Miracle-dz/UniFAR-FTUs huggingface dataset:
Detection, occurrence, and removal of selected pharmaceuticals in Missouri source and finished drinking waters

Abstract A simple, sensitive, and selective solid phase extraction – ultra-fast liquid chromatography – tandem mass spectrometry (SPE-UFLC-MS/MS) method was developed and applied for the analysis of selected important pharmaceutical compounds in source and finished drinking waters. The method detected the following six pharmaceuticals, cotinine, cephapirin, ciprofloxacin, enrofloxacein, azithromycin, and diphenhydramine, at sub-μg/L level in multiple water matrices after pre-concentration by SPE. Cotinine-d3 and 13C315 N-Ciprofloxacin were used as internal standards for accurate quantitation. This method was validated through spike recoveries (67–129%), reproducibility (RSD: 2.3–15.7%), and method detection limits (MDLs: 2–5 ng/L). The method was used to test for occurrence of these pharmaceuticals in source and drinking waters from 13 Missouri water treatment facilities in four different seasons. In general, higher detection frequency and concentrations of pharmaceuticals were observed in colder months due presumably to less dilution (at lower flows) and slower degradation. The PPCP removals by different activated carbons were also evaluated. The occurrence and removal results in this study provide valuable information to help water treatment facilities taking appropriate strategies for better control of trace pharmaceuticals in drinking water.
A stacked split word-line (SSW) cell for low-voltage operation, large capacity, high speed SRAMs

Stacked Split Word-Line cell technology suitable for low voltage operation, large capacity and high speed SRAMs has been proposed. Two pull-down transistors and two access transistors are fabricated employing two separate gate formations. A pair of split word-lines is stacked over pull-down transistors. That permits large cell ratio in small cell area and independent optimization of pull-down and access transistors. Threshold voltage of access transistors is lowered to improve cell stability. Top gate thin film polysilicon transistor and Vcc plate are used to make cell node capacitor and improve soft error immunity. This technology is applied to a fast 16M bit SRAM and enabled a 7.16 /spl mu/m/sup 2/ cell area in relaxed 0.4 /spl mu/m layout rule utilizing conventional i-line stepper without phase-shift masks. <<ETX>>
Towards Provisioning Vehicle-Based Information Services

Smart vehicles are considered key enablers for intelligent transport systems. They are equipped with components to enable services for vehicle occupants, other vehicles on roads, and third parties. In-vehicle sensors, diversified communication modules, and an on-board unit with high computing and storage capabilities enable the smart vehicle to work as a mobile resource of diverse scopes of services. With the high benefits the public sensing paradigm brought to the application domain, there is interest nowadays to widen the scope of applications by engaging more resources in the sensing loop. Although smartphones have been the main players in this domain, their use suffers from limitations due to the scarcity of their on-board resources and their unpredictable mobility patterns. Concurrently, the plethora of on-board resources in smart vehicles along with their ubiquitous mobility are pushing towards utilizing them for providing remarkable public sensing services. In this thesis, we unveil the different resources a smart vehicle can provide on roads or at parking lots highlighting diversified information services that can come into action through utilizing such resources. Motivated by the high rise of the public sensing paradigm, we propose a vehicular public sensing platform that aims at exploiting the sensing, storage, processing and relaying resources of smart vehicles for provisioning ubiquitous, sensing-based information services. As parts of the proposed
Colliding with the Real World: Heresies and Unexplored Questions about Audience, Economics, and Control of Digital Libraries

This chapter contains sections titled: Introduction, A Few Disturbing Observations from Early Digital Library Experience, A Framework for Analysis: Control and Governance, Economics and Sustainability, and Audience, Commercially Based Digital Libraries, Library-Based Digital Libraries in the Academic Setting, Prospects and Barriers in User-Centered Design of Academic Digital Libraries, Postscript: The Focus on the User and The Ultimate Heresy, Acknowledgments
Sliding mode disturbance observer-based adaptive integral backstepping control of a piezoelectric nano-manipulator

This paper investigates a systematic modeling and control methodology for a multi-axis PZT (piezoelectric transducer) actuated servo stage supporting nano-manipulations. A sliding mode disturbance observer-based adaptive integral backstepping control method with an estimated inverse model compensation scheme is proposed to achieve ultra high precision tracking in the presence of the hysteresis nonlinearities, model uncertainties, and external disturbances. By introducing a time rate of the input signal, an enhanced rate-dependent Prandtl–Ishlinskii model is developed to describe the hysteresis behaviors, and its inverse is also constructed to mitigate their adverse effects. In particular, the corresponding inverse compensation error is analyzed and its boundedness is proven. Subsequently, the sliding mode disturbance observer-based adaptive integral backstepping controller is designed to guarantee the convergence of the tracking error, where the sliding mode disturbance observer can track the total disturbances in a finite time, while the integral action is incorporated into the adaptive backstepping design to improve the steady-state control accuracy. Finally, real time implementations of the proposed algorithm are applied on the PZT actuated servo system, where excellent tracking performance with tracking precision error around 6‰ for circular contour tracking is achieved in the experimental results.
Experiences of a Speech-enabled Conversational Agent for the Self-report of Well-being among People Living with Affective Disorders: An In-the-Wild Study

