Miracle-dz/UniFAR-FTUs huggingface dataset:
An Efficient Transfer Learning Technique by Using Final Fully-Connected Layer Output Features of Deep Networks

In this paper, we propose a computationally efficient transfer learning approach using the output vector of final fully-connected layer of deep convolutional neural networks for classification. Our proposed technique uses a single layer perceptron classifier designed with hyper-parameters to focus on improving computational efficiency without adversely affecting the performance of classification compared to the baseline technique. Our investigations show that our technique converges much faster than baseline yielding very competitive classification results. We execute thorough experiments to understand the impact of similarity between pre-trained and new classes, similarity among new classes, number of training samples in the performance of classification using transfer learning of the final fully-connected layer's output features.
Reassessment and Monitoring of Loan Applications with Machine Learning

ABSTRACT Credit scoring and monitoring are the two important dimensions of the decision-making process for the loan institutions. In the first part of this study, we investigate the role of machine learning for applicant reassessment and propose a complementary screening step to an existing scoring system. We use a real data set from one of the prominent loan companies in Turkey. The information provided by the applicants form the variables in our analysis. The company’s experts have already labeled the clients as bad and good according to their ongoing payments. Using this labeled data set, we execute several methods to classify the bad applicants as well as the significant variables in this classification. As the data set consists of applicants who have passed the initial scoring system, most of the clients are marked as good. To deal with this imbalanced nature of the problem, we employ a set of different approaches to improve the performance of predicting the applicants who are likely to default. In the second part of this study, we aim to predict the payment behavior of clients based on their static (demographic and financial) and dynamic (payment) information. Furthermore, we analyze the effect of the length of the payment history and the staying power of the proposed prediction models.
Magnetic resonance imaging analysis of work-related chronic low back pain: comparisons of different lumbar disc patterns

Background Currently, there is a lack of comparative research about different lumbar disc patterns in patients with work-related chronic low back pain (CLBP) based on magnetic resonance imaging (MRI) analysis. Therefore, this study, on different patterns of lumbar disc degeneration or herniation in patients with CLBP, is valuable. In this study, we retrospectively investigated lumbar degenerative changes in patients with CLBP by using MRI analysis. Materials and methods Two hundred and eighty-three patients (110 women and 173 men) with work-related CLBP were enrolled and divided into four groups based on intervertebral disc morphology from MRI analysis, including normal discs (ND) group, degenerative discs (DD) group, bulging discs (BD) group, and herniated discs (HD) group. Demographic characteristics, occupational information, Visual Analog Scale (VAS) scores, and Oswestry Disability Index (ODI) scores were analyzed. Moreover, multiple parameters were investigated in the MRI analysis. Results The mean age of all 283 patients was 41.8±12.0 years (range, 18–80) and the mean duration of CLBP for all patients was 24.5±24.9 months. There were no significant differences in the patients’ BMI, history of smoking, and education level (P>0.05). The three most common occupational types were manual worker, desk worker, and technician. The VAS and ODI scores of patients with CLBP in the DD, BD, and HD groups were significantly higher than those of patients in the ND group (P<0.05). The degrees of degeneration of L4/5 and L5/S1 were significantly higher than those of other intervertebral discs (P<0.05). The disc heights of L4/5 in the BD and HD groups were significantly lower than those of the ND group (P<0.05) and the disc height of L5/S1 in the HD group was significantly lower than that of the ND group (P<0.05). At the neutral position, the distances of L3/4, L4/5, and L5/S1 discs’ bulge/herniation in the BD and HD groups were significantly higher than those in the ND and DD groups (P<0.05). Conclusion In summary, more severe degenerative changes of lower lumbar discs (L4/5 and L5/S1) such as higher degree of degeneration of disc, lower disc height, and significant displacement of disc were found in patients with work-related CLBP based on MRI analysis.
The Effect of Mixed-Joint Bundling Strategy in the Hospitality Industry

Price bundling is one of the most important pricing strategies in the hospitality industry. This paper aims to investigate the specific importance of mixed-joint bundling strategy in hotels' profitability. Data was gathered through an ad hoc questionnaire, administrated in three and five-star hotels'. Univariate and bivariate techniques were performed to eventually identify statistical differences. The results show statistical differences between bundling with two services and bundling with more than two services included. Bundling strategy with restaurant service included is more attractive to customers in the hospitality industry. With these findings, managers can structure effective but different bundling solutions for both 3 and 5 stars hotels.
Improving Photoplethysmographic Measurements Under Motion Artifacts Using Artificial Neural Network for Personal Healthcare

