Miracle-dz/UniFAR-FTUs huggingface dataset:
Double Marginalization in Performance-Based Advertising: Implications and Solutions

An important current trend in advertising is the replacement of traditional pay-per-exposure (pay-per-impression) pricing models with performance-based mechanisms in which advertisers pay only for measurable actions by consumers. Such pay-per-action (PPA) mechanisms are becoming the predominant method of selling advertising on the Internet. Well-known examples include pay-per-click, pay-per-call, and pay-per-sale. This work highlights an important, and hitherto unrecognized, side effect of PPA advertising. I find that, if the prices of advertised goods are endogenously determined by advertisers to maximize profits net of advertising expenses, PPA mechanisms induce firms to distort the prices of their goods (usually upward) relative to prices that would maximize profits in settings where advertising is sold under pay-per-exposure methods. Upward price distortions reduce both consumer surplus and the joint publisher--advertiser profit, leading to a net reduction in social welfare. They persist in current auction-based PPA mechanisms, such as the ones used by Google, Yahoo! , and Microsoft. In the latter settings they also reduce publisher revenues relative to pay-per-exposure methods. I show that these phenomena constitute a form of double marginalization and discuss a number of enhancements to today's PPA mechanisms that restore equilibrium pricing of advertised goods to efficient levels, improving both consumer surplus as well as the publisher's expected profits. This paper was accepted by Lorin Hitt, information systems.
Particle-Filtering-Based Discharge Time Prognosis for Lithium-Ion Batteries With a Statistical Characterization of Use Profiles

We present the implementation of a particle-filtering-based prognostic framework that utilizes statistical characterization of use profiles to (i) estimate the state-of-charge (SOC), and (ii) predict the discharge time of energy storage devices (lithium-ion batteries). The proposed approach uses a novel empirical state-space model, inspired by battery phenomenology, and particle-filtering algorithms to estimate SOC and other unknown model parameters in real-time. The adaptation mechanism used during the filtering stage improves the convergence of the state estimate, and provides adequate initial conditions for the prognosis stage. SOC prognosis is implemented using a particle-filtering-based framework that considers a statistical characterization of uncertainty for future discharge profiles based on maximum likelihood estimates of transition probabilities for a two-state Markov chain. All algorithms have been trained and validated using experimental data acquired from one Li-Ion 26650 and two Li-Ion 18650 cells, and considering different operating conditions.
Angiotensin II receptor blocker combinations: From guidelines to clinical practice

Abstract European guidelines recommend a combination of at least two antihypertensive drugs to achieve blood pressure (BP) goals in the majority of patients. In addition, they encourage simplification of treatment regimens using single-pill, fixed-dose combinations (FDCs) to aid compliance. Of the preferred combinations, those based on angiotensin II receptor blockers (ARBs) may be more desirable than those based on angiotensin-converting enzyme inhibitors, because of equivalent efficacy and superior tolerability. Significantly better BP reductions and control rates have been observed with the dual combinations of ARBs with amlodipine or hydrochlorothiazide (HCZT) compared with component monotherapies. Furthermore, in the 15−20% of patients who require triple combination therapy to achieve BP goals, fixed-dose triple combinations with an ARB, calcium-channel blocker and diuretic, which have recently become available, provide significantly better BP reductions and control compared with dual combinations. Within the ARB class, olmesartan stands out as being one that has been recently investigated in a considerable number of studies that are relevant to the modern concept of FDC therapy in terms of both dual and triple combination therapy. The availability of such single-pill FDCs has the potential to deliver strong antihypertensive efficacy with good tolerability and improved compliance.
Feasibility of BAALC gene expression for detection of minimal residual disease and risk stratification in normal karyotype acute myeloid leukaemia

