Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of vocal tract disorders using Mel-Frequency Cepstral Coefficients and Empirical Mode Decomposition based features

This work investigates the possibility of developing a non-invasive technique for the detection of vocal tract disorders from voice samples of patients. The existing techniques are invasive, expensive or both and hence the relevance of this study. Mel-Frequency Cepstral Coefficients (MFCC), dynamic measures derived from MFCC and statistical features extracted from Empirical Mode Decomposition (EMD) of voice samples provide distinct features capable of discriminating pathological and normal voice samples. A Support Vector Machine (SVM) classifier is used for classification. Experimental evaluations on a voice database created from videostroboscopy data yield accuracies more than 90%. It is observed that although MFCC is a good discriminating feature as far as speech/voice segments are considered, EMD, being a significant analysis technique for non-linear, non-stationary signals, also proves to give good discrimination possibilities for detecting vocal tract disorders.
The lived experiences of late-adolescent female suicide survivors: ‘A part of me died’

People’s thoughts often focus on the suicide victim immediately after a completed suicide. Yet, the real victims of such an event are those individuals who are left behind to cope with the aftermath of the suicide. This phenomenological psychological study explored the lived experiences of late-adolescent suicide survivors, particularly those negative experiences that seemed to worsen in the weeks and months after a significant other’s completed suicide. The research participants were five female late-adolescents (aged 17–22 years) who were recruited by means of purposive sampling at a South African tertiary institution and at youth camps. Data collection consisted of collage-facilitated, face-to-face phenomenological interviews. In addition, some participants provided documentary material in the form of personal diaries, letters and poems. The data analysis was conducted according to Giorgi’s phenomenological method. The following salient experiences emerged during the data analysis: guilt, self-blame, blaming others or God, anger, loss or restriction of ‘self’, depression, suboptimal behavioural coping patterns, changes in relationship dynamics, and suicidality. The results of this study can be used by mental health professionals and caregivers to support adolescent suicide survivors effectively, in the midst of their mourning. Opsomming Mense se gedagtes fokus meestal op die selfmoordslagoffer onmiddellik na ’n voltooide selfmoord. Tog is die werklike slagoffers die persone wat agterbly om die lewe na die selfmoord te hanteer. Hierdie fenomenologies-sielkundige studie het die geleefde belewenisse van laat-adolessente oorlewendes ondersoek, spesifiek daardie negatiewe belewenisse wat skynbaar erger word in die weke en maande na ’n betekenisvolle ander se voltooide selfmoord. Die navorsingsdeelnemers was vyf vroulike laat-adolessente (17–22 jaar oud) wat gewerf is deur middel van doelgerigte selektering by ’n Suid-Afrikaanse tersiere instelling en jeugkampe. Data-insameling het geskied aan die hand van collage-gefasiliteerde, aangesig-tot-aangesig fenomenologiese onderhoude. Sommige deelnemers het addisionele dokumente in die vorm van persoonlike dagboeke, briewe en gedigte beskikbaar gestel vir data-analise. Die data is geanaliseer volgens Giorgi se fenomenologiese metode. Die volgende belewenisse het na vore getree tydens die data-analise: skuldgevoelens, self-blaam/spyt, blameer ander/God, woede, verlies/inperking van ‘self’, depressie, sub-optimale gedragshanteringspatrone, veranderinge in verhoudingsdinamika, en selfmoordneigings. Die resultate van hierdie studie kan deur geestesgesondheidwerkers en versorgers aangewend word om adolessente selfmoordagtergeblewenes effektief te ondersteun in die rouproses.
X‐linked mental retardation: focus on synaptic function and plasticity

Among mental disorders, mental retardation has been shown to be caused by various factors including a large array of genetic mutations. On the basis of remarkable progress, the emerging view is that defects in the regulation of synaptic activity and morphogenesis of dendritic spines are apparently common features associated with mutations in several genes implicated in mental retardation. In this review, we will discuss X‐linked MR‐related gene products that are potentially involved in the normal structure and function of the synapses, with a particular focus on pre‐ and/or post‐synaptic plasticity mechanisms. Progress in understanding the underlying conditions leading to mental retardation will undoubtedly be gained from a closer collaboration of geneticists, physiologists and cognitive neuroscientists, which should enable the establishment of standardized approaches.
The Stress-Activated Signaling (SAS) Pathways of a Human Fungal Pathogen, Cryptococcus neoformans

