Miracle-dz/UniFAR-FTUs huggingface dataset:
IoT-enabled water monitoring and control for smart city

In a world when resources of living are scarce, urban people are suffering from a crisis of potable drinking water. The massive increase and concentration of human population in urban areas are liable for consumption of the vast majority of resources. Therefore it is highly pertinent to make cities greener and more sustainable. Advanced systems developed to improve and automate processes within a city will play a leading role in smart cities. From the intelligent design of buildings, which capture and harvest rainwater for future use, to smart control systems, which can monitor infrastructures autonomously, the possible improvements enabled by sensing technologies are of utmost importance. Internet of things (IoT)-enabled sensing and control poses numerous challenges, which are of a technological and social nature. The IoT solutions of smart water can help water utilities to coordinate analysis of supply and demand to provide smooth control actions across large numbers of distributed smart assets to monitor and deliver optimized performance to entire water production and distribution network. This ensures minimum water loss, assured water quality and quantity to every consumer. It is an excellent challenge in technology, and IoT-enabled smart assets will play a vital role towards the solution. The plugin Internet interface modules are developed to convert existing sensor and actuator system for secure and speedier communication of data to the central decision system either situated in the plant or in a cloud. All smart devices for water monitoring systems are M2M enabled and can share information directly or through the central system. The smart water solution technology is applicable for improvement of overall performance, quality and reliability of water and wastewater treatment and distribution system. The topic includes remote-based pipe monitoring and leak detection system to minimize nonrevenue water and to restore water supply in 24×7 manners with active operational management in damaged assets.
ROLE OF ORAL MIDAZOLAM AS A PROCEDURAL SEDATIVE IN CHILDREN AGED 6 MONTHS TO 12 YEARS

Pediatric procedural sedation is a safe, effective and humane way to facilitate appropriate medical care. We conducted a prospective, open-label randomized controlled trial in 272 children in the age group of 6 months to 12 years who need to undergo a procedure requiring pain or anxiety management. The objective was to evaluate the efficacy and safety profile of oral midazolam in comparison with intravenous midazolam. Out of 272 children, 42.5% children underwent invasive procedures and the rest non-invasive. For non-invasive procedures, 79% subjects in the oral group were adequately sedated, compared to 63% in the intravenous group. For invasive procedures, 71% subjects were adequately sedated with oral midazolam and 78% in intravenous group. 85% procedures were successfully completed in oral group compared to 79% in intravenous. Occurrence of adverse effects like desaturation, apnea and paradoxical hyper agitation was less with oral midazolam compared to intravenous.
Unsupervised Learning of Depth and Visual Odometry using Photometric Calibration

Depth and visual odometry estimation are two essential parts in SLAM systems. Compared with traditional algorithms, supervised learning methods have shown promising results in single view depth estimation and visual odometry estimation. However, they require large amounts of labeled data. Recently, some unsupervised approaches to estimate depth and odometry via minimizing photometric error draw great attention. In this paper, we present a novel approach to learn depth and odometry via unsupervised learning. Our method ameliorates the original photometric loss to enhance the robustness to illumination change in real scenarios. In addition, we propose a new structure of Pose-net and Explainability-net to achieve rotation-sensitive odometry results and more accurate explainability masks. The experimental results have demonstrated that our approach achieves better performance than existing unsupervised methods in both depth and odometry results.
Clinical Evaluation of a New Hysteroscopic Morcellator—Retrospective Case Review

Objective: The objective of this study was to clinically assess the cutting efficiency and safety of a new hysteroscopic morcella tor. Methods: A retrospective review of medical records for 11 premenopausal women who had been treated with the new hys teroscopic morcellator was conducted at 4 hospital or ambulatory surgical center sites. Four physicians performed hysteroscop ic operative procedures to remove intrauterine polyps and type 0 (completely within the uterine cavity), type I (mostly within the cavity), and type II (< 40% within the cavity) submucous myomas. Percent pathology removed, total morcellation time, total fluid used, fluid deficit, and treatment-related adverse events were assessed. Results: In all cases involving polyps and type 0 and type I submucous myomas, 100% of target pathology was removed by the morcellator device. The morcellator removed 50% of target pathology (100% of the intrauterine portion) in the single case involving a type II submucous myoma. For all cases, mean morcel lation time was 3 minutes 3 seconds (range 14 seconds for polyps ≤ 1 cm to 22 minutes 38 seconds for a 4 cm submucous myoma). Fluid deficits for the reported cases ranged from 30 mL to 1,900 mL based on the size of the pathology and associated duration of the procedure. None of the study subjects experienced an adverse event. Conclusions: Early data suggest that this new hysteroscopic morcellator may be a safe and efficient treatment option for the removal of intracavity myomas and polyps.
Prediction of User Emotion and Dialogue Success Using Audio Spectrograms and Convolutional Neural Networks

