Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Consonant Duration on Formation of Consonant-Vowel Syllable Evoked Auditory Cortical Potentials.

OBJECTIVE To compare P1-N1-P2-N2 response latencies and amplitudes evoked by voiced and unvoiced consonant-vowel syllables (CVS) /bi/-/pi/ and /di/-/ti/ by analyzing how the cortical responses to consonants and vowels interact during the formation of a syllable-evoked response. MATERIALS AND METHODS Auditory late latency responses were recorded from 12 healthy individuals between the ages of 20 and 40 years with normal hearing while presenting /bi/-/pi/ and /di/-/ti/ tokens and individual consonant-vowel parts of syllables. Amplitude/latency values of P1-N1-P2-N2 responses were compared between /bi/-/pi/ and /di/-/ti/ pairs. Formation of CVS-evoked responses by consonant and vowel responses was also investigated. RESULTS N1-P2-N2 latencies evoked by /bi/ were significantly shorter than /pi/. P2-N2 amplitudes evoked by /di/ were significantly higher and N2 latencies were shorter than /ti/. N1-P2-N2 peaks of /bi/, /pi/, and /di/ seemed to be combinations of respective peaks of consonant and vowel-evoked responses. For /ti/, P1 and N1 seem to be stemming only from the consonant part, P2 from consonant P2 and vowel N1, and N2 from consonant N2 and vowel P2-N2. CONCLUSION For both CVS pairs, longer consonant durations resulted in lower amplitudes and/or longer latencies, and this sheds light on why voiced-unvoiced CVSs evoke cortical responses with different features. Obtaining evoked responses to each consonant-vowel part of the syllables among listeners with perceptual difficulties and hearing devices might help to reveal which acoustic cues are not well represented in the auditory brain.
Magnoliae Cortex and maize modulate Porphyromonas gingivalis-induced inflammatory reactions

Purpose The aim of this study was to evaluate the capacity of single and combined applications of the bark of the stems and roots of Magnolia officinalis Rehd. et Wils. (Magnoliae Cortex) and Zea mays L. (maize) to modulate inflammation in RAW 264.7 cells stimulated with Porphyromonas gingivalis. Methods RAW 264.7 cells were stimulated with P. gingivalis, and Magnoliae Cortex and/or maize was added. Cytotoxicity and the capacity to modulate inflammation were determined with a methylthiazol tetrazolium (MTT) assay, nitrite production, enzyme-linked immunosorbent assay (ELISA), and western blotting. Results Treatment with Magnoliae Cortex and/or maize inhibited nuclear transcription factor κB (NF-κB) pathway activation and nuclear p44/42 mitogen-activated protein kinase (MAPK) and inducible nitric oxide synthase (iNOS) protein expression in P. gingivalis-stimulated RAW 264.7 cells. Moreover, the treatments suppressed cytokines (prostaglandin E2 [PGE2], interleukin [IL]-1β, and IL-6) and nitrite production. Conclusions Both Magnoliae Cortex and maize exerted an anti-inflammatory effect on P. gingivalis-stimulated RAW 264.7 cells, and this effect was more pronounced when the extracts were combined. These findings show that these extracts may be beneficial for slowing the progression of periodontal disease.
From Social Contract to Arab Spring: Macroeconomic Adjustment under Regime Change

Following the Arab-Spring protests, we examine macroeconomic interactions between a productive firm and a rent-seeking government characterized by a continuous probability of regime shift. The model is able to rationalize the early growth leaps witnessed in many Arab economies (the “Social Contract”), as well as their subsequent stagnation. Although post-Spring outcomes are judged benevolent, the macroeconomic inheritance is dependent on the earlier transition characteristics. The model thus sheds light on Arab economic evolutions, the shifting preferences and technologies of authorities and the likely success of economic reforms.
In Silico prediction of the molecular basis of ClTx and AaCTx interaction with matrix metalloproteinase-2 (MMP-2) to inhibit glioma cell invasion

Glioblastoma is the deadliest type of brain cancer. Treatment could target the Matrix metalloproteinase-2 (MMP-2), which is known to be involved in the invasion process of glioblastoma cells. But current available inhibitors are not selective to MMP-2 due to their interaction with the catalytic binding site, which is highly conserved in all MMPs structures. Interestingly, members of the chloride channel blocker scorpion toxins, such as chlorotoxin (ClTx) and AaCTx, inhibit glioblastoma cell invasion and show a promising therapeutic potential. Indeed, it has been shown that CITx inhibits selectively MMP-2 and was also able to cross the blood brain and tissue barriers. Although ClTx and AaCTx show high sequence similarity, AaCTx is ten times less active than ClTx. By using molecular modeling, molecular dynamics and MM-PB(GB)SA free energy estimation, we present the first computational study reporting the interaction mode of ClTx/AaCTx with MMP-2. We found that the two peptides probably act on an exosite of MMP-2 comprising mainly residues from the collagen binding domain, a feature that could be exploited to enhance the selectivity toward MMP-2. van der Waals and hydrophobic forces are the primary mediators of this interaction. The N- and C-termini of the two peptides harbor the key residues of the interaction spread across a conserved amino acid patch. In particular, F6 contributes mostly to the binding free energy in ClTx. We also suggest that the lack of the C-terminal arginine and the residues P10 and R24, might be responsible for altering the activity of AaCTx toward glioblastoma cells compared to ClTx.
First-Order Query Evaluation with Cardinality Conditions

