Miracle-dz/UniFAR-FTUs huggingface dataset:
Primary Peritonitis: An Index Case of Mycoplasma hominis Infection in a Healthy Female

Introduction Primary peritonitis in healthy immunocompetent individuals is rare. Several case reports of Streptococcus species causing peritonitis have been described. Here, we present the first case of Mycoplasma hominis as the cause of primary peritonitis in a healthy woman. Case Report A 42-year-old female with history of uterine fibroids was admitted with abdominal pain and intraperitoneal fluid of unknown etiology. She was initially managed nonoperatively and empirically treated with broad spectrum antibiotics. Blood and urine cultures were unrevealing. Increasing abdominal pain and peritoneal fluid prompted diagnostic laparoscopy which revealed a dense fibrinous exudate covering the entire peritoneal cavity. Peritoneal fluid and biopsies were sent for cytology and culture. The peritoneal fluid was eventually sent for 16 s ribosomal analysis, which discovered Mycoplasma hominis RNA. Her antibiotics were narrowed, and she eventually made a full recovery. Discussion M. hominis is a rare source of systemic infection but has been known to colonize the urogenital tract and cause localized infections. This is the first presentation of M. hominis causing primary peritonitis in a healthy immunocompetent female. Multidisciplinary management of these patients is critical to achieve a timely diagnosis. Surgical exploration is often unavoidable to rule out secondary peritonitis.
Topology Mismatch Avoidable Cross-Layer Protocol for P2P File Discovery in MANETs

To resolve the topology mismatch problem when applying Peer-to-Peer (P2P) file sharing over Mobile Ad hoc networks (MANETs), a cross-layer protocol is proposed by combining P2P file discovery with the route discovery process at the network layer. In this protocol, the functionality of conventional routing protocols is extended to identify the file discovery request, and P2P connections are established on demand to avoid duplicated broadcast at both P2P and network layers. Simulation results show that the proposed protocol can significantly decrease the control overhead during file discovery process, and provide less lookup response delay than that of the off-the-shelf approaches.
Studies on Fabrication and Reliability of GaN High-Resistivity-Cap-Layer HEMT

In this paper, we systematically investigate the effect of hydrogen plasma treatment radio frequency (RF) power, treatment time, and rapid thermal annealing (RTA) on the performance of high-resistivity-cap-layer high-electron-mobility-transistor (HRCL-HEMT). It is found that high RF power contributes to obtain high drain current, but induces more damage. An appropriate RTA process not only can repair the plasma damage but also improves the static characteristics of HRCL-HEMT. Subsequently, a large hydrogen plasma treatment time window of 4 min is demonstrated with an optimized RF power of 2 W and RTA at 350 °C for 5 min. Furthermore, the thermal stability of the optimized HRCL-HEMT is investigated by high temperature test and long-term thermal stress test. No obvious degradation of <inline-formula> <tex-math notation="LaTeX">${V}_{\text {TH}}$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">${I}_{G}$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">${R}_{\text {SH}}$ </tex-math></inline-formula>, and dynamic <inline-formula> <tex-math notation="LaTeX">${R}_{ \mathrm{\scriptscriptstyle ON}}$ </tex-math></inline-formula> is observed in both before and after passivation devices after 1000-h thermal stress. Finally, gate reliability of the HRCL-HEMT is also analyzed by time-to-failure test. The maximum gate voltage is determined to be 6.28 V for a ten-year lifetime with a failure rate of 1% at 25 °C.
Non-Invasive Detection of Moving and Stationary Human With WiFi