The growing commercial success of smart speaker devices following recent advancements in speech recognition technology has surfaced new opportunities for collecting self-reported health and well-being data. Speech-enabled conversational agents (CAs) in particular, deployed in home environments using just such systems, may offer increasingly intuitive and engaging means of self-report. To date, however, few real-world studies have examined users’ experiences of engaging in the self-report of mental health using such devices or the challenges of deploying these systems in the home context. With these aims in mind, this article recounts findings from a 4-week “in-the-wild” study during which 20 individuals with depression or bipolar disorder used a speech-enabled CA named “Sofia” to maintain a daily diary log, responding also to the World Health Organization–Five Well-Being Index WHO-5 scale every 2 weeks. Thematic analysis of post-study interviews highlights actions taken by participants to overcome CAs’ limitations, diverse personifications of a speech-enabled agent, and unique forms of valuing of this system among users’ personal and social circles. These findings serve as initial evidence for the potential of CAs to support the self-report of mental health and well-being, while highlighting the need to address outstanding technical limitations in addition to design challenges of conversational pattern matching, filling unmet interpersonal gaps, and the use of self-report CAs in the at-home social context. Based on these insights, we discuss implications for the future design of CAs to support the self-report of mental health and well-being.
HotFuzz: Discovering Temporal and Spatial Denial-of-Service Vulnerabilities Through Guided Micro-Fuzzing

Fuzz testing repeatedly assails software with random inputs in order to trigger unexpected program behaviors, such as crashes or timeouts, and has historically revealed serious security vulnerabilities. In this article, we present HotFuzz, a framework for automatically discovering Algorithmic Complexity (AC) time and space vulnerabilities in Java libraries. HotFuzz uses micro-fuzzing, a genetic algorithm that evolves arbitrary Java objects in order to trigger the worst-case performance for a method under test. We define Small Recursive Instantiation (SRI) as a technique to derive seed inputs represented as Java objects to micro-fuzzing. After micro-fuzzing, HotFuzz synthesizes test cases that triggered AC vulnerabilities into Java programs and monitors their execution in order to reproduce vulnerabilities outside the fuzzing framework. HotFuzz outputs those programs that exhibit high resource utilization as witnesses for AC vulnerabilities in a Java library. We evaluate HotFuzz over the Java Runtime Environment (JRE), the 100 most popular Java libraries on Maven, and challenges contained in the DARPA Space and Time Analysis for Cybersecurity (STAC) program. We evaluate SRI’s effectiveness by comparing the performance of micro-fuzzing with SRI, measured by the number of AC vulnerabilities detected, to simply using empty values as seed inputs. In this evaluation, we verified known AC vulnerabilities, discovered previously unknown AC vulnerabilities that we responsibly reported to vendors, and received confirmation from both IBM and Oracle. Our results demonstrate that micro-fuzzing finds AC vulnerabilities in real-world software, and that micro-fuzzing with SRI-derived seed inputs outperforms using empty values in both the temporal and spatial domains.
Study of Walking Robot for 3 Dimensional Terrain (Optimization of Walking Motion Based on GDA and Coupled Drive).

The mobile robots which can walk around and perform several tasks over 3D terrain, a generalized terrain including the surface of wall and ceiling of large constructions are highly demanded. We discuss the control of the leg motion of quadruped-wall-climbing-robot specifically designed for 3D terrain from the view point of two design and control concepts which we have already proposed, the GDA, or gravitationally decoupled actuation, and Coupled Drive. The GDA was introduced to eliminate negative power consumption and improve energy efficiency in ground walking, and the Coupled Drive was introduced to evenly distribute power generation among installed actuators, decrease the weight of the actuation mechanism, and enable powerful walking in wall climbing motion. In this article we propose a new control method to adaptively select walking postures in both ground walk and wall climbing and optimize the walking performances in terms of the concepts of GDA and Coupled Drive. We made simulation experiments considering actual actuation characteristics, standing motion constraint and other boundary conditions and shows that the introduced control improve walking performance in 3D terrain well.
Recent advancements in metal–organic frameworks integrating quantum dots (QDs@MOF) and their potential applications

