Miracle-dz/UniFAR-FTUs huggingface dataset:
First report of the molecular detection of Ancylostoma caninum in Lahore, Pakistan: the threat from pets

The molecular prevalence of Ancylostoma caninum was determined in stray and pet dogs in Lahore, Pakistan from July 2014 to August 2015. A total of 500 dog faecal samples were first evaluated using a sedimentation technique and further through a PCR assay targeting the ITS-2 region of the A. caninum genome. Overall, 130 (26%) samples were positive for hookworm infestation by microscopic examination. Only microscopically positive samples were processed for PCR and 89 (17.6%) were positive for A. caninum. Sequence analysis of amplicons showed 100% homology with A. caninum and the genotypes clustered in one clade with Brazilian A. caninum hookworms. There was a significantly (P < 0.05) increased prevalence in male dogs younger than six months old. Labrador retrievers had higher A. caninum incidence compared to German shepherds and other breeds. To the best of our knowledge, this is the first report of the molecular prevalence of A. caninum in dogs in Pakistan. The novel results of the present study allow us to conclude that A. caninum is more prevalent in pet dogs, especially puppies, and this can be a potential threat for humans that come into contact with such animals. Therefore, the routine monitoring of pets, especially the more susceptible breeds, is essential for disease control.
The Mitigating Effect of Bank Financing on Shareholder Value and Firm Policies Following Rating Downgrades

We document that shareholders of high-yield firms are less sensitive to credit rating downgrades the higher the proportion of bank financing in the firm. This positive effect is linked to firm behavior. In the year after the downgrade, high-yield firms with large bank debt ratios i) need to reduce their leverage less, and ii) display higher capital expenditures, compared to peers that rely relatively more on other sources of debt. Bank financing thus helps alleviate the adverse effects of rating downgrades on shareholders and firms in the high-yield segment. As such, one may view our findings as new evidence of the “specialness” and flexibility of bank debt.
Proxy Fairness

We consider the problem of improving fairness when one lacks access to a dataset labeled with protected groups, making it difficult to take advantage of strategies that can improve fairness but require protected group labels, either at training or runtime. To address this, we investigate improving fairness metrics for proxy groups, and test whether doing so results in improved fairness for the true sensitive groups. Results on benchmark and real-world datasets demonstrate that such a proxy fairness strategy can work well in practice. However, we caution that the effectiveness likely depends on the choice of fairness metric, as well as how aligned the proxy groups are with the true protected groups in terms of the constrained model parameters.
AI in Education needs interpretable machine learning: Lessons from Open Learner Modelling

Interpretability of the underlying AI representations is a key raison d'\^{e}tre for Open Learner Modelling (OLM) -- a branch of Intelligent Tutoring Systems (ITS) research. OLMs provide tools for 'opening' up the AI models of learners' cognition and emotions for the purpose of supporting human learning and teaching. Over thirty years of research in ITS (also known as AI in Education) produced important work, which informs about how AI can be used in Education to best effects and, through the OLM research, what are the necessary considerations to make it interpretable and explainable for the benefit of learning. We argue that this work can provide a valuable starting point for a framework of interpretable AI, and as such is of relevance to the application of both knowledge-based and machine learning systems in other high-stakes contexts, beyond education.
Robot-assisted renal surgery: current status and future directions

This paper examines the current role of robot-assisted renal surgery as complex and partial nephrectomies, including vena cava thrombus, combined nephroureterectomies, living donor nephrectomy, autotransplantation, and difficult anatomy as in patients with obesity or adhesions. Indications for robot-assisted renal surgery are comparable to those of conventional laparoscopic approaches. A reduction in the learning curve leads to a stabilization of the procedure and further increases the number of minimally invasive procedures performed. A Medline literature search for publications on the field of robotic kidney surgery has been performed using the MeSH terms: robotic surgical procedures and kidney. Future directions include progress in robotic technology and instrumentation with further miniaturization of robotic procedures as laparoendoscopic single-site interventions and progress in image-guided robotic surgery.
Detailed Visual Memory Capacity Is Present Early in Childhood