Non-invasive human sensing based on radio signals has attracted a great deal of research interest and fostered a broad range of innovative applications of localization, gesture recognition, smart health-care, etc., for which a primary primitive is to detect human presence. Previous works have studied the detection of moving humans via signal variations caused by human movements. For stationary people, however, existing approaches often employ a prerequisite scenario-tailored calibration of channel profile in human-free environments. Based on in-depth understanding of human motion induced signal attenuation reflected by PHY layer channel state information (CSI), we propose DeMan, a unified scheme for non-invasive detection of moving and stationary human on commodity WiFi devices. DeMan takes advantage of both amplitude and phase information of CSI to detect moving targets. In addition, DeMan considers human breathing as an intrinsic indicator of stationary human presence and adopts sophisticated mechanisms to detect particular signal patterns caused by minute chest motions, which could be destroyed by significant whole-body motion or hidden by environmental noises. By doing this, DeMan is capable of simultaneously detecting moving and stationary people with only a small number of prior measurements for model parameter determination, yet without the cumbersome scenario-specific calibration. Extensive experimental evaluation in typical indoor environments validates the great performance of DeMan in various human poses and locations and diverse channel conditions. Particularly, DeMan provides a detection rate of around 95% for both moving and stationary people, while identifies human-free scenarios by 96%, all of which outperforms existing methods by about 30%.
Adaptive Human–Robot Interaction Control for Robots Driven by Series Elastic Actuators

Series elastic actuators (SEAs) are known to offer a range of advantages over stiff actuators for human–robot interaction, such as high force/torque fidelity, low impedance, and tolerance to shocks. While a variety of SEAs have been developed and implemented in initiatives that involve physical interactions with humans, relatively few control schemes were proposed to deal with the dynamic stability and uncertainties of robotic systems driven by SEAs, and the open issue of safety that resolves the conflicts of motion between the human and the robot has not been systematically addressed. In this paper, a novel continuous adaptive control method is proposed for SEA-driven robots used in human–robot interaction. The proposed method provides a unified formulation for both the robot-in-charge mode, where the robot plays a dominant role to follow a desired trajectory, and the human-in-charge mode, in which the human plays a dominant role to guide the movement of robot. Instead of designing multiple controllers and switching between them, both typical modes are integrated into a single controller, and the transition between two modes is smooth and stable. Therefore, the proposed controller is able to detect the human motion intention and guarantee the safe human–robot interaction. The dynamic stability of the closed-loop system is theoretically proven by using the Lyapunov method, with the consideration of uncertainties in both the robot dynamics and the actuator dynamics. Both simulation and experimental results are presented to illustrate the performance of the proposed controller.
Understanding Wealth in New York City From the Activity of Local Businesses

In this work, we aim to understand the relationships between local businesses and the demographics of communities that surround them within New York City. Understanding demographics in relation to business activity is important for applications both in business and social sciences. In our approach, we aim to predict demographics using social-media check-in data. We construct a novel dataset that combines FourSqaure check-in data [1] with census data from the 2015 American Community Survey [2]. Afterwards, we manually construct features based on the various check-in categories and timestamps. We test a number of models on these features and we achieve 41.03% accuracy on an income classification task using Gradient Boosting Trees, compared to 25% accuracy from random guessing.
Design of Miniaturized and Ultrathin Absorptive/Transmissive Radome Based on Interdigital Square Loops

This paper designs a miniaturized and ultrathin absorptive/transmissive radome based on interdigital square loops. The thickness of designed radome is only 4.5 mm. The period of the radome is 10 mm, which is λ/17.5 (λ corresponding to the wavelength of center frequency of passband). In order to verify the transmission and reflection properties, a prototype is fabricated. Its effectiveness is verified by both synthetic experiments and measurements in the anechoic chamber. Furthermore, the oblique incidents are also evaluated for both the transmission coefficients and reflection coefficients.
Comparisons of the Orbiting Carbon Observatory-2 (OCO-2) X CO 2 measurements with TCCON