High BAALC gene expression has been associated with poor prognosis in cytogenetically normal acute myeloid leukaemia (CN‐AML) and has been suggested as a suitable marker for assessing minimal residual disease (MRD). The purpose of this study was to substantiate these findings by the analysis of a large data set of 632 diagnostic and follow‐up samples in 142 intensively treated CN‐AML patients. Paired diagnostic/relapse samples of 35 patients revealed stable high BAALC expression in 89%, irrespective of a high proportion of clonal evolution found in 49% of these cases. High BAALC expression, both directly after induction chemotherapy and within 3–6 months after induction chemotherapy, correlated significantly with shorter event‐free survival and overall survival. Moreover, 8 of 10 patients displaying high BAALC expression levels after completion of induction therapy as well as 5 of 5 patients exhibiting high BAALC expression levels within 3–6 months after induction chemotherapy experienced relapse with a median of 197 and 101 days, respectively, from sampling to relapse. Thus, BAALC expression‐based MRD detection during therapy may be considered a strategy to identify patients at high risk of relapse.
Assessment of client satisfaction in labor and delivery services at a maternity referral hospital in Ethiopia

Introduction Patients perception about service quality shapes their confidence with regard to use of the available health care facility. This study is aimed to assess the client`s satisfaction in a maternal health care setting. Methods This is an institution based cross sectional descriptive study. A total of 423 postpartum women were interviewed. Data was analyzed using SPSS version 20 statistical package. Results The proportion of mothers who are completely satisfied with health care ranges between 2.4 to 21%. Pain control was the poorest source of satisfaction with 82% reporting dissatisfaction. Provider's communication with clients yielded complete satisfaction rates ranging between 0.7 to 26%. Inadequate information about the drug prescribed and explanation of procedures to be done to the client were found to be major causes of dissatisfaction. The complete satisfaction rate with environmental factor of the hospital was between 3.3 to 40.2%. Age of the client, educational status, income of the client and client's address away from Addis Ababa were found to be the predictors of client satisfaction. Provider's attitude and communication, as well as longer duration of stay in the ward were independent predictors of client satisfaction. Conclusion Pain management, client privacy and client provider communication need to be addressed to ensure the satisfaction of maternity clients. The clients need to be involved in the management of their own health problems.
Determinants of quality of life in Brazilian patients with Parkinson's disease

Our objective was to identify determinants of health‐related quality of life (HRQoL) in a cohort of Brazilian patients with Parkinson's disease (PD). Patients were evaluated by means of the Hoehn and Yahr staging (H&Y), Unified Parkinson's Disease Rating Scale (UPDRS), Schwab and England scale (S&E), Mini‐Mental State Exam, Geriatric Depression Scale, and Hospital Anxiety and Depression Scale (HADS). HRQol was assessed using the MOS‐Short‐Form 36 (SF‐36), the Parkinson's disease Questionnaire (PDQ‐39), and the Scales for Outcomes in Parkinson's Disease‐Psychosocial Questionnaire (SCOPA‐PS). 144 patients were evaluated (mean age 62 years; 53.5% men; mean duration of illness 6.6 years; median H&Y, 2 (range: 1–4). Mean SCOPA‐PS and PDQ‐39 Summary Index (SI) were 39.2 and 40.7, respectively. Both, PDQ‐39 and SCOPA‐PS SIs correlated at a moderate level (r = 0.30–0.50) with H&Y, S&E, total UPDRS, HADS subscales, and SF‐36 Physical and Mental Components. PDQ‐39 and SCOPA‐PS were closely associated (r = 0.73). HRQoL significantly deteriorated as H&Y progressed, as a whole. Mood disturbances, disability, motor complications, and education were independent predictors of HRQoL in the multivariate analysis model. In PD Brazilian patients, HRQoL correlated significantly with diverse measures of severity. Depression showed to be the most consistent determinant of HRQoL, followed by disability, motor complications, and education years. There was a close association between the PDQ‐39 and SCOPA‐PS summary scores. © 2007 Movement Disorder Society
A Bayesian Filter to Detect Misbehaving Nodes in MANETs

