to the maximum communication complexity, where a protocol is charged for the maximum communication sent by a single player rather than the total communication sent by all players. Our main result is a lower bound of $n/2$ bits for deterministic protocols, independent of the number of players. We also provide a matching upper bound, as well as an $\Omega(n/k\log n)$ lower bound for randomized protocols, improving on the bounds of Chakrabarti. In the non-Boolean version of the problem, we give a lower bound of $n (\log^{(k-1)} n)(1-o(1))$ bits, essentially matching the upper bound from Damm et al.
PSA bouncing after brachytherapy HDR and external beam radiation therapy: a study of 121 patients with minimum 5-years follow-up

Purpose To determine the clinical and dosimetric factors that predict prostate-specific antygen (PSA) bouncing following brachytherapy HDR and three-dimensional conformal radiation therapy (3D-CRT) for prostate cancer patients. Material and methods The evaluated population consisted of 121 prostate cancer patients with a minimum of 5 years of follow-up and at least 6 post-treatment PSA levels. All patients were treated using 3D-CRT combined with brachytherapy HDR. A bounce was defined as a PSA rise of ≥ 0.2 ng/ml above the nadir followed by a subsequent 120 decline of ≥ 0.2 ng/ml. The evaluated clinical factors included: patient age, Gleason score, maximum initial pretreatment PSA value (iPSAmax), clinical stage, prostate volume, median time to PSA nadir, median PSA nadir value and patient follow-up in months. The dosimetric factors evaluated included the percentage of the prostate volume receiving 100% (V100), 150% (V150) and 200% (V200) of the prescribed minimal peripheral dose. Results Statistically significant predictive factors for PSA bounce were age, V100, V150, V200, iPSAmax and median time to PSA nadir. Logistic regression model for multivariate analysis revealed that only age, iPSAmax and V200 were statistically significant predictors for PSA bounce. There were not statistical differences between median nadir among patients who exhibited a PSA bounce and did not but non-bouncer reached PSA nadir earlier than bouncer, respectively median time was 12.1 vs. 17.2 months. Conclusions PSA bouncing occurs in approximately a one third (1/3) of patients treated with 3D-CRT and brachytherapy HDR. Bouncing is associated with age, higher pretreatment PSA level and increased V200 factor.
Aligning Capacity Decisions in Supply Chains When Demand Forecasts Are Private Information: Theory and Experiment

We study the problem of a two-firm supply chain in which firms simultaneously choose a capacity before demand is realized. We focus on the role that private information about demand has on firms' ability to align their capacity decisions. When forecasts are private information, there are at most two equilibria: a complete coordination failure or a monotone equilibrium. The former equilibrium always exists, whereas the latter exists only when the marginal cost of capacity is sufficiently low. We also show that both truthful information sharing and preplay communication have an equilibrium with higher profits. We then test the model's predictions experimentally. Contrary to our theoretical predictions, we show that private demand forecasts do not have a consistently negative effect on firm profits, though capacities are more misaligned. We show that preplay communication may be more effective at increasing profits than truthful information sharing. Finally, we document that "honesty is the best policy" when communicating private information.
Functions of the subesophageal ganglion in the medicinal leech revealed by ablation of neuromeres in embryos

SUMMARY Two general trends in the evolution of the nervous system have been toward centralization of neuronal somata and cephalization of the central nervous system (CNS). These organizational trends are apparent in the nervous system of annelid worms, including leeches. To determine if the anterior brain of the leech serves functions similar to those of the brains of more complex organisms, including vertebrates, we ablated one of the two major regions of the cephalic brain - the subesophageal ganglion (SubEG). For anatomical reasons, ablations were performed in embryos, rather than in adults. At the end of embryonic development, we observed the leeches' spontaneous behaviour and their responses to moderate touch. We observed that, although the midbody ganglia of the leech CNS display a high degree of local autonomy, the cephalic brain provides generalized excitation to the rest of the CNS, is a source of selective inhibition that modulates behaviour, integrates sensory information from the head with signals from the rest of the body, and plays an important role in organizing at least some complicated whole-body behaviours. These roles of the leech cephalic brain are common features of brain function in many organisms, and our results are consistent with the hypothesis that they arose early in evolution and have been conserved in complex nervous systems.
Constraints on distances to Galactic Centre non-thermal filaments from HI absorption