NASA's Orbiting Carbon Observatory-2 (OCO-2) has been measuring carbon dioxide column-averaged dry-air mole fraction, X_(CO_2), in the Earth's atmosphere for over 2 years. In this paper, we describe the comparisons between the first major release of the OCO-2 retrieval algorithm (B7r) and X_(CO2) from OCO-2's primary ground-based validation network: the Total Carbon Column Observing Network (TCCON). The OCO-2 X_(CO_2) retrievals, after filtering and bias correction, agree well when aggregated around and coincident with TCCON data in nadir, glint, and target observation modes, with absolute median differences less than 0.4 ppm and RMS differences less than 1.5 ppm. After bias correction, residual biases remain. These biases appear to depend on latitude, surface properties, and scattering by aerosols. It is thus crucial to continue measurement comparisons with TCCON to monitor and evaluate the OCO-2 X_(CO_2) data quality throughout its mission.
Perceptual Load and Color Singletons 1 Running head : PERCEPTUAL LOAD AND COLOR SINGLETONS Does Low Perceptual Load Enable Capture by Color Singletons ?

There is considerable debate as to whether color singletons can capture attention in a stimulus-driven manner. In this study, we explore one potential capture enabling condition – low perceptual load. To test this hypothesis, we manipulated perceptual load in a flanker task in which flanking letters sometimes were color singletons. If low load enhances capture by color singletons, then color singletons should produce an especially large increase in overall reaction times and in flanker-target compatibility effects. Neither of these predictions was confirmed in any of the four experiments reported here, although we did replicate the classic load effects from previous studies. These experiments indicate that although perceptual load does strongly modulate overall performance, it does not facilitate capture by color singletons. This finding contrasts sharply with findings from other types of salient stimuli (abrupt onsets and moving objects). Implications for theories of attentional capture will be discussed.
The properties of artificial dielectrics at centimetre wavelengths

The properties of an artificial dielectric at centimetre wavelengths are compared with those of a solid material, and the possible definitions of the refractive index and the wave impedance are examined. It is concluded that the most appropriate definition of the latter is in terms of the reflection coefficient at an interface between the artificial dielectric and free space. The reactive fields which are set up near such an interface are discussed qualitatively, and a number of ways in which they may be represented are given. The paper concludes with suggestions for further applications of artificial dielectrics.
Quaternion adaptive line enhancer

The recovery of periodic signals from their noisy single channel mixtures has made wide use of the adaptive line enhancer (ALE). The ALE, however, is not designed for detection of two-(2-D) or three-dimensional (3-D) periodic signals such as tremor in an unconstrained hand motion. An ALE which can perform restoration of 3-D periodic signals is therefore required for such purposes. These signals may not exhibit periodicity in a single dimension. To address and solve this problem a quaternion adaptive line enhancer (QALE) is introduced in this paper for the first time which exploits the quaternion least mean square (QLMS) algorithm for the detection of 3-D (extendable to 4-D) periodic signals.
Supervised machine learning in intelligent character recognition of handwritten and printed nameplate

We are in the midst of a revolution, digital revolution which is primarily responsible for the advancements in various computing fields. There is a greater need for smart devices, devices that do not just compute faster but also ‘smarter’. As soon as we encounter the word ‘smart’, we think of intelligence. Intelligence has certainly shaped our modern life in the last decade. One such form of intelligence is seen in character recognition devices. Normal optical character recognition methods seem to be working fine upto a good extent, but challenges arise when the input set starts becoming dynamic. In that case, these techniques fall short when the text is handwritten or sometimes when the there is a variation in styles, fonts, etc. In addition, there is a crucial need to produce accurate results irrespective of what the given dataset is. Supervised machine learning when applied here works by learning attributes and classifying labels (target names). This method has consistently shown accurate results in the past as it helps in training the machine well. This is the driving force behind our selection of this specific algorithm. Even when the dataset becomes extensively large due to multiple language scripts, this method works fine. In this paper, we propose a method for intelligent character recognition using classifiers and transferring the data to excel sheet. The results show such methods can produce accuracies close to 95% for alpha numerals and special characters.
A live vaccine to Staphylococcus aureus infection

In this issue Moscoso et al [1] present exciting data utilizing a D-alanine mutant of Staphylococcus aureus as a live vaccine against lethal infection. Given the absence of a currently approved vaccine and antibiotic resistance within the S. aureus population it provides new hope in the prevention of this common human pathogen.
AN 11‐Year‐Old Boy with a Leptomeningeal Tumor