Composed of mobile nodes, MANETs rely on the entire collaboration of nodes to provide routing and forwarding functions. Most MANET security solutions identify and exclude malicious and selfish nodes. These mechanisms rely on local monitoring tools to detect untrustworthy nodes and then spread trust information through recommendations. In this paper we apply a Bayesian model [1] to improve MANET security. We classify nodes behavior relying on a decision based on a probabilistic Bayesian model. The novelty of our approach is that it classifies nodes based on distant observations. We describe statistical parameters like Accuracy, Error and the Total Cost Ratio that are used to evaluate the efficiency of the filter through a set of simulations of an attacked pure ad hoc network.
Determinants of taxonomic composition of plant viruses at the Nature Conservancy’s Tallgrass Prairie Preserve, Oklahoma

The role of biotic and abiotic factors in shaping the diversity and composition of communities of plant viruses remain understudied, particularly in natural settings. In this study, we test the effects of host identity, location, and sampling year on the taxonomic composition of plant viruses in six native plant species [Ambrosia psilostachya (Asteraceae), Vernonia baldwinii (Asteraceae), Asclepias viridis (Asclepiadaceae), Ruellia humilis (Acanthaceae), Panicum virgatum (Poaceae) and Sorghastrum nutans (Poaceae)] from the Nature Conservancy’s Tallgrass Prairie Preserve in northeastern Oklahoma. We sampled over 400 specimens of the target host plants from twenty sites (plots) in the Tallgrass Prairie Preserve over 4 years and tested them for the presence of plant viruses applying virus-like particle and double-stranded RNA enrichment methods. Many of the viral sequences identified could not be readily assigned to species, either due to their novelty or the shortness of the sequence. We thus grouped our putative viruses into operational viral taxonomic units for further analysis. Partial canonical correspondence analysis revealed that the taxonomic composition of plant viruses in the target species had a significant relationship with host species (P value: 0.001) but no clear relation with sampling site or year. Variation partitioning further showed that host identity explained about 2–5 per cent of the variation in plant virus composition. We could not interpret the significant relationship between virus composition and host plants with respect to host taxonomy or ecology. Only six operational viral taxonomic units had over 5 per cent incidence over a 4-year period, while the remainder exhibited sporadic infection of the target hosts. This study is the first of its kind to document the dynamics of the entire range of viruses in multiple plant species in a natural setting.
Dynamic visibility checking for vision-based motion planning

An important problem in position-based visual servoing (PBVS) is to guarantee that a target will remain within the field of view for the duration of the task. In this paper, we propose a dynamic visibility checking algorithm that, given a parametrized trajectory of the camera, determines if an arbitrary 3D target will remain within the field of view. We reformulate this problem as the problem of determining if the 3D coordinates of the target collide with the frustum formed by the camera field of view during the camera trajectory. To solve this problem, our algorithm computes and compares the shortest distance between the target and the frustum with the length of the trajectory described by the target in the camera's coordinate frame. Furthermore, we demonstrate that our algorithm can be combined with path planning algorithms and, in particular, probabilistic roadmaps (PRM). Results suggest that our algorithm is computationally efficient even when the target moves in the vicinity of image borders. In simulations, we use our dynamic visibility checking algorithm in conjunction with a PRM to plan collision free paths while providing the guarantee that a specific target will not leave the field of view.
Face and eye rectification in video conference using affine transform

The lack of eye contact in video conference degrades the user's experience. This problem has been known and studied for many years. There are hardware-based solutions to the eye gazing problem. However, these specialized systems are not generally accessible. This paper suggests a software approach that rectifies the face and the eyes in video conference, only utilizing one camera. In the setup phase, the view point and the affine transform matrix are calculated, using five frames each from the front view and the above view, with the aids of face detection and eye detection algorithm. Once the setup is done, we rectify the face with affine transformation, and rectify the eyes using image warping, based on an eye model. This is done in near real time (18 frames per second, for the resolution of 320/spl times/240). The result is not genuine but is significantly better.
Effects of Quetiapine and Haloperidol on Prepulse Inhibition of the Acoustic Startle (Eyeblink) Response and the N1/P2 Auditory Evoked Response in Man