Previous studies have shown that adults are able to remember more than 1,000 images with great detail. However, little is known about the development of this visual capacity, nor its presence early in life. This study tests the level of detail of young children’s memory for a large number of items, adapting the method of Brady, Konkle, Alvarez, and Oliva (2008). Four- and six-year-old children were shown more than 100 images of everyday objects. They were then tested for recognition of familiar items in a binary decision task. The identity of the foil test item was manipulated in three conditions (Category, Exemplar, and State). Children demonstrated high accuracy across all conditions, remembering not only the basic-level category (Category), but also unique details (Exemplar), and information about position and arrangement of parts (State). These findings demonstrate that children spontaneously encode a high degree of visual detail. Early in life, visual memory exhibits high fidelity and extends over a large set of items.
The timing and interval of mate encounter affects investment during mating

The benefits obtained from mating are usually condition-dependent, favouring the evolution of flexible investment during copulation; for example, in terms of invested time, energy or sperm. Flexible investment strategies are predicted to depend on the likelihood of acquiring alternative mates and therefore they should depend on the timing of mate encounter. However, scarce experimental evidence for this hypothesis exists. In the present study, we manipulated the time delay until first mating and the interval between first and second mating in the polygynandrous common lizard Zootoca vivipara. We determined treatment effects on fertilization success and copulation duration, with the latter being a proxy for investment in mating and for the quantity of transferred sperm. The duration of the second copulation decreased with increasing inter-mating interval and depended on the fertilization success of first mates. The former provides evidence for time-dependent investment strategies, most likely resulting from the progression of the female's reproductive cycle. The fertilization success of first mates increased with increasing inter-mating interval and was higher when females were closer to ovulation, showing that flexible investment strategies significantly affected male reproductive success. This indicates fertilization assurance, which may mitigate the negative effects of low population density on reproductive success (e.g. Allee effects).
The Neuroprotective Effects of Long-Term Repetitive Transcranial Magnetic Stimulation on the Cortical Spreading Depression-induced Damages in Rat’s Brain

Introduction: Cortical Spreading Depression (CSD) is a propagating wave of neural and glial cell depolarization with important role in several clinical disorders. Repetitive Transcranial Magnetic Stimulation (rTMS) is a potential tool with preventive treatment effects in psychiatric and neuronal disorders. In this paper, we study the effects of rTMS on CSD by using behavioral and histological approaches in hippocampus and cortical regions. Methods: Twenty-four rats were divided into four groups. A group of control rats were kept in their home cage during the experiment. The CSD group received four CSD inductions during 4 weeks with 1 week intervals. The CSD-rTMS group were treated with rTMS stimulation (figure-eight coils, 20 Hz, 10 min/d) for 4 weeks. The fourth group, i.e. rTMS group received rTMS stimulation similar to the CSD-rTMS group without CSD induction. Results: Long-term rTMS application in treated groups significantly reduced production of dark neurons, increased the mean volume of normal neurons, and decreased the number of apoptotic neurons in cortical regions compared to the control group. The protective effects of long-term treatment by rTMS in the hippocampal regions were also studied. It was effective in some regions; however, rTMS effects on hippocampal regions were lower than cortical ones. Conclusion: Based on the study results, rTMS has significant preventive and protective effects in CSD-induced damages in cortical and hippocampal regions of the rat’s brain.
Climatology and atmospheric chemistry of the non-methane hydrocarbons ethane and propane over the North Atlantic