Abstract Cryptococcus neoformans is a basidiomyeete human fungal pathogen that causes meningoencephalitis in both immunocompromised and immunocompetent individuals. The ability to sense and respond to diverse extracellular signals is essential for the pathogen to infect and cause disease in the host. Four major stress-activated signaling (SAS) pathways have been characterized in C. neoformans, including the HOG (high osmolarity glycerol response), PKC/Mpkl MAPK (mitogen-activated protein kinase), ealeium-dependent ealeineurin, and RAS signaling pathways. The HOG pathway in C. neoformans not only controls responses to diverse environmental stresses, including osmotic shock, UV irradiation, oxidative stress, heavymetal stress, antifungal drugs, toxic metabolites, and high temperature, but also regulates ergosterol biosynthesis. The PKC (Protein kinase C)/Mpkl pathway in C. neoformans is involved in a variety of stress responses, including osmotic, oxidative, and nitrosative stresses and breaches of cell wall integrity. The Ca2+/ealmodulin- and Ras-signaling pathways also play critical roles in adaptation to certain environmental stresses, such as high temperature and sexual differentiation. Perturbation of the SAS pathways not only impairs the ability of C. neoformans to resist a variety of environmental stresses during host infection, but also affects production of virulence factors, such as capsule and melanin. A drug(s) capable of targeting signaling components of the SAS pathway will be effective for treatment of cryptococcosis.
An Opportunistic Downlink Mimo-Ofdm Scheme

This paper presents an opportunistic multiple-input multiple-output (MIMO) scheme that achieves increased throughput of multi-user downlink transmission in frequency-selective channels. Developed for OFDM systems, the main idea of the proposed scheme is to find the optimal subset of users for each subchannel and optimal transmit beamforming vector which would maximize the sum-rate. Assuming perfectly known channel information, an optimal solution is derived and a suboptimal solution with much lower complexity that provides comparable results to the optimal solution is also presented. The proposed scheme outperforms the existing FDMA-based and SDMA-based schemes significantly in terms of sum-rate by efficiently exploiting the time-varying nature of radio channels and multi-user diversity
Insights into melanoma: targeting the mTOR pathway for therapeutics

Introduction: Cutaneous melanoma represents < 5% of all skin cancers, but is responsible for the majority of skin cancer-related deaths. Ocular melanoma is the most common primary eye tumor in adults, and accounts for approximately 5% of all melanomas. Despite new diagnostic and therapeutic tools, the overall survival of patients treated for melanoma has not improved and most patients die of metastatic disease. Therefore, clarification of the molecular mechanisms underlying the etiopathogenesis of cutaneous and ocular melanomas may help determining the prognosis and tailoring therapy of patients harboring melanomas. Areas covered: In this review the authors aim to survey relevant research in the molecular mechanisms underlying melanomagenesis, and therapies under evaluation with emphasis in the mTOR pathway. Expert opinion: Despite an increasingly understanding of the genetics and biochemistry of melanoma, the mechanisms underlying their complex interactions are still poorly understood. Their clarification will lead to more successful therapeutic strategies and evidence-based management of patients with melanoma. More active drug combinations together with appropriate melanoma patient stratification based on molecular biomarkers will be essential for new advances in melanoma therapy.
Cancer Management and Research Dovepress Microrna Dysregulation as a Prognostic Biomarker in Colorectal Cancer