In this paper we aim to predict dialogue success and user satisfaction as well as emotion on a turn level. To achieve this, we investigate the use of spectrogram representations, extracted from audio files, in combination with several types of convolutional neural networks. The experiments were performed on the Let’s Go V2 database, comprising 5065 audio files and having labels for subjective and objective dialogue turn success, as well as the emotional state of the user. Results show that by using only audio, it is possible to predict turn success with very high accuracy for all three labels (90%). The best performing input representation were 1s long mel-spectrograms in combination with a CNN with a bottleneck architecture. The resulting system has the potential to be used real-time. Our results significantly surpass the state of the art for dialogue success prediction based only on audio.
Esophagus Detection for Halal Classification in SYCUT

According to the Islamic Law, one of the procedures in halal slaughtering of chicken is the step of severing the trachea, esophagus and both the carotid arteries and jugular veins to accelerate the chicken’s bleeding and death. Syariah Compliance Automated Chicken Processing System (SYCUT) uses the Vision Inspection Technology to detect and classify whether a chicken is halal or not. The lack of quality and halal assurance in chicken processing industry made it a need to produce such technology. The system implements image processing techniques and artificial intelligence approach, particularly the Viola and Jones object detection framework for esophagus detection. The results of the experiment from two different sites (Az-Zain and 3P) are 81.8% and 55% respectively. The detection module of those two sites show results of 95.6% and 93.5% which are the accuracy as good as human personnel.
DscoreApp: An user-friendly web application for computing the Implicit Association Test D-score

The Implicit Association Test (IAT; Greenwald, McGhee, & Schwartz, 1998) is one of the most commonly used measures in psychology for the implicit assessment of attitudes and preferences. It is based on the speed and accuracy with which stimuli representing four different categories (e.g., flowers and insects, positive and negative words in a Flowers-Insects IAT) are assigned to the category to which they belong by means of two response keys. The IAT is usually composed of seven blocks, three of which are pure practice blocks where either flowers-insects images or positive-negative words are sorted in their categories. The remaining four blocks are associative practice and associative test blocks. These blocks forms the two contrasting associative conditions under which the categorization task takes place. In one associative condition (i.e., practice blocks Mapping A and test blocks Mapping A), images of flowers and positive words share the same response key, while images of insects and negative words share the other response key. In the contrasting associative condition (i.e., practice blocks Mapping B and test blocks Mapping B), images of insects and positive words share the same response key, while images of flowers and negative words share the opposite response key.
Finite-Time Observer-Based Sliding Mode Control for Quantized Semi-Markov Switching Systems With Application

This article investigates the problem of sliding mode control (SMC) for semi-Markov switching systems (S-MSSs) with quantized measurement in finite-time level. The transition between different subsystems obeys a stochastic semi-Markov process related to nonexponential distribution. Additionally, due to the sensor information constraints, the state vectors are not always measurable in practice. Moreover, compared with existing results in literature, the output quantization is first considered for finite-time SMC problem via a logarithmic quantizer. Our attention is to design an appropriate finite-time SMC law to attenuate the influences of parametrical uncertainty and external disturbance onto the overall performance of the system under consideration. First, by the key points of stochastic semi-Markov Lyapunov function and observer design theory, a desired SMC law is constructed to guarantee that the system trajectories can arrive at the specified sliding surface (SSS) within an assigned finite-time level. Then, ST-dependent sufficient conditions are established to ensure the required finite-time boundedness performance including both reaching phase and sliding motion phase. Finally, the applicability of the proposed results is demonstrated by a single-link robot arm model.
A Comparative Study for Management of Anemia in Elective Surgery Patients with Combination of IV Iron and Erythropoietin Alpha Vs Hemotransfusion

Title: A COMPARATIVE STUDY FOR MANAGEMENT OF ANAEMIA IN ELECTIVE SURGERY PATIENTS WITH COMBINATION OF IV IRON AND ERYTHROPOIETIN ALPHA VS HEMOTRANSFUSION Background: Generally defined, anemia is present when the hemoglobin concentration is below a normal value based on the reference population. The mean normal value of hemoglobin is dependent on age, gender, race, and altitude. According to WHO criteria, the lower limit of normal in adults is 13 g/dL in men and 12 g/dL in women. Anaemia is believed to increase the risk of surgery, and it is common practice for non-urgent surgery to be postponed if a patient is anaemic. The level of circulating haemoglobin below which such an effect exists is, however, unknown. Nor is it known whether the risk is real. The justification for considering anaemia as a risk is based on the theoretical concept of oxygen flux (Freeman and Nunn, 1963). This study is aimed to evaluate the efficacy of the combination therapy of intravenous iron sucrose and subcutaneous human recombinant erythropoietin alpha therapy in reducing the need for blood transfusion and maintenance of hemoglobin level in perioperative management of patients undergoing elective surgery. Methods: A hospital based Prospective Comparative Study was undertaken among pre-operative patients. It is a prospective randomized control trial. A total number of 100 patients (50 in each group) will be enrolled. Group A will be study group and Group B will be control group. Patient will be screened prior to enrollment and eligibility will be assessed by specific inclusion and exclusion criteria.
Implantation of an Intraocular Silicone Prosthesis in a Great Horned Owl (Bubo virginianus)