Contraction of the orbicularis oculi muscle in response to a sudden loud sound (acoustic startle response) and the N1/P2 component of the auditory evoked potential are both attenuated when a brief low-intensity stimulus is presented 30-500 ms before the ‘startle-eliciting’ stimulus (PPI). Here, we report the effects of the ‘atypical’ antipsychotic drug quetiapine and the ‘conventional’ antipsychotic haloperidol on these responses. Sixteen males (aged 19-38 years) participated in four sessions at 7-day intervals, in which they received quetiapine 12.5 mg, quetiapine 25 mg, haloperidol 3 mg and placebo, according to a balanced double-blind design. Electromyographic (EMG) responses of the orbicularis oculi muscle and N1/P2 auditory evoked potentials were recorded in a 20-min session, 2 h after treatment. Subjects received 40 trials in which 1-kHz sounds were presented: (i) 40 ms, 115 dB (‘pulse alone’ trials) and (ii) 40 ms, 85 dB, followed after 120 ms by 40 ms, 115 dB (‘prepulse/pulse’ trials). Mean amplitudes of the EMG response and the N1/P2 potential were derived from the pulse-alone trials and, in each case, percentage PPI was calculated. Serum prolactin was measured after each treatment, and autonomic (heart rate, blood pressure, salivation) and psychological (visual analogue self-ratings of mood and alertness, critical flicker fusion frequency) measures were taken before and after each treatment. Quetiapine 12.5 mg and 25 mg significantly reduced the amplitude of the EMG response without altering its inhibition by prepulses; haloperidol had no effect on EMG response amplitude or PPI. Neither drug affected N1/P2 amplitude or PPI of this response. Quetiapine, but not haloperidol, reduced subjective alertness and critical flicker fusion frequency. Haloperidol, but not quetiapine, elevated serum prolactin level. The ability of quetiapine to attenuate the startle response may reflect its sedative action.
Crystal Structure of the Streptomyces coelicolor Sortase E1 Transpeptidase Provides Insight into the Binding Mode of the Novel Class E Sorting Signal

Many species of Gram-positive bacteria use sortase transpeptidases to covalently affix proteins to their cell wall or to assemble pili. Sortase-displayed proteins perform critical and diverse functions for cell survival, including cell adhesion, nutrient acquisition, and morphological development, among others. Based on their amino acid sequences, there are at least six types of sortases (class A to F enzymes); however, class E enzymes have not been extensively studied. Class E sortases are used by soil and freshwater-dwelling Actinobacteria to display proteins that contain a non-canonical LAXTG sorting signal, which differs from 90% of known sorting signals by substitution of alanine for proline. Here we report the first crystal structure of a class E sortase, the 1.93 Å resolution structure of the SrtE1 enzyme from Streptomyces coelicolor. The active site is bound to a tripeptide, providing insight into the mechanism of substrate binding. SrtE1 possesses β3/β4 and β6/β7 active site loops that contact the LAXTG substrate and are structurally distinct from other classes. We propose that SrtE1 and other class E sortases employ a conserved tyrosine residue within their β3/β4 loop to recognize the amide nitrogen of alanine at position P3 of the sorting signal through a hydrogen bond, as seen here. Incapability of hydrogen-bonding with canonical proline-containing sorting signals likely contributes to class E substrate specificity. Furthermore, we demonstrate that surface anchoring of proteins involved in aerial hyphae formation requires an N-terminal segment in SrtE1 that is presumably positioned within the cytoplasm. Combined, our results reveal unique features within class E enzymes that enable them to recognize distinct sorting signals, and could facilitate the development of substrate-based inhibitors of this important enzyme family.
Novel Immunogenic Peptides Elicit Systemic Anaphylaxis in Mice: Implications for Peptide Vaccines