Colorectal cancer (CRC) is one of the most potentially curable cancers, yet it remains the fourth most common overall cause of cancer death worldwide. The identification of robust molecular prognostic biomarkers can refine the conventional tumor–node–metastasis staging system, avoid understaging of tumor, and help pinpoint patients with early-stage CRC who may benefit from aggressive treatments. Recently, epigenetic studies have provided new molecular evidence to better categorize the CRC subtypes and predict clinical outcomes. In this review, we summarize recent findings concerning the prognostic potential of microRNAs (miRNAs) in CRC. We first discuss the prognostic value of three tissue miRNAs (miR-21-5p, miR-29-3p, miR-148-3p) that have been examined in multiple studies. We also summarize the dysregulation of miRNA processing machinery DICER in CRC and its association with risk for mortality. We also reviewe the potential application of miRNA-associated single-nucleotide polymorphisms as prognostic biomarkers for CRC, especially the miRNA-associated polymorphism in the KRAS gene. Last but not least, we discuss the microsatellite instability-related miRNA candidates. Among all these candidates, miR-21-5p is the most promising prognostic marker, yet further prospective validation studies are required before it can go into clinical usage.
Optimally organizing distributed-component computing in the clouds: From both the user perspective and resource view

With the sharp increase of computing demands, computations more and more rely on the distributed components. However, the relatively inferior quality of wide-area networks hampers such trend. This paper proposes an approach aiming at optimally organizing the distributed-component computing in the current Internet in which some nodes with large computational freedom and capability for the public to compute are emerging, such as the initially born data centers in the present Cloud computing environments. Both the user experience and the resource utilization are taken into the quantitative analysis and optimization. Facing the exponential growth of the problem's solution space, this paper develops an effective approach. Experimental simulations show that the approach generates the result significantly approximating the optimal solution, in the meantime with high efficiency.
Propagation de fronts et p-laplacien normalisé sur graphes : algorithmes et applications au traitement d'images et de données. (Fronts propagation and normalized p-laplacien on graphs : Algorithms and applications to images and data processing)

Cette these s'interesse a la transcription d'equations aux derivees partielles vers des domaines discrets en exploitant le formalisme des equations aux differences partielles definies sur des graphes ponderes. Dans une premiere partie, nous proposons une transcription de l'operateur p-laplacien normalise au domaine des graphes comme une combinaison lineaire entre le laplacien infini non-local et le laplacien normalise (ces deux operateurs etant discrets). Cette adaptation peut etre consideree comme une nouvelle classe d'operateurs p-laplaciens sur graphes, qui interpolent entre le laplacien infini non-local et le laplacien normalise. Dans une seconde partie, nous nous interessons aux equations de propagation de fronts sur des graphes de topologie arbitraire. Ces equations sont obtenues par la transcription de la methode des ensembles de niveaux, definie en continu, vers une formulation discrete definie sur le domaine des graphes. Au dela de la transcription en elle-meme, nous proposons une formulation generale et des algorithmes efficaces pour la propagation simultanees de plusieurs fronts evoluant sur un graphe. Les approches proposees dans ces deux premieres parties donnent lieu a de nombreuses applications en segmentation d'images et classification de donnees que nous illustrons dans ce manuscrit. Enfin, dans une troisieme partie, nous presentons une application a l'aide au diagnostic informatise concretisant l'emploi des differents outils proposes dans les deux premieres parties. Nous presentons egalement le logiciel Antarctic developpe au cours de cette these.
Liposome‐encapsulated curcumin

Because a role for nuclear factor‐κB (NF‐κB) has been implicated in the pathogenesis of pancreatic carcinoma, this transcription factor is a potential target for the treatment of this devastating disease. Curcumin (diferuloylmethane) is a phytochemical with potent NF‐κB‐inhibitory activity. It is pharmacologically safe, but its bioavailability is poor after oral administration.
Practical scrubbing: Getting to the bad sector at the right time

Latent sector errors (LSEs) are a common hard disk failure mode, where disk sectors become inaccessible while the rest of the disk remains unaffected. To protect against LSEs, commercial storage systems use scrubbers: background processes verifying disk data. The efficiency of different scrubbing algorithms in detecting LSEs has been studied in depth; however, no attempts have been made to evaluate or mitigate the impact of scrubbing on application performance. We provide the first known evaluation of the performance impact of different scrubbing policies in implementation, including guidelines on implementing a scrubber. To lessen this impact, we present an approach giving conclusive answers to the questions: when should scrubbing requests be issued, and at what size, to minimize impact and maximize scrubbing throughput for a given workload. Our approach achieves six times more throughput, and up to three orders of magnitude less slowdown than the default Linux I/O scheduler.
Diagnostics for Joint Longitudinal and Dropout Time Modeling