An 11-year-old male patient was addressed to our institution with headache, vomiting and right VI cranial nerve paralysis. Clinical examination did not reveal any other neurological deficits. During skin examination, multiple congenital melanocytic nevi were observed (Figure 1A). MRI scans showed a leptomeningeal lesion extending from T5 to T11 (Figure 1B). This lesion was hypersignal on T1 sequence enhanced with gadolinium injection and hypointense signal on T2 sequence. At the supratentorial level a dilatation of the lateral and the third ventricle with a wide posterior fossa were found, without tumoral lesion (Figure 1C). MICROSCOPIC FINDINGS
Casein kinase 1‐epsilon deletion increases mu opioid receptor‐dependent behaviors and binge eating 1

Genetic and pharmacological studies indicate that casein kinase 1 epsilon (Csnk1e) contributes to psychostimulant, opioid, and ethanol motivated behaviors. We previously used pharmacological inhibition to demonstrate that Csnk1e negatively regulates the locomotor stimulant properties of opioids and psychostimulants. Here, we tested the hypothesis that Csnk1e negatively regulates opioid and psychostimulant reward using genetic inhibition and the conditioned place preference assay in Csnk1e knockout mice. Similar to pharmacological inhibition, Csnk1e knockout mice showed enhanced opioid‐induced locomotor activity with the mu opioid receptor agonist fentanyl (0.2 mg/kg i.p.) as well as enhanced sensitivity to low‐dose fentanyl reward (0.05 mg/kg). Interestingly, female knockout mice also showed a markedly greater escalation in consumption of sweetened palatable food – a behavioral pattern consistent with binge eating that also depends on mu opioid receptor activation. No difference was observed in fentanyl analgesia in the 52.5°C hot plate assay (0–0.4 mg/kg), naloxone conditioned place aversion (4 mg/kg), or methamphetamine conditioned place preference (0–4 mg/kg). To identify molecular adaptations associated with increased drug and food behaviors in knockout mice, we completed transcriptome analysis via mRNA sequencing of the striatum. Enrichment analysis identified terms associated with myelination and axon guidance and pathway analysis identified a differentially expressed gene set predicted to be regulated by the Wnt signaling transcription factor, Tcf7l2. To summarize, Csnk1e deletion increased mu opioid receptor‐dependent behaviors, supporting previous studies indicating an endogenous negative regulatory role of Csnk1e in opioid behavior.
Reactors: A Case for Predictable, Virtualized Actor Database Systems

The requirements for OLTP database systems are becoming ever more demanding. Domains such as finance and computer games increasingly mandate that developers be able to encode complex application logic and control transaction latencies in in-memory databases. At the same time, infrastructure engineers in these domains need to experiment with and deploy OLTP database architectures that ensure application scalability and maximize resource utilization in modern machines. In this paper, we propose a relational actor programming model for in-memory databases as a novel, holistic approach towards fulfilling these challenging requirements. Conceptually, relational actors, or reactors for short, are application-defined, isolated logical actors that encapsulate relations and process function calls asynchronously. Reactors ease reasoning about correctness by guaranteeing serializability of application-level function calls. In contrast to classic transactional models, however, reactors allow developers to take advantage of intra-transaction parallelism and state encapsulation in their applications to reduce latency and improve locality. Moreover, reactors enable a new degree of flexibility in database deployment. We present ReactDB, a system design exposing reactors that allows for flexible virtualization of database architecture between the extremes of shared-nothing and shared-everything without changes to application code. Our experiments illustrate latency control, low overhead, and asynchronicity trade-offs with ReactDB in OLTP benchmarks.
Improvement properties of nylon fabric by corona pre-treatment and nano coating