Photoplethysmographic (PPG) measurements are susceptible to motion artifacts (MA) due to movement of the peripheral body parts. In this paper, we present a new approach to identify the MA corrupted PPG beats and then rectify the beat morphology using artificial neural network (ANN). Initially, beat quality assessment was done to identify the clean PPG beats by a pretrained feedback ANN to generate a reference beat template for each person. The PPG data were decomposed using principal component analysis (PCA) and reconstructed using fixed energy retention. A weight coefficient was assigned for each PPG sample in such a way that when they are multiplied, the modified beat morphology matches the reference template. A particle swarm optimization-based technique was utilized to select the best weight vector coefficients to tune another feedback ANN, fed with a set of significant features generated by an auto-encoder from PCA reconstructed data. For real-time implementation, this pretrained ANN was operated in feed-forward mode to directly generate the weight vectors for any subsequent measurements of PPG. The method was validated with PPG data collected from 55 human subjects. An average root-mean-square error of 0.28 and signal-to-noise ratio improvement of 14.54 dB were obtained, with an average improvement of 36% and 47% measurement accuracies on crest time and systolic to diastolic peak height ratio, respectively. With the IEEE Signal Processing Cup 2015 challenge database, Pearson’s correlation coefficient between PPG-estimated and ECG-derived heart rates was 0.990. The proposed method can be useful for personal health monitoring applications.
Loss of HDAC11 ameliorates clinical symptoms in a multiple sclerosis mouse model

In an animal model for multiple sclerosis, the absence of HDAC11 reduces clinical severity, spinal cord demyelination, and immune cell infiltration, suggesting that HDAC11 is a promising target for MS treatment. Multiple sclerosis (MS) is a chronic, immune-mediated, demyelinating disease of the central nervous system (CNS). There is no known cure for MS, and currently available drugs for managing this disease are only effective early on and have many adverse side effects. Results from recent studies suggest that histone deacetylase (HDAC) inhibitors may be useful for the treatment of autoimmune and inflammatory diseases such as MS. However, the underlying mechanisms by which HDACs influence immune-mediated diseases such as MS are unclear. More importantly, the question of which specific HDAC(s) are suitable drug targets for the potential treatment of MS remains unanswered. Here, we investigate the functional role of HDAC11 in experimental autoimmune encephalomyelitis, a mouse model for MS. Our results indicate that the loss of HDAC11 in KO mice significantly reduces clinical severity and demyelination of the spinal cord in the post-acute phase of experimental autoimmune encephalomyelitis. The absence of HDAC11 leads to reduced immune cell infiltration into the CNS and decreased monocytes and myeloid DCs in the chronic progressive phase of the disease. Mechanistically, HDAC11 controls the expression of the pro-inflammatory chemokine C–C motif ligand 2 (CCL2) gene by enabling the binding of PU.1 transcription factor to the CCL2 promoter. Our results reveal a novel pathophysiological function for HDAC11 in CNS demyelinating diseases, and warrant further investigations into the potential use of HDAC11-specific inhibitors for the treatment of chronic progressive MS.
A PB1-K577E Mutation in H9N2 Influenza Virus Increases Polymerase Activity and Pathogenicity in Mice

H9N2 avian influenza viruses are present in poultry worldwide. These viruses are considered to have pandemic potential, because recent isolates can recognize human-type receptor and several sporadic human infections have been reported. In this study, we aimed to identify mutations related to mammalian adaptation of H9N2 influenza virus. We found that mouse-adapted viruses had several mutations in hemagglutinin (HA), PB2, PA, and PB1. Among the detected mutations, PB1-K577E was a novel mutation that had not been previously reported to involve mammalian adaptation. A recombinant H9N2 virus bearing only the PB1-K577E mutation showed enhanced pathogenicity in mice, with increased virus titers in nasal turbinates compared to that in mice infected with the wild-type virus. In addition, the PB1-K577E mutation increased virus polymerase activity in human cell culture at a lower temperature. These data suggest that the PB1-K577E mutation is a novel pathogenicity determinant of H9N2 virus in mice and could be a signature for mammalian adaptation.
Design and Evaluation of Semi-Transparent Keyboards on a Touchscreen Tablet

As tablet computers are hosting more productivity applications, efficient text entry is becoming more important. A soft keyboard, which is the primary text entry interface for tablets, however, often competes with applications for the limited screen space. A promising solution to this problem may be a semi-transparent soft keyboard (STK), which can share the screen with an application. A few commercial STK products are already available, but research questions about the STK design have not been explored in depth yet. Therefore, we conducted three experiments to answer 1) the effect of the transparency level on usability, 2) exploration of diverse design options for an STK, and 3) the effect of an STK on the different text caret positions. The results imply that STKs with 50% opacity showed a balanced performance; well-designed STKs were acceptable in both content reading and typing situations; which could reach 90-100% of an opaque keyboard in terms of overall performance; and the text caret could intrude the STK down to the number row.
Deep Brain Stimulation Surgery for Parkinson Disease Coexisting With Communicating Hydrocephalus: A Case Report