We have studied HI absorption towards three non-thermal filaments (NTFs) Sgr-C, G359.54+0.18 and G359.79+0.17 using the Giant Metrewave Radio Telescope (GMRT). Our study, for the first time, constrains the distance of the Sgr C NTF and the HII region seen associated with the NTF in the sky plane, to within a few hundred parsecs from the Galactic Centre (GC). A molecular cloud with a velocity of -100 km/s appears to be associated with the central part of the Sgr C NTF. Our study also indicates that the Sgr C HII region is relatively farther away than the NTF along our line of sight, and thereby provides evidence against any possible interaction between the two objects. The NTF G359.54+0.18 shows weak HI absorption (4 sigma detection) at a velocity of -140 km/s, which is the velocity of a known dense molecular cloud seen towards the NTF. This cloud is expected to be located within ~200 pc from the GC and thereby provides a lower limit to the distance. The upper limit to the distance of this NTF from the Sun is 10.5 kpc. The distance to the NTF G359.79+0.17 is between 5.1 and 10.5 kpc from the Sun.
Classifiers in almost empty spaces

Recent developments in defining and training statistical classifiers make it possible to build reliable classifiers in very small sample size problems. Using these techniques advanced problems may be tackled, such as pixel based image recognition and dissimilarity based object classification. It can be explained and illustrated how recognition systems based on support vector machines and subspace classifiers circumvent the curse of dimensionality, and even may find nonlinear decision boundaries for small training sets represented in Hilbert space.
The spacetime of double field theory: Review, remarks, and outlook

We review double field theory (DFT) with emphasis on the doubled spacetime and its generalized coordinate transformations, which unify diffeomorphisms and b‐field gauge transformations. We illustrate how the composition of generalized coordinate transformations fails to associate. Moreover, in dimensional reduction, the O(d,d) T‐duality transformations of fields can be obtained as generalized diffeomorphisms. Restricted to a half‐dimensional subspace, DFT includes ‘generalized geometry’, but is more general in that local patches of the doubled space may be glued together with generalized coordinate transformations. Indeed, we show that for certain T‐fold backgrounds with non‐geometric fluxes, there are generalized coordinate transformations that induce, as gauge symmetries of DFT, the requisite O(d,d;ℤ) monodromy transformations. Finally we review recent results on the α′ extension of DFT which, reduced to the half‐dimensional subspace, yields intriguing modifications of the basic structures of generalized geometry.
Power Reduction of Wireless Sensor Networks Using Ant Colony Optimization

Power consumption is one of the most important problems for wireless sensor networks because of the battery limitation in each sensor. This paper presents an ant colony optimization- (ACO-) based routing algorithm to reduce power consumption. First, a grade table is built and referred to generate several possible routing paths. Then, the ACO explores these paths to reduce the power consumption of the nodes. The simulations indicate that the proposed algorithm obtains more balanced transmission among the nodes and reduces the power consumption of the routing.
A Rare Inherited 15q11.2-q13.1 Interstitial Duplication with Maternal Somatic Mosaicism, Renal Carcinoma, and Autism

Chromosome 15q11-q13.1 duplication is a common copy number variant associated with autism spectrum disorder (ASD). Most cases are de novo, maternal in origin and fully penetrant for ASD. Here, we describe a unique family with an interstitial 15q11.2-q13.1 maternal duplication and the presence of somatic mosaicism in the mother. She is typically functioning, but formal autism testing showed mild ASD. She had several congenital anomalies, and she is the first 15q Duplication case reported in the literature to develop unilateral renal carcinoma. Her two affected children share some of these clinical characteristics, and have severe ASD. Several tissues in the mother, including blood, skin, a kidney tumor, and normal kidney margin tissues were studied for the presence of the 15q11-q13.1 duplication. We show the mother has somatic mosaicism for the duplication in several tissues to varying degrees. A growth competition assay in two types of stem cells from duplication 15q individuals was also performed. Our results suggest that the presence of this interstitial duplication 15q chromosome may confer a previously unknown growth advantage in this particular individual, but not in the general interstitial duplication 15q population.
Corticotropin-Releasing Factor Receptor 1