Summary. We present a variety of informal graphical procedures for diagnostic assessment of joint models for longitudinal and dropout time data. A random effects approach for Gaussian responses and proportional hazards dropout time is assumed. We consider preliminary assessment of dropout classification categories based on residuals following a standard longitudinal data analysis with no allowance for informative dropout. Residual properties conditional upon dropout information are discussed and case influence is considered. The proposed methods do not require computationally intensive methods over and above those used to fit the proposed model. A longitudinal trial into the treatment of schizophrenia is used to illustrate the suggestions.
Valuing Diversity and Widening Participation: The Experiences of Access to Social Work Students in Further and Higher Education

Social work is one of the success stories of Access to Higher Education. University departments of social work along with nursing and the allied health professions, recruit more former Access students than any other areas of study. This paper explores the experiences of Access students prior to and during their experience on a particular university social work programme in the light of the government's agenda for widening participation in higher education and the introduction of the new degree in social work.
Prioritizing variants in complete Hereditary Breast and Ovarian Cancer (HBOC) genes in patients lacking known BRCA mutations

BRCA1 and BRCA2 testing for HBOC does not identify all pathogenic variants. Sequencing of 20 complete genes in HBOC patients with uninformative test results (N=287), including non-coding and flanking sequences of ATM, BARD1, BRCA1, BRCA2, CDH1, CHEK2, EPCAM, MLH1, MRE11A, MSH2, MSH6, MUTYH, NBN, PALB2, PMS2, PTEN, RAD51B, STK11, TP53, and XRCC2, identified 38,372 unique variants. We apply information theory (IT) to predict and prioritize non-coding variants of uncertain significance (VUS) in regulatory, coding, and intronic regions based on changes in binding sites in these genes. Besides mRNA splicing, IT provides a common framework to evaluate potential affinity changes in transcription factor (TFBSs), splicing regulatory (SRBSs), and RNA-binding protein (RBBSs) binding sites following mutation. We prioritized variants affecting the strengths of 10 splice sites (4 natural, 6 cryptic), 148 SRBS, 36 TFBS, and 31 RBBS. Three variants were also prioritized based on their predicted effects on mRNA secondary (2°) structure, and 17 for pseudoexon activation. Additionally, 4 frameshift, 2 in-frame deletions, and 5 stop-gain mutations were identified. When combined with pedigree information, complete gene sequence analysis can focus attention on a limited set of variants in a wide spectrum of functional mutation types for downstream functional and co-segregation analysis.
Prenatal Cytomegalovirus Disease and Cerebral Microgyria: Evidence for Perfusion Failure, not Disturbance of Histogenesis, as the Major Cause of Fetal Cytomegalovirus Encephalopathy

From the study of four personal cases of microgyria related to fetal CMV infection and a review of the literature it is concluded that: 1) Microgyria is a frequent neuropathological finding in this disease - 2) CMV microgyria is the result of an insufficiency of cerebral blood supply and is not due to a disturbance of neurogenesis or histogenesis as a consequence of a direct cytopathic effect of the virus on germinal cells. The way by which the CMV causes cerebral ischemia - angeitis or more probably, transient systemic perfusion failure, - is discussed, but remains obscure. Other viruses may act on the fetal brain by way of circulatory disturbances.
Index-Based Approach to Similarity Search in Protein and Nucleotide Databases