We report a successful bilateral globus pallidus internus-deep brain stimulation (GPi-DBS) for a Parkinson disease (PD) patient with idiopathic normal pressure hydrocephalus (INPH) and an unusually long anterior commissure-posterior commissure (AC-PC) line. A 54-year-old man presented with a history of 3 months of severe shuffling gait, rigidity, slow movements of the left side limbs, and difficulty managing finances. A brain MRI revealed marked ventriculomegaly (Evans index = 0.42). The patient was diagnosed with INPH and a ventriculoperitoneal shunt was placed. Cognitive impairment improved, but walking disturbances, slowness, and rigidity persisted. Then treatment with levodopa was added, and the patient experienced a sustained improvement. He was diagnosed with PD. After 7 years, the patient developed gait freezing and severe levodopa-induced dyskinesia. The patient underwent bilateral GPi-DBS. We used MRI/CT fusion techniques for anatomical indirect targeting. Indirect targeting is based on standardized stereotactic atlas and on a formula—derived method based on AC-PC landmarks. The AC-PC line was 40 mm (the usual length is between 19 and 32 mm). Intraoperative microelectrode recording was a non-expendable test, but multiple recordings were avoided to reduce the surgical risk of ventricular involvement. There was a 71% decrease in the UPDRS III score during the on-stimulation state (28 to 8). The patient's dyskinesias resolved dramatically with a UdysRS of 15 (88% improvement) during the on-stimulation condition. The observed motor benefits and the improvement of his daily activities have persisted 6 months after surgery. Deep brain stimulation surgery in PD with ventriculomegaly is a challenge. This procedure can result in a greater chance of breaching the ventricle, with risks of intraventricular hemorrhage and migration of cerebrospinal fluid into the brain parenchyma with target displacement. Furthermore, clinical judgment is paramount when recent onset of shuffling gait coexists with ventriculomegaly because the most common dilemma is differentiating between PD and INPH. For these reasons, neurologists and surgeons may refuse to operate on PD patients with ventriculomegaly. However, DBS should be considered for PD patients with motor complications when responsiveness to levodopa is demonstrated, even in the context of marked ventriculomegaly.
Agent-based Modeling of Social Behavioral Challenges in Transportation

Agent-Based modeling has been around us for reasonably some time now and has thus developed a vital factor for performing prediction-based scheduling, such as the transportation models for municipal cities. This paper assumes the important understanding of the agent-based modelling and imitation and its application to the transportation models while deliberating the possibility of its applications and advantages too. The paper then presents the ideas recognised to the social behaviours in combination with the agent-based modelling procedures useful so far. The literature review showed in lieu of this work has caused in agreement with the fact that the applicability of agent-based modelling is by far superior than ever due to the ever-improving computing speeds and abilities, while the understanding of complex human behaviour will endure to be a challenge for imitations and mechanisation methods developed so far.
Decision and navigation in mouse parietal cortex

Posterior parietal cortex (PPC) has been implicated in navigation, in the control of body movement, and in visually-guided decisions. Seeking to relate these views, we measured activity in populations of PPC neurons while mice performed a virtual navigation task driven by visual decisions. We found that PPC neurons are selective for specific combinations of the animal’s spatial position and heading angle. This selectivity closely predicted both the activity of individual PPC neurons, and the arrangement of their collective firing patterns in choice-selective sequences. These sequences reflected the influence on PPC of the animal’s navigation trajectory. An alternative model in which PPC activity encoded position and decision performed more poorly, and a model with all three variables barely outperformed the simple position-heading model. Alternative models based on visual or motor variables were inferior. We conclude that when mice use vision to choose their trajectories, a large fraction of parietal cortex activity can be predicted from simple attributes such as spatial position and heading.
AMGSEFLamide, a member of a broadly conserved peptide family, modulates multiple neural networks in Homarus americanus