Corticotropin-Releasing Factor and the Stress Response in the HypothalamicPituitary-Adrenal Axis The hypothalamic-pituitary-adrenal (HRA) axis begins in the brain with the amygdala, which is involved in recognizing environmental stressors (Figure 1A). After a stressor, the amygdala signals the cells in the paraventricular nuclei of the hypothalamus (Figure 1B) to release corticotropin-releasing factor (CRF) to the pituitary gland (Figure 1C), which is rich in CRF type 1 receptors (CRFR-1). In response, the pituitary releases adrenocorticotropic hormone (ACTH) into the bloodstream. This hormone travels to the adrenal glands, which sit atop the kidneys
A Framework for Human Pose Estimation in Videos

In this paper, we present a method to estimate a sequence of human poses in unconstrained videos. We aim to demonstrate that by using temporal information, the human pose estimation results can be improved over image based pose estimation methods. In contrast to the commonly employed graph optimization formulation, which is NP-hard and needs approximate solutions, we formulate this problem into a unified two stage tree-based optimization problem for which an efficient and exact solution exists. Although the proposed method finds an exact solution, it does not sacrifice the ability to model the spatial and temporal constraints between body parts in the frames; in fact it models the {\em symmetric} parts better than the existing methods. The proposed method is based on two main ideas: `Abstraction' and `Association' to enforce the intra- and inter-frame body part constraints without inducing extra computational complexity to the polynomial time solution. Using the idea of `Abstraction', a new concept of `abstract body part' is introduced to conceptually combine the symmetric body parts and model them in the tree based body part structure. Using the idea of `Association', the optimal tracklets are generated for each abstract body part, in order to enforce the spatiotemporal constraints between body parts in adjacent frames. A sequence of the best poses is inferred from the abstract body part tracklets through the tree-based optimization. Finally, the poses are refined by limb alignment and refinement schemes. We evaluated the proposed method on three publicly available video based human pose estimation datasets, and obtained dramatically improved performance compared to the state-of-the-art methods.
Optimal transforms for multispectral and multilayer image coding

Multispectral images are composed of a series of images at differing optical wavelengths. Since these images can be quite large, they invite efficient source coding schemes for reducing storage and transmission requirements. Because multispectral images include a third (spectral) dimension with nonstationary behavior, these multilayer data sets require specialized coding techniques. The authors develop both a theory and specific methods for performing optimal transform coding of multispectral images. The theory is based on the assumption that a multispectral image may be modeled as a set of jointly stationary Gaussian random processes. Therefore, the methods may be applied to any multilayer data set which meets this assumption. Although the authors do not assume the autocorrelation has a separable form, they show that the optimal transform for coding has a partially separable structure. In particular, they prove that a coding scheme consisting of a frequency transform within each layer followed by a separate KL transform across the layers at each spatial frequency is asymptotically optimal as the block size becomes large. Two simplifications of this method are also shown to be asymptotically optimal if the data can be assumed to satisfy additional constraints. The proposed coding techniques are then implemented using subband filtering methods, and the various algorithms are tested on multispectral images to determine their relative performance characteristics.
Context- and Content-aware Embeddings for Query Rewriting in Sponsored Search

Search engines represent one of the most popular web services, visited by more than 85% of internet users on a daily basis. Advertisers are interested in making use of this vast business potential, as very clear intent signal communicated through the issued query allows effective targeting of users. This idea is embodied in a sponsored search model, where each advertiser maintains a list of keywords they deem indicative of increased user response rate with regards to their business. According to this targeting model, when a query is issued all advertisers with a matching keyword are entered into an auction according to the amount they bid for the query, and the winner gets to show their ad. One of the main challenges is the fact that a query may not match many keywords, resulting in lower auction value, lower ad quality, and lost revenue for advertisers and publishers. Possible solution is to expand a query into a set of related queries and use them to increase the number of matched ads, called query rewriting. To this end, we propose rewriting method based on a novel query embedding algorithm, which jointly models query content as well as its context within a search session. As a result, queries with similar content and context are mapped into vectors close in the embedding space, which allows expansion of a query via simple K-nearest neighbor search in the projected space. The method was trained on more than 12 billion sessions, one of the largest corpuses reported thus far, and evaluated on both public TREC data set and in-house sponsored search data set. The results show the proposed approach significantly outperformed existing state-of-the-art, strongly indicating its benefits and the monetization potential.
Learning of Constraints and Logical Implications in The Spatial Domain

In the spatial domain, the inclusion of an object in a region c a be defined by inequations containing trigonometric expressions and several variables. Proving that a relation holds involves constraint solving. To circu mvent the computational difficulties arising for these probl ems, we explore the applicablility of classification learni ng programs to this domain.