A record spanning ten years of non-methane hydrocarbon (NMHC) data from the Pico Mountain Observatory (PMO), Pico Island, Azores, Portugal, was analyzed for seasonal NMHC behavior, atmospheric processing, and trends, focusing on ethane and propane. The location of this site in the central North Atlantic, at an elevation of 2225 m asl, allows these data to be used to investigate the background conditions and pollution transport events occurring in the lower free North Atlantic troposphere. The quantity ln([propane]/[ethane]) was used as an indicator of both photochemical processing and a marker for the occurrence of pollution transport events detected at the station. The Pico data were compared with three other continuous NMHC data sets from sites bordering the North Atlantic, i.e. the Global Atmospheric Watch (GAW) stations at Summit, Greenland, Hohenpeisssenberg, Germany, and Cape Verde, using ln([propane]/[ethane]) results as an indicator for the degree of photochemical processing (‘aging’) seen in the data. Comparisons of these three data sets showed some significant differences in the seasonal background and range of observed values. The statistical distribution of binned monthly data was determined, and individual sample events were then scaled to the monthly median observed value. Back trajectories, determined by the HYSPLIT model were used to investigate the geographic origin of the observed trace gases as a function of the degree of photochemical processing. Results show that PMO samples have been subjected to a diversity of air transport and aging, from highly processed air to freshly emitted air throughout the year, and in particular during summer months. The predominant air transport is from North America, with only occasional influence from continental areas located east and southeast (Europe and Africa). The available record was found to be too variable and still too short to allow deciphering NMHC trends from the data. Ethane and propane measurements at the PMO were compared with the MOZART-4 atmospheric chemistry and transport model at the appropriate time and location. The model was found to yield good agreement in the description of the lower range of atmospheric mole fractions observed, of the seasonal cycle, and the regional oxidation chemistry. However, ethane and propane enhancements in transport events were underestimated, indicating that after the ≥ 3 days of synoptic transport to PMO the spatial extent of plumes frequently is smaller than the 2.8° × 2.8° (∼300 km) model grid resolution.
Transfer Function of Macro-Micro Manipulation on a PDMS Microfluidic Chip

To achieve fast and accurate cell manipulation in a microfluidic channel, it is essential to know the true nature of its input-output relationship. This paper aims to reveal the transfer function of such a micro manipulation controlled by a macro actuator. Both a theoretical model and experimental results for the manipulation are presented. A second-order transfer function is derived based on the proposed model, where the polydimethylsiloxane (PDMS) deformation plays an important role in the manipulation. Experiments are conducted with input frequencies up to 300 Hz. An interesting observation from the experimental results is that the frequency responses of the transfer function behave just like a first-order integration operator in the system. The role of PDMS deformation for the transfer function is discussed based on the experimentally-determined parameters and the proposed model.
Sensor-Based Continuous Authentication Using Cost-Effective Kernel Ridge Regression

People prefer to store important, private, and sensitive information on smartphones for convenient storage and fast access, such as photos and emails. To prevent information leakage and smartphone illegal access, we propose a novel sensor-based continuous authentication system, SensorCA, for continuously monitoring users’ behavior patterns, by leveraging the accelerometer, gyroscope, and magnetometer ubiquitously built-in smartphones. We are among the first to exploit the data augmentation approach of the rotation, which creates additional data by applying it on the collected raw data and improves the robustness of the proposed system. With the augmented data, SensorCA extracts sensor-based features in both time and frequency domains within a time window, then utilizes the kernel ridge regression with truncated Gaussian radial basis function kernel (KRR-TRBF) to train the classifier, and finally authenticates the current user as a legitimate user or an impostor. We evaluate the authentication performance of SensorCA in terms of different classifiers including KRR-TRBF, KRR-POLY, and SVM-RBF, and the data augmentation approach rotation on KRR-TRBF6 and SVM-RBF. The experimental results show that under the KRR-TRBF6 classifier, SensorCA reaches the lowest median equal error rate of 3.0% with dataset size 8000 and consumes the shortest training time of 0.054 seconds with dataset size 1000.
Phomopsis longanae Chi-Induced Disease Development and Pericarp Browning of Harvested Longan Fruit in Association With Energy Metabolism