When searching databases of nucleotide or protein sequences, finding a local alignment of two sequences is one of the main tasks. Since the sizes of available databases grow constantly, the eciency of retrieval methods becomes the critical issue. The sequence retrieval re- lies on finding sequences in the database which align best with the query sequence. However, an optimal alignment can be found in quadratic time (by use of dynamic programming) while this is infeasible when dealing with large databases. The existing solutions use fast heuristic methods (like BLAST, FASTA) which produce only an uncontrolled approxima- tion of the best alignment and even do not provide any information about the alignment approximation error. In this paper we propose an approach of exact and approximate indexing using several metric access methods (MAMs) in combination with the TriGen algorithm, in order to reduce the number of alignments (distance computations) needed. The exper- imental results have shown that a straightforward adoption of MAMs to sequence retrieval cannot outperform the specialized heuristic algo- rithms (at least at the moment). On the other side, the results show MAMs could provide a basis for specialized access methods capable of precision/ecienc y trade-o control.
Robust activity recognition for assistive technologies: Benchmarking machine learning techniques

An increasing need for healthcare provision and assistive technologies (AT) calls for the development of machine learning techniques able to cope with the variability inherent to real-world deployments. In the particular case of activity recognition applications sensor networks may be prone to changes at different levels ranging from sensor data variability to network reconfiguration. Robust methods are required to deal with those changes providing graceful degradation upon failure or self-configuration and adaptation capabilities that ensure their proper operation for long periods of time. Currently there is a lack of common tools and datasets that allow for replicable and fair comparison of different recognition approaches. We introduce a large database of human daily activities recorded in a sensor-rich environment. The database provides large amount of instances of the recorded activities using a significant number of sensors. In addition, we reviewed some of the techniques that have been proposed to cope with changes in the system, including missing data, sensor location/orientation change, as well as the possibility to exploit data from unknown discovered sensors. These techniques have been tested in the aforementioned datasets showing its suitability to emulate different sensor network configurations and recognition goals.
A 12-year population-based study of psychosis in Parkinson disease.

OBJECTIVE To investigate the prevalence, incidence, risk factors, and concomitants of Parkinson disease (PD)-associated psychosis (PDP) in a population-based prevalent cohort. DESIGN Prospective longitudinal cohort study. SETTING Community-based study in southwestern Norway. PARTICIPANTS Two hundred thirty community-based PD patients were followed up prospectively for 12 years. Reassessments were conducted at 4 and 8 years and then annually. MAIN OUTCOME MEASURES Severity of PDP was measured by the Unified Parkinson Disease Rating Scale thought disorder (UPDRS-TD) item. Patients with a UPDRS-TD score of 2 or more or those taking antipsychotic drugs owing to psychotic symptoms were categorized at each visit as having PDP. Generalized estimating equations were applied to investigate baseline risk factors for incident PDP and clinical and demographic concomitants of PDP during 12 years. RESULTS By study's end, 137 patients (60%) had developed hallucinations or delusions. The incidence rate of PDP was 79.7 per 1000 person-years. Higher age at onset, higher baseline levodopa-equivalent doses, probable rapid eye movement (REM) sleep behavior disorder at baseline, and follow-up time were independent risk factors of incident PDP. Significant concomitant features of patients with PDP during the 12-year study period were low activities of daily living function (UPDRS II), dementia, high levodopa-equivalent dose, and probable REM sleep behavior disorder. CONCLUSIONS Psychotic symptoms affect most patients with PD, with increased risk in those with higher age at onset, need for high doses of dopaminergic drugs, and probable REM sleep behavior disorder. This risk factor pattern and the observed associations with increased disability and dementia place PDP within a symptom complex signaling a malignant disease course.
WebIQ: Learning from the Web to Match Deep-Web Query Interfaces

Integrating Deep Web sources requires highly accurate semantic matches between the attributes of the source query interfaces. These matches are usually established by comparing the similarities of the attributes’ labels and instances. However, attributes on query interfaces often have no or very few data instances. The pervasive lack of instances seriously reduces the accuracy of current matching techniques. To address this problem, we describe WebIQ, a solution that learns from both the Surface Web and the Deep Web to automatically discover instances for interface attributes. WebIQ extends question answering techniques commonly used in the AI community for this purpose. We describe how to incorporate WebIQ into current interface matching systems. Extensive experiments over five realworld domains show the utility ofWebIQ. In particular, the results show that acquired instances help improve matching accuracy from 89.5% F-1 to 97.5%, at only a modest runtime overhead.