This article tries to represent a supplemental method based on surface modification in order to optimizing the per cent of nano cohesion to give the better performances, such as antibacterial resistance and UV-blocking characteristic (especially in nano-ZnO), which nanoparticles carry inherently. Corona treatment was used to modify the surface of Nylon 6 fabrics in Sixdifferent conditions (related to power and passages). Treated fabrics were dyed with acidic dye and imbued with nano-ZnO simultaneously and antibacterial property, dye absorption and UV-blocking characteristic of samples were investigated. Scanning electron microscopy (SEM) was used to observe a porous Nylon fibre consisting of nano-ZnO. By increasing the power and number of passages of the corona atmosphere in which samples were contacted with, the water absorption increased. The result demonstrated that by increasing power and passages of corona treatment, dye absorption decrease likely due to the increase of the nano-ZnO cohesion. UV blocking increased in relation with increasing power and passages of corona treating. Results from antibacterial property on samples showed that by increasing the power and passages of corona treatment, the fabrics became more resistance to Staphylococcus aureus and Escherichia coli bacteria.
A Fluid Category Structure for Metaphor Processing

Metaphor and analogy are processes that creatively play with our conventional conceptions of what constitutes a category structure. Knowledge of conventional category boundaries can be found in ontologies of varying richness and coverage, from WordNet to Cyc. But what each of these ontologies have in common is a rather static, topdown view of category structure. In this paper we outline a dynamic, bottom-up view of category membership based on contextsensitive corpus analysis. By learning from corpora about how people creatively use categories, we believe that our computational systems can learn for themselves how to replicate this category-level creativity.
Antioxidant Treatment Induces Hyperactivation of the HPA Axis by Upregulating ACTH Receptor in the Adrenal and Downregulating Glucocorticoid Receptors in the Pituitary

Glucocorticoid (GC) production is physiologically regulated through a negative feedback loop mediated by the GC, which appear disrupted in several pathological conditions. The inability to perform negative feedback of the hypothalamus-pituitary-adrenal (HPA) axis in several diseases is associated with an overproduction of reactive oxygen species (ROS); however, nothing is known about the effects of ROS on the functionality of the HPA axis during homeostasis. This study analyzed the putative impact of antioxidants on the HPA axis activity and GC-mediated negative feedback upon the HPA cascade. Male Wistar rats were orally treated with N-acetylcysteine (NAC) or vitamin E for 18 consecutive days. NAC-treated rats were then subjected to a daily treatment with dexamethasone, which covered the last 5 days of the antioxidant therapy. We found that NAC and vitamin E induced an increase in plasma corticosterone levels. NAC intensified MC2R and StAR expressions in the adrenal and reduced GR and MR expressions in the pituitary. NAC also prevented the dexamethasone-induced reduction in plasma corticosterone levels. Furthermore, NAC decreased HO-1 and Nrf2 expression in the pituitary. These findings show that antioxidants induce hyperactivity of the HPA axis via upregulation of MC2R expression in the adrenal and downregulation of GR and MR in the pituitary.
Does self-brand personality fit affect brand attitudes towards cars and attitudes towards an electric car extension?

In representative Belgian samples, the influence of self-brand personality fit on car brand evaluation, electric car line extension evaluation and parent brand feedback effects is investigated. Evaluations of desired self-brand personality fit appear to be more relevant for brand evaluations than the mere difference between a brand’s personality and the personality of the consumer. For extensions and parent brand evaluations after extensions, self-brand personality fit also plays a significant role. Moreover, the relative importance of personality dimensions that drive extension judgment and parent brand feedback is different from those of brand evaluation in general. Regardless of the brand, desirable car personality characteristics drive extension and parent brand feedback evaluations.
A low-complexity equalizer for massive MIMO systems based on array separability

In this paper, we propose a low-complexity equalizer for multiple-input multiple-output systems with large receive antenna arrays. The computational complexity reduction is achieved by exploiting array separability on a geometric channel model. This property suggests a two-stage receive processing, consisting of (i) sub-array beamforming and (ii) low-dimension minimum mean square error (MMSE) equalization. Simulations indicate that the proposed method outperforms the classical MMSE filter in terms of complexity provided that the number of channel scatterers and the sub-arrays dimensions are not excessively large.