We study an extension of first-order logic FO that allows to express cardinality conditions in a similar way as SQL's COUNT operator. The corresponding logic FOC(P) was introduced by Kuske and Schweikardt, who showed that query evaluation for this logic is fixed-parameter tractable on classes of databases of bounded degree. In this paper, we first show that the fixed-parameter tractability of FOC(P) cannot even be generalised to very simple classes of databases of unbounded degree such as unranked trees or strings with a linear order relation. Then, we identify a fragment FOC1(P) of FOCP which is still extends FO and is sufficiently strong to express standard applications of SQL's COUNT operator. Our main result shows that query evaluation for FOC1(P) is fixed-parameter tractable on nowhere dense classes of databases. This, in particular, implies that the counting problem for first-order queries on nowhere dense classes is fixed-parameter tractable.
End-to-end, sequence-to-sequence probabilistic visual odometry through deep neural networks

This paper studies visual odometry (VO) from the perspective of deep learning. After tremendous efforts in the robotics and computer vision communities over the past few decades, state-of-the-art VO algorithms have demonstrated incredible performance. However, since the VO problem is typically formulated as a pure geometric problem, one of the key features still missing from current VO systems is the capability to automatically gain knowledge and improve performance through learning. In this paper, we investigate whether deep neural networks can be effective and beneficial to the VO problem. An end-to-end, sequence-to-sequence probabilistic visual odometry (ESP-VO) framework is proposed for the monocular VO based on deep recurrent convolutional neural networks. It is trained and deployed in an end-to-end manner, that is, directly inferring poses and uncertainties from a sequence of raw images (video) without adopting any modules from the conventional VO pipeline. It can not only automatically learn effective feature representation encapsulating geometric information through convolutional neural networks, but also implicitly model sequential dynamics and relation for VO using deep recurrent neural networks. Uncertainty is also derived along with the VO estimation without introducing much extra computation. Extensive experiments on several datasets representing driving, flying and walking scenarios show competitive performance of the proposed ESP-VO to the state-of-the-art methods, demonstrating a promising potential of the deep learning technique for VO and verifying that it can be a viable complement to current VO systems.
Alcohol enhances symptoms and propensity for infection in inflammatory bowel disease patients and a murine model of DSS‐induced colitis

Over 1.4 million Americans have been diagnosed with inflammatory bowel disease (IBD), and ulcerative colitis (UC) makes up approximately half of those diagnoses. As a disease, UC cycles between periods of remission and flare, which is characterized by intense abdominal pain, increased weight loss, intestinal inflammation, rectal bleeding, and dehydration. Interestingly, a widespread recommendation to IBD patients for avoidance of a flare period is “Don't Drink Alcohol” as recent work correlated alcohol consumption with increased GI symptoms in patients with IBD. Alcohol alone not only induces a systemic pro‐inflammatory response, but can also be directly harmful to gut barrier integrity. However, how alcohol could result in the exacerbation of UC in both patients and murine models of colitis has yet to be elucidated. Therefore, we conducted a retrospective analysis of patients admitted for IBD with a documented history of alcohol use in conjunction with a newly developed mouse model of binge alcohol consumption following dextran sulfate sodium (DSS)‐induced colitis. We found that alcohol negatively impacts clinical outcomes of patients with IBD, specifically increased intestinal infections, antibiotic injections, abdomen CT scans, and large intestine biopsies. Furthermore, in our mouse model of binge alcohol consumption following an induced colitis flare, we found alcohol exacerbates weight loss, clinical scores, colonic shortening and inflammation, and propensity to infection. These findings highlight alcohol's ability to potentiate symptoms and susceptibility to infection in UC and suggest alcohol as an underlying factor in perpetuating symptoms of IBD.
Methicillin-resistant Staphylococcus aureus bacteremia among liver transplant recipients: epidemiology and associated risk factors for morbidity and mortality