Longan fruit is a popular subtropical fruit with a relatively short shelf life at room temperature mainly due to pericarp browning and fungal infection. This study aimed to investigate the infection of Phomopsis longanae Chi in longan fruit and its effects on the storability and shelf life of longan fruit. The relationship between the energy metabolism of harvested longan fruit and disease development and pericarp browning was elucidated. Results show that P. longanae-inoculation accelerated the deterioration of longan fruit and caused pericarp browning. It also led to the energy deficit in pericarp of longan fruit, which was reflected as lower contents of ATP and ADP, higher AMP content, and lower energy charge as compared to the control samples. Additionally, P. longanae-infection reduced the activities of H+-ATPase, Ca2+-ATPase, and Mg2+-ATPase in plasma, vacuolar, and mitochondrial membranes during the storage period. The results demonstrate that P. longanae-infection led to disease development and pericarp browning in harvested longan fruit, which were due to the infection-induced energy deficit and low ATPase activity that caused disorders of ion transport and distribution, and damaged the structure and function of vacuole, mitochondria, and eventually the whole cells of fruit tissues.
Analysis of correlations between indicators influencing successful deployment of ePortfolios

This paper brings the selected results of the research focused on measuring the success of an ePortfolio system deployment at the individual level. Further, it explores the structural model based on the DeLone & McLean's IS success model by investigating the relationships between the Use, User Satisfaction and Net Benefits as the main constructs of the model. The analysis involved 186 students from 10 different institutions worldwide. The descriptive statistics is used to identify and explain the correlations between main constructs, as well as to explain the correlations between indicators that are direct benefits of using ePortfolios. The results confirmed the previous research implications and found the modest correlation between the Use and Net Benefits, as well as a moderate correlation between the User Satisfaction and Net Benefits.
Adaptability of Closed Loop During Labor, Delivery, and Postpartum: A Secondary Analysis of Data from Two Randomized Crossover Trials in Type 1 Diabetes Pregnancy

Abstract Tight glucose control during labor and delivery is recommended for pregnant women with type 1 diabetes. This can be challenging to achieve using the current treatment modalities. The automated nature of closed loop and its ability to adapt to real-time glucose levels make it well suited for use during labor, delivery, and the immediate postpartum period. We report observational data of participants from two randomized crossover trials who chose to continue using closed loop during labor, delivery, and postpartum. Labor was defined as the 24 h before delivery and postpartum as the 48 h after delivery. The glucose target range during pregnancy was 3.5–7.8 mmol/L (63–140 mg/dL) and 3.9–10 mmol/L (70–180 mg/dL) after delivery. Twenty-seven (84.4%) of the potential 32 trial participants used closed loop through labor, delivery, and postpartum. Use of closed loop was associated with 82.0% (interquartile range [IQR] 49.3, 93.0) time-in-target range during labor and delivery and a mean glucose of 6.9 ± 1.4 mmol/L (124 ± 25 mg/dL). Closed loop performed well throughout vaginal, elective, and emergency cesarean section deliveries. Postpartum, women spent 83.3% (IQR 75.2, 94.6) time-in-target range (3.9–10.0 mmol/L [70–180 mg/dL]), with a mean glucose of 7.2 ± 1.4 mmol/L (130 ± 25 mg/dL). There was no difference in maternal glucose concentration between mothers of infants with and without neonatal hypoglycemia (6.9 ± 1.6 mmol/L and 6.8 ± 1.1 mmol/L [124 ± 29 mg/dL and 122 ± 20 mg/dL] respectively; P = 0.84). Automated closed-loop insulin delivery is feasible during hospital admissions for labor, delivery, and postpartum. Larger scale studies are needed to evaluate its efficacy compared with current clinical approaches as well as understand how women and healthcare providers will adopt this technology.
Unrestricted Bridging Resolution