A mature great horned owl (Bubo virginianus) was presented to a raptor rehabilitation center because of head injury and severe trauma to the left eye. Ophthalmic examination revealed a painful left eye with evidence of chronic inflammation and blindness. After evisceration of the left eye, an intraocular silicone prosthesis was implanted to maintain symmetry of the head. Three weeks after surgery, a corneal ulcer developed in the left eye. Attempts to manage the ulcer with topical therapy were unsuccessful. After superficial debridement, a conjunctival pedicle graft was done, and the eye was then treated with topical antifungal and antibacterial agents. The pedicle graft remained intact. The owl was intended to be used as a permanent resident and educational tool. However, because of its aggressive nature and its ability to capture and kill live prey, the owl underwent flight training and was subsequently released into the wild.
Assesment of Platelet Indices in Post-Cesarean Section Surgical Site Infections

Backround: We aimed to investigate the association of platelet count (PLT) and MPV/PLT ratio with the development of surgical site infections ( SSI) in patients who have undergone elective cesarean section (CS). Materials and Methods: We retrospectively evaluated patients who underwent elective cesarean section and 44 patients (mean age 28.7±7.3 years) who encountered surgical site infection (infection group) and 42 patients (mean age 27.8±6.1 years) without surgical site infection after cesarean section (normal group) were enrolled in the study. Results: Platelet count (291.7±46.8 10 3 /µL vs. 235.4 ± 64.7 10 3 /µL; p< 0.001) was decreased and MPV/PLT ratio (0.035±0.006 vs 0.047±0.02.; p= 0.01) was statistically increased in infection group Conclusions: Patients undergoing elective cesarean section and experiencing surgical site infections have higher MPV/PLT ratio than patients without SSI. These measurements may provide clues for the development of SSI and allow clinicians to recognize and monitor patients under substantial risk for development of SSI and offers an opportunity to evolve systematic approaches to eliminate or reduce risk factors.
Natural Language Processing Methods for Acoustic and Landmark Event-Based Features in Speech-Based Depression Detection

The processing of speech as an explicit sequence of events is common in automatic speech recognition (linguistic events), but has received relatively little attention in paralinguistic speech classification despite its potential for characterizing broad acoustic event sequences. This paper proposes a framework for analyzing speech as a sequence of acoustic events, and investigates its application to depression detection. In this framework, acoustic space regions are tokenized to ‘words’ representing speech events at fixed or irregular intervals. This tokenization allows the exploitation of acoustic word features using proven natural language processing methods. A key advantage of this framework is its ability to accommodate heterogeneous event types: herein we combine acoustic words and speech landmarks, which are articulation-related speech events. Another advantage is the option to fuse such heterogeneous events at various levels, including the embedding level. Evaluation of the proposed framework on both controlled laboratory-grade supervised audio recordings as well as unsupervised self-administered smartphone recordings highlight the merits of the proposed framework across both datasets, with the proposed landmark-dependent acoustic words achieving improvements in F1(depressed) of up to 15% and 13% for SH2-FS and DAIC-WOZ respectively, relative to acoustic speech baseline approaches.
The Effects of Circuit Training on Muscle Strength and Resistance

The circuit is a methodical procedure with highly efficient effects in the development of motor qualities, mainly strength and resistance. The purpose of this paper was to demonstrate the efficiency of training in the circuit in the development of this motor quality. The sample within the research comprised 30 women aged 25-35 and who practiced 3 practices per week for 6 months. The independent variable included circuits for beginners (30” workout - 30” pause), circuits for middle level (45” workout - 30” pause) and circuits for advanced (50” workout - 30” pause). The tests applied concerned the strength and resistance of abdominal muscles, of the back, of the legs and of the arms. Findings. In the test for the strength and resistance of abdominal muscles, the values of the average and of standard deviation were 13.8 ±1.52 initially and 15.2 ±1.08 finally; concerning the strength and resistance of the back muscles, the values increased from 21.46 ±1.684 initially to 23.53 ±1.641 finally; in the strength and muscles of the legs, the values ranged between 14.86 ±1.767 initially and 16.80 ±1.473; in the strength and muscles of the arms, the values recorded an increase from 14.40±0.985 initially to 16.26 ±0.961 finally. The present research demonstrated that the use of circuit workout can improve the motor qualities of strength and it can also improve the motor qualities of strength and resistance, which confirms the purpose of the paper.
Calibration of a CCD Camera and Correction of its Images