Bacteremia due to Staphylococcus aureus, especially methicillin-resistant S. aureus (MRSA), complicates the clinical course of liver transplantation and is associated with high morbidity and mortality. Intravascular catheters had been reported to be the most frequent source of MRSA bacteremia. Among bacteremic liver recipients, 26.3%–100% of S. aureus were MRSA. Previous studies identified pre-transplant and post-transplant acquired S. aureus carriage, greater severity of liver disease, hepatocellular carcinoma and infection with immuno-modulatory viruses as predictors of S. aureus bacteremia in liver recipients. MRSA bacteremia accompanied by pneumonia and abdominal infections was related to mortality. Vancomycin, as well as daptomycin, is a first-line antibiotic for MRSA bacteremia. The purpose of this review is to better understand the characteristics of MRSA bacteremia by summarizing the epidemiology and antimicrobial resistance of S. aureus, the primary source, and related risk factors for morbidity and mortality of MRSA bacteremia. We have also explored the diagnostic, therapeutic and preventive measures for MRSA bacteremia to improve the outcomes of liver recipients.
Shoulder Instability: Arthroscopic Capsulolabral Repair: the Gold Standard

There still exists some skepticism in the orthopedic community regarding the effectiveness of all-arthroscopic shoulder stabilization surgeries, mostly due to older literature, which report high failure rates when compared to open surgery. We look to present the modern indications and techniques of arthroscopic shoulder stabilization and highlight recent studies which show equivalent or superior results even in the contact athlete. There exists an abundance of literature which shows arthroscopic shoulder stabilization done with proper anchor placement, incorporating capsulolabral shifts, with the patient positioned in lateral decubitus position provides for superior outcomes. It is also critical to recognize and address concomitant lesions of instability at the time of surgery to further reduce surgical failures. We contend that there still exists a role for open stabilizations especially in the setting of significant glenoid bone loss or in the revision setting, however for the majority of stabilization procedures, arthroscopic technique is the gold standard.
Heterogeneity in EGF-binding affinities arises from negative cooperativity in an aggregating system

Scatchard analysis of the binding of EGF to its receptor yields concave up plots that indicate the presence of two classes of binding sites. However, how two independent classes of sites arise from the expression of a single EGF receptor protein has never been adequately explained. Using a new analytical approach involving the simultaneous fitting of binding isotherms from cells expressing increasing levels of EGF receptors, we show that 125I-EGF-binding data can be completely explained by a model involving negative cooperativity in an aggregating system. This approach provides an experimentally determined value for the monomer–dimer equilibrium constant, which, for wild-type EGF receptors, corresponds to ≈50,000 receptors per cell. Therefore, changes in receptor expression within the physiological range can modulate the outcome of a signaling stimulus. Analysis of the L680N-EGF receptor mutant, in which the formation of asymmetric kinase domain dimers is blocked, indicates that the kinase dimers make a substantial energetic contribution to the ligand-independent association of EGF receptor monomers, but are not necessary for negative cooperativity. The model accurately predicts the behavior of receptor mutants, such as the dimerization-defective Y246D-EGF receptor, which exhibit a single class of binding sites and provides a framework for understanding secondary dimer formation and lateral signaling in the EGF receptor family.
Micromorphometry and cellular characteristics of the canine cervical intervertebral discs.

BACKGROUND Dogs have a high prevalence of disc-associated cervical spinal cord disorders. Despite this, there are no descriptions of the micromorphometry or cellular characteristics of canine cervical intervertebral discs. HYPOTHESIS/OBJECTIVES To compare micromorphometric and cellular characteristics at 4 disc regions (outer annulus [OA], inner annulus [IA], transitional zone [TZ], nucleus pulposus [NP]). We hypothesized that measurements would differ between chondrodystrophic (CH) and nonchondrodystrophic (NCH) dogs. ANIMALS Six CH dogs and 6 NCH dogs, under 3 years old. METHODS Histologic sections of all cervical discs from each dog were examined. Micromorphometric variables included relative ratio of ventral to dorsal annulus fibrosus (AF), number and mean width of AF fibers, and relative percentage of NP. Cellular variables included cell density, morphology, and grouping. RESULTS The NP from CH dogs was smaller, more rounded, and more dorsally located compared with that from NCH dogs. The NP occupied a greater proportion of the disc in NCH dogs compared with CH dogs (27.7 versus 15.8%; P<.001). The ratio of ventral to dorsal AF was approximately 3:1 in the CH group and 2:1 in the NCH group. Cellular variables were region dependent. Cell density was 2.4-fold higher in the OA compared with the NP. Approximately 50 of NP cells and 4.5% of OA cells occurred in groups. CONCLUSIONS AND CLINICAL IMPORTANCE Micromorphometric variables differed by CH status. Cellular variables differed by disc region. Our findings potentially can explain the high incidence of intervertebral disc extrusions in CH dogs compared with NCH dogs.
Mapping Texts to Scripts: An Entailment Study

Commonsense knowledge as provided by scripts is crucially relevant for text understanding systems, providing a basis for commonsense inference. This paper considers a relevant subtask of script-based text understanding, the task of mapping event mentions in a text to script events. We focus on script representations where events are associated with paraphrase sets, i
Policy Announcements in FX Markets