In contrast to identity anaphors, which indicate coreference between a noun phrase and its antecedent, bridging anaphors link to their antecedent(s) via lexico-semantic, frame, or encyclopedic relations. Bridging resolution involves recognizing bridging anaphors and finding links to antecedents. In contrast to most prior work, we tackle both problems. Our work also follows a more wide-ranging definition of bridging than most previous work and does not impose any restrictions on the type of bridging anaphora or relations between anaphor and antecedent. We create a corpus (ISNotes) annotated for information status (IS), bridging being one of the IS subcategories. The annotations reach high reliability for all categories and marginal reliability for the bridging subcategory. We use a two-stage statistical global inference method for bridging resolution. Given all mentions in a document, the first stage, bridging anaphora recognition, recognizes bridging anaphors as a subtask of learning fine-grained IS. We use a cascading collective classification method where (i) collective classification allows us to investigate relations among several mentions and autocorrelation among IS classes and (ii) cascaded classification allows us to tackle class imbalance, important for minority classes such as bridging. We show that our method outperforms current methods both for IS recognition overall as well as for bridging, specifically. The second stage, bridging antecedent selection, finds the antecedents for all predicted bridging anaphors. We investigate the phenomenon of semantically or syntactically related bridging anaphors that share the same antecedent, a phenomenon we call sibling anaphors. We show that taking sibling anaphors into account in a joint inference model improves antecedent selection performance. In addition, we develop semantic and salience features for antecedent selection and suggest a novel method to build the candidate antecedent list for an anaphor, using the discourse scope of the anaphor. Our model outperforms previous work significantly.
Adaptive Maximum Power Point Finding Using Direct VOC/2 Tracking Method With Microwatt Power Consumption for Energy Harvesting

Maximum power transfer occurs in many energy harvesters at their half open-circuit voltage (<inline-formula> <tex-math notation="LaTeX">$V_{{\rm{OC}}}/ 2$</tex-math></inline-formula>). A novel implementation method of maximum power point finding based on the <inline-formula><tex-math notation="LaTeX">$V_{{\rm{OC}}}/ 2$</tex-math> </inline-formula> method is presented by exploiting the capacitor charging voltage across a smoothing capacitor connected in parallel with the energy harvester. The presented technique has a specifically designed high-pass filter, which has a peak output voltage that corresponds to the <inline-formula><tex-math notation="LaTeX">$V_{{\rm{OC}}}/ 2$ </tex-math></inline-formula> of the energy harvester. The control circuit filters and differentiates the voltage across the smoothing capacitor to directly determine the timing of reaching the <inline-formula><tex-math notation="LaTeX"> $V_{{\rm{OC}}}/ 2$</tex-math></inline-formula> of the energy harvester without having to find the <inline-formula> <tex-math notation="LaTeX">$V_{{\rm{OC}}}$</tex-math></inline-formula> first and is fully implemented using discrete analog components without the need of a programmable controller, leading to low power consumption of the method. In this paper, the control circuit is used in conjunction with a full-wave diode bridge rectifier and a dc–dc converter to harvest energy from a piezoelectric energy harvester (PEH) as the studied case. The PEH was subjected to various strain levels at low frequencies from 2 to 10 Hz. Experimental results show that the implemented circuit is adaptive to various vibration amplitudes and frequencies and has a maximum power point finding efficiency of up to 98.28% with power consumption as low as 5.16 μW.
Effects of High Glucose on the Expression of LAMA1 and Biological Behavior of Choroid Retinal Endothelial Cells

Hyperglycemia is one of the main causes of proliferative diabetic retinopathy (PDR) characterized by thickening of the vascular basement membrane. Laminin alpha 1 (LAMA1) is a primary component of laminin, a major protein constituent of the basement membrane. In this study, we investigated the role of LAMA1 in the development of PDR. Retinal choroidal vascular endothelial cells (RF/6A line) were exposed to glucose at different concentrations (5 mM, 15 mM, 25 mM, and 35 mM) and analyzed for cell growth, migration, proliferation, and adhesion. LAMA1 expression was examined 24 and 48 h following glucose treatment using Western blotting, RT-PCR, and immunofluorescence. The results showed that the proliferation, migration, and adhesion of RF/6A cells were increased by high glucose, whereas LAMA1 expression was slightly higher at 15 mM but decreased at 25 mM and 35 mM glucose compared to control. Thus, the changes in the biological behavior of high glucose-exposed retinal vascular endothelial cells correspond to variations in LAMA1 expression, indicating a possibility for LAMA1 involvement in PDR development. Our findings suggest that LAMA1 may play a role in PDR and, thus, may serve as a potential target for DR diagnosis and/or treatment.