ABSTRACT Recent genomic/transcriptomic studies have identified a novel peptide family whose members share the carboxyl terminal sequence –GSEFLamide. However, the presence/identity of the predicted isoforms of this peptide group have yet to be confirmed biochemically, and no physiological function has yet been ascribed to any member of this peptide family. To determine the extent to which GSEFLamides are conserved within the Arthropoda, we searched publicly accessible databases for genomic/transcriptomic evidence of their presence. GSEFLamides appear to be highly conserved within the Arthropoda, with the possible exception of the Insecta, in which sequence evidence was limited to the more basal orders. One crustacean in which GSEFLamides have been predicted using transcriptomics is the lobster, Homarus americanus. Expression of the previously published transcriptome-derived sequences was confirmed by reverse transcription (RT)-PCR of brain and eyestalk ganglia cDNAs; mass spectral analyses confirmed the presence of all six of the predicted GSEFLamide isoforms – IGSEFLamide, MGSEFLamide, AMGSEFLamide, VMGSEFLamide, ALGSEFLamide and AVGSEFLamide – in H. americanus brain extracts. AMGSEFLamide, of which there are multiple copies in the cloned transcripts, was the most abundant isoform detected in the brain. Because the GSEFLamides are present in the lobster nervous system, we hypothesized that they might function as neuromodulators, as is common for neuropeptides. We thus asked whether AMGSEFLamide modulates the rhythmic outputs of the cardiac ganglion and the stomatogastric ganglion. Physiological recordings showed that AMGSEFLamide potently modulates the motor patterns produced by both ganglia, suggesting that the GSEFLamides may serve as important and conserved modulators of rhythmic motor activity in arthropods. Summary: A recently identified arthropod neuropeptide family is highly conserved within the crustaceans; one family member (AMGSEFLamide), which is highly conserved within the decapods, potently modulates three motor-pattern-generating circuits.
Effects of an Aqueous Extract of Withania somnifera on Strength Training Adaptations and Recovery: The STAR Trial

Withania somnifera (Ashwagandha) is an Ayurvedic herb categorized as having “rasayana” (rejuvenator), longevity, and revitalizing properties. Sensoril® is a standardized aqueous extract of the roots and leaves of Withania somnifera. Purpose: To examine the impact of Sensoril® supplementation on strength training adaptations. Methods: Recreationally active men (26.5 ± 6.4 years, 181 ± 6.8 cm, 86.9 ± 12.5 kg, 24.5 ± 6.6% fat) were randomized in a double-blind fashion to placebo (PLA, n = 19) or 500 mg/d Sensoril® (S500, n = 19). Body composition (DEXA), muscular strength, power, and endurance, 7.5 km cycling time trial, and clinical blood chemistries were measured at baseline and after 12 weeks of supplementation and training. Subjects were required to maintain their normal dietary habits and to follow a specific, progressive overload resistance-training program (4-day/week, upper body/lower body split). 2 × 2 mixed factorial ANOVA was used for analysis and statistical significance was set a priori at p ≤ 0.05. Results: Gains in 1-RM squat (S500: +19.1 ± 13.0 kg vs. PLA +10.0 ± 6.2 kg, p = 0.009) and bench press (S500: +12.8 ± 8.2 kg vs. PLA: +8.0 ± 6.0 kg, p = 0.048) were significantly greater in S500. Changes in DEXA-derived android/gynoid ratio (S500: +0.0 ± 0.14 vs. PLA: +0.09 ± 0.1, p = 0.03) also favored S500. No other between-group differences were found for body composition, visual analog scales for recovery and affect, or systemic hemodynamics, however, only the S500 group experienced statistically significant improvements in average squat power, peak bench press power, 7.5 km time trial performance, and perceived recovery scores. Clinical chemistry analysis indicated a slight polycythemia effect in PLA, with no other statistical or clinically relevant changes being noted. Conclusions: A 500 mg dose of an aqueous extract of Ashwagandha improves upper and lower-body strength, supports a favorable distribution of body mass, and was well tolerated clinically in recreationally active men over a 12-week resistance training and supplementation period.
Non-clinical isolates as potential reservoirs of antibiotic resistance in Port Harcourt, Nigeria

Introduction Multidrug resistance (MDR) is a growing problem worldwide. This type resistance often arises due to the sequential acquisition of drug resistance determinants and subsequent clonal spread. It is therefore important to determine possible reservoirs of these MDR gene to help set out control strategies. This study was aimed at analysing susceptibility patterns of various non-clinical Gram negative bacterial strains to determine their potential as reservoirs of MDR. Methods Thirty-five non-clinical Gram negative bacteria were identified and susceptibility profile determined using standard methodologies. Results Findings showed a preponderance of Pseudomonas aeruginosa and Escherichia Coli. Resistance rates of above 80% were noted in 50% of antibiotics, though none of the isolates were resistant to Ofloxacin. Majority of isolates (68.6%) had a multiple antibiotic resistance (MAR) index greater than 0.5, but only 20% of Escherichia Eoli. were found in this category. A high level of MDR was noted in this study (71.4%), but again only 20% of these were Escherichia Coli. Conclusion Gram negative bacteria are the most common group of bacteria frequently encountered in clinical microbiology. In more recent years, infections with these organisms have been further complicated by the phenomenon of drug resistance. Non-clinical isolates have been postulated as possible reservoirs. Findings from this study of widespread multidrug resistance support this idea. This study however highlights the lack of MDR in Escherichia Coli, which is promising. More extensive studies will need to be carried out to properly assess the role of non-clinical isolates as reservoirs of MDR determinants.