This paper studies empirically and theoretically the price of monetary policy uncertainty in the foreign exchange (FX) market. Using a large crosssection of foreign exchange data we document that carry returns are mainly earned on days of scheduled meetings of the Federal Open Market Committee (FOMC). More concretely, on announcement days, currencies with low interest rates produce an average daily return of 5.2 basis points (bp) compared to -1 bp on non-announcement days. This wedge becomes larger for high interest rate currencies and during bad economic times. We develop a model of an international long-run risk economy in which asset prices respond to revisions of the monetary policy. Monetary policy uncertainty commands a risk premium that is larger in weaker economic conditions when a revision of the monetary policy is more probable. A calibrated version is consistent with the cross-sectional pattern of carry trade risk premia observed in the data.
Durable Spending, Relative Prices and Consumption

In real terms, the growth of durable spending has substantially outpaced that of spending on other goods and services since the mid-1990s. But that gap largely reflects the effects of falling relative prices: nominal spending on durables and on non-durables has grown at similar rates during that period. This article uses a simple framework to assess the behaviour of the real and nominal ratio of durables to non-durable spending in the long run. It also considers the current position of the ratios in more detail and provides some assessment of how we might expect them to have evolved given prevailing cyclical factors.
Predicting Earnings - Entity Versus Subentity Data

The reporting of subentity earnings by large diversified corporations has been the subject of much discussion and research. Attention has centered on the need for the information by investors and the theoretical and practical problems to be encountered in furnishing the information. ' Those who have supported the reporting of subentity earnings data have argued that rates of growth and profitability and degrees of risk differ among the segments of a company operating in substantially different industries. This makes the prediction of consolidated earnings of the diversified company unnecessarily difficult. Since little information on subentity earnings has been made public in the past, research in this area has been confined to calling attention to possible uses of the data by investors. The purpose of this study is to test the relative predictive power of subentity earnings data for a sample of companies which have voluntarily reported sales and earnings data by subentity. Consolidated earnings for these firms will be predicted for 1968 and 1969 using subentity and entity sales and earnings data in conjunction with other investment and economic data available in early 1968 and early 1969, respectively. Specifically the question examined is: Will the disaggregation of consolidated earnings permit better predictions of next year's earnings using certain objective prediction models? Relatively simple prediction models are employed as objectively as possible in order to isolate a measure of the value of certain investment in-
Using Machine Learning for Detection of Autism Spectrum Disorder

Autism Spectrum Disorders are not hard to detect, but it requires that physicians have proper training and experience. At the moment however Autism Spectrum Disorder is detected much later than is actually possible. Early detection of Autism Spectrum Disorder improves the overall mental health of the child. In this research we use machine learning to determine a set of conditions that together prove to be predictive of Autism Spectrum Disorder. This will be a of great use to physicians, helping them detect Autism Spectrum Disorder at a much earlier stage. This will be done through literature review, data exploration and evaluation. Predicting if a child has Autism Spectrum Disorder proved possible by using developmental delay, learning disability and speech or other language problems as attributes and also include physical activity, premature birth and birth weight to improve the accuracy. Using the 1-away method it was also possible to predict the severity of Autism Spectrum Disorder quite reasonably. The 1-away method improved the accuracy from 54.1% to 90.2%, which is a significant increase. This and the fact that the severity was based on input from just the caretakers of the children, prompts the need for further research in this matter.
The Experience of Workplace Spirituality: Do Age and Educational Attainment Matter?

We examined the experience of workplace spirituality with respect to its three dimensions namely, meaningful work (sense of purpose in work), sense of community (sense of relationship with others at work), and value allignment (match between employee and organization’s values). We also compare the experience of spirituality among younger and older employees and among those with different levels of educational attainment. Using self-administered survey questionnaires, we collected data from 274 Malaysian public service employees involved in poverty alleviation programs in the rural sector. The experience of workplace spirituality is considerably high for all the three dimensions, especially so for meaningful work. Workplace spirituality did not differ significantly by employee age but differed significantly by employee educational attainment. The experience of workplace spirituality for all the three dimensions were greater among employees with college and university education than their counterparts with high school education. Implications for human resource development and future research are presented.
Information set based features for the speed invariant gait recognition

A novel speed-invariant gait features called two-fold information set (2FInS) features that capture both spatial and temporal variations in a gait cycle are proposed in this study. These features are obtained by applying first histogram of oriented gradients descriptors on the gait images followed by the representation of the underlying possibilistic uncertainty using the Hanman-Jeevan entropy function. The 2FInS features are validated on three databases: CASIA-C, OU-ISIR Treadmill-A and OU-ISIR Treadmill-D using Procrustes distance based classifier. In view of accounting both spatial and temporal information distributed throughout a gait cycle, the results obtained are superior to those of the existing methods.