Peptide-based therapies are showing increasing potential for the development of vaccines and in the treatment of many important diseases. We previously reported two peptide conjugate vaccines that protected mice against pneumococcal disease. During this study, we observed an unexpected phenomenon; several vaccine candidates induced a rapid, fatal anaphylaxis after booster injection of the peptide conjugate. Further investigation indicated the reaction was mediated by the production of peptide-specific IgE and the release of histamine. Notably, among seven peptides tested, all of which bound the same mAb that selected them from a phage library, only four elicited this severe reaction. Sequence alignment analysis of all peptides revealed unique clusters of acidic amino acid residues in the allergenic peptides. Substitution of the acidic amino acid residues, ED, of peptide MP2 with their amine equivalents, QN, eliminated the anaphylactic effects but did not affect the production of peptide-specific IgG. These results have important implications for both the study of allergens and the development of future peptide-based therapies.
A Pilot Study on the Cross-Cultural Acceptance of Technology

In this period of technological innovations, there is no doubt that the study of technology acceptance and diffusion is important. There have been numerous advancements in this regard. However, there has been relatively little cross-cultural research done in this domain. The purpose of this study is to explore the role that cultural differences play in the acceptance of technology and in particular, a popular email service provider, Gmail©. A mixed methods approach was followed for this study. Data regarding perception of Gmail© between participants in India (collectivist) and the U.S. (individualistic) was collected using online questionnaires. Correlational analysis and content analysis were used to analyze the data. While there was no statistical significance regarding ease of use, content analysis found that ‘ease of use’ could be an important factor for the Indian sample. Difference in loyalty towards Gmail© was found to be approaching significance (at α=0.05). ‘Ease of acquiring’ was found to be important for the acceptance of technology for both cultures studied implying that designers and producers must make it easy for potential users from any country to get their product. An interesting trend noticed was that the Indian sample identified social factors like the chat system Gtalk©, if Gmail© was exciting, and if it was good when they compared it to other systems, while the U.S. sample seemed to find work-related factors, like if it was integrated across multiple platforms or if it was a requirement with the organization, to be important. The U.S. sample also brought up the price and brand name a lot more than the Indian sample.
Robust visual reranking via sparsity and ranking constraints

Visual reranking has become a widely-accepted method to improve traditional text-based image search engines. Its basic principle is that visually similar images should have similar ranking scores. While existing methods are different in specifics, almost all of them are based on explicit or implicit pseudo-relevance feedback (PRF). Explicit PRF-based approaches, including classification-based and clustering-based reranking, suffer from the difficulty of selecting reliable positive and negative samples. Implicit PRF-based approaches, such as graph-based and Bayesian visual reranking, deal with such unreliability by making use of the initial ranking in a soft manner, but have limited capability of promoting relevant images and lowering down irrelevant images. In this paper, we propose l1 square loss optimization based on sparsity and ranking constraints to detect confident samples which are most likely to be relevant to a query. Based on the discovered confident samples, we present an adaptive kernel-based scheme to rerank the images. The success of our proposed method comes from another important observation that irrelevant images, whether initially positioned at the top or bottom, are usually less-popular and more diverse than relevant images. Therefore, it is robust against outlier images and suitable when relevant images are multi-modally distributed. The experimental results demonstrate significant improvement of our method over several existing reranking approaches on both MSRA-MM V1.0 and Web Queries datasets.
Investigating Techniques for Teaching Word Meanings

EXAMINES THE EFFECTIVENESS of 4 methods for teaching word meanings. Theoretical rationale is provided by aspects of language, cognitive development, and memory processes relevant to learning word meanings. A repeated measures 4 x 4 Latin square type design was utilized, so that all subjects received all methods over an 8-week period. Analysis of performance scores on weekly evaluation tasks indicated that the methods used to teach word meanings differed in effectiveness, with the context method being most effective (p<.001). Findings were interpreted as supportive of vocabulary instruction, which includes using new words in sentences that provide examples of appropriate usage of the new word within the context of familiar events. Associating new words with familiar synonyms was also supported. Use of category labels and dictionary practice was not strongly supported. Results of the study indicated that an interactive model for cognitive processes might provide useful information for studies investigating vocabulary development.