The abstract of the thesis of Armin Rest for the Master of Science in Physics presented August 23, 1996. Title: Calibration of a CCD camera and correction of its images Charge-Coupled-Device (CCD) cameras have opened a new world in astronomy and other related sciences with their high quantum efficiency, stability, linearity, and easy handling. Nevertheless, there is still noise in raw CCD images and even more noise is added through the image calibration process. This makes it essential to know exactly how the calibration process impacts the noise level in the image. The properties and characteristics of the calibration frames were explored. This was done for bias frames, dark frames and flat-field frames at different temperatures and for different exposure times. At first, it seemed advantageous to scale down a dark frame from a high temperature to the temperature at which the image is taken. However, the different pixel populations have different doubling temperatures. Although the main population could be scaled down accurately, the hot pixel populations could not. A global doubling temperature cannot be used to scale down dark frames taken at one temperature to calibrate the image taken at another temperature.
Acceleration of Target Detection Based on Forced Knowledge Distillation

In recent years, deep learning has achieved outstanding results on many problems such as computer vision, natural language processing and so on. The research of network model compression and acceleration can make the network model run efficiently on resource-constrained devices by greatly reducing the amount of computation of the network when the performance of the network decreases slightly. At present, knowledge distillation has achieved good results in classification tasks, but it shows strong limitations in the face of more complex tasks like detection. In this work, we propose a forced knowledge distillation framework, which focuses on improving the ability of feature extraction in detection. The whole model can be compact and fast without losing much accuracy. We use PASCAL VOC, KITTI and MSCOCO data sets to make a comprehensive evaluation. The results show that the forced knowledge distillation framework can fully learn the knowledge of teacher networks and achieve better detection results in smaller student networks.
The Knowledge And Skills Of Surgical Foundation Year One Doctors In A Teaching Hospital In The UK: A Review And Results Of A Survey

Introduction:Junior doctors had acquired knowledge and skills in the past using weekly specialty based teaching sessions and on the job learning.They currently learn on the job as before (with the restraints of less working hours). However, generic hospital wide teaching programmes have replaced the specialty teaching programmes. We aim to assess the effects of these changes on the surgical foundation year one doctors’ knowledge of common surgical conditions and on their basic surgical skills. Methods: We carried out a survey of foundation year one doctors towards the end of their first surgical placements in the largest teaching trust in Manchester. We surveyed the foundation year one doctors’ perception of their abilities to manage common surgical conditions and to carry out basic surgical procedures. Results: Response rate was 100% with 24 doctors participating in the survey (n=24). Only 9 out of 24 FY1s (38%) agreed that the generic teaching programme provided teaching which is relevant to their surgical placement. The FY1s’ perceived knowledge and ability to deal with common surgical conditions was 3/5. Doctors in GI surgery placements fared better on average (mean 3.20 vs. 2.78, p Conclusions: Foundation year one doctors needs specialty teaching as they rotate through their rotations apart from the generic teaching programme. It could be useful if all those who cover surgical on call shift to go through a GI placement to improve their skills and knowledge in common surgical conditions.
Phase II study of temozolomide (TMZ) in metastatic colorectal cancer (mCRC) patients molecularly selected by MGMT promoter hypermethylation.

583 Background: O(6)-methylguanine-DNA-methyltransferase (MGMT) is a DNA repair protein. About 40% of mCRC display MGMT deficiency due to promoter hypermethylation, leading to susceptibility to treatment with cytotoxic alkylating agents. We previously reported that objective clinical response to dacarbazine is confined to tumors harboring MGMT promoter hypermethylation (Amatu et al. Clin Cancer Res 2013). Based on these findings, we conducted a phase II study with TMZ in MGMT-deficient mCRCs after failure of standard therapies (EudraCT 2012-003338-17). Methods: We screened mCRC patients for MGMT promoter hypermethylation on archival FFPE specimens by methylation-specific PCR (MSP). All eligible patients underwent tumor biopsy prior to start of treatment. Patients received TMZ 200 mg/m2 po qd days 1-5 q28 until progression or intolerable toxicity. We used a Fleming single-stage design to determine whether PFS rate at 12 week would be ≥35% (H0≤15%, type I error=0.059 (1-sided) and power=0.849). Secondary en.
Simulating an induction motor multi-operating point speed control using PI controller with neural network

The Induction Motors (IM) speed widely influenced due to various motor loading conditions. When the load is applied the motor speed is reduced from the reference speed. This work presents a Matlab simulation of a Proportional Integral (PI) controller incorporating Neural Network for IM speed controls. The motor speed response profile under this control is improved and still constant at the point of load applied. Also, this controller stilled operates efficiently at a wide range of operating frequencies when compared with the traditional PI controller.