Abstract Design and development of new materials and their hybrids are key to addressing current energy issues. Thanks to their tunable textural and physiochemical properties, metal–organic frameworks (MOFs) show great potential toward gas sorption, catalysis, sensing, and electrochemical energy applications. Nevertheless, practical applications of MOFs have been hampered because of their limited electrical conductivity, micropore size, and poor stability. However, smart integration of zero-dimensional quantum dots (QDs) into an MOF template, where the host structure offers suitable interactions for enhancing the stability and synergic properties, may be a solution. The objective of this review is to summarize recent advances in the field of QD@MOFs, highlighting fresh approaches to synthesis strategies and progress made in their application to optoelectronic devices, sensing, biomedical, catalysis, and energy storage. The current challenges and future directions of QDs@MOFs hybrids toward advancing energy and environmental applications are also addressed. We anticipate that this review will inspire researchers to develop novel MOF hybrids for energy, optoelectronics, and biomedical applications.
Food Nitrogen Footprint of the Indian Subcontinent Toward 2050

Substantial loss of nitrogen (N) in reactive forms (nitrogen species except for N2) induced by agro–food system is a cause of the environmental degradation and harms human health. The main factors influencing the food N footprint of the Indian Subcontinent (ISC) are the nitrogen use efficiency (NUE) of crop cultivation and religious dietary cultures. In this study, we assess the food N footprint of the ISC and establish reduction scenarios toward 2050. We used a religion-sensitive N-Calculator method and food consumption data from the Food and Agriculture Organization of the United Nations to estimate the food N footprint of the ISC of different religious communities. We developed four reduction scenarios as follows: The business-as-usual scenario; a 30% increase in the crop cultivation NUE; altered protein supplies to the healthy EAT–Lancet reference diet considering religious food taboos; and an integrated approach with a 30% increase in the NUE increase and the altered diet. We used the long short-term memory recurrent neural network approach to predict the future. The study revealed that the average food N footprint per-capita per-year increased from 7.94 kg-N in the 1960s to 8.43 kg-N in the early 2010s, and the crop cultivation NUE was reduced to less than 40%. Buddhists had the lowest footprint over the period. An increase in the NUE of the crop cultivation and an altered diet results in a 13% reduction in the N footprint compared to the business-as-usual scenario. We conclude that improved crop cultivation NUEs and an altered religion-specific healthy diet would reduce the N footprint.
Decreased Exercise-Induced Changes in Prefrontal Cortex Hemodynamics Are Associated With Depressive Symptoms

People with a depressed mood tend to perform poorly on executive function tasks, which require much of the prefrontal cortex (PFC), an area of the brain which has also been shown to be hypo-active in this population. Recent research has suggested that these aspects of cognition might be improved through physical activity and cognitive training. However, whether the acute effects of exercise on PFC activation during executive function tasks vary with depressive symptoms remains unclear. To investigate these effects, 106 participants were given a cardiopulmonary exercise test (CPET) and were administered a set of executive function tests directly before and after the CPET assessment. The composite effects of exercise on the PFC (all experimental blocks) showed bilateral activation changes in dorsolateral (BA46/9) and ventrolateral (BA44/45) PFC, with the greatest changes occurring in rostral PFC (BA10). The effects observed in right ventrolateral PFC varied depending on level of depressive symptoms (13% variance explained); the changes in activation were less for higher levels. There was also a positive relationship between CPET scores (VO2peak) and right rostral PFC, in that greater activation changes in right BA10 were predictive of higher levels of aerobic fitness (9% variance explained). Since acute exercise ipsilaterally affected this PFC subregion and the inferior frontal gyrus during executive function tasks, this suggests physical activity might benefit the executive functions these subregions support. And because physical fitness and depressive symptoms explained some degree of cerebral upregulation to these subregions, physical activity might more specifically facilitate the engagement of executive functions that are typically associated with hypoactivation in depressed populations. Future research might investigate this possibility in clinical populations, particularly the neural effects of physical activity used in combination with mental health interventions.
The Development of Mechanical Allodynia in Diabetic Rats Revealed by Single-Cell RNA-Seq

Mechanical allodynia (MA) is the main reason that patients with diabetic peripheral neuropathy (DPN) seek medical advice. It severely debilitates the quality of life. Investigating hyperglycemia-induced changes in neural transcription could provide fundamental insights into the complex pathogenesis of painful DPN (PDPN). Gene expression profiles of physiological dorsal root ganglia (DRG) have been studied. However, the transcriptomic changes in DRG neurons in PDPN remain largely unexplored. In this study, by single-cell RNA sequencing on dissociated rat DRG, we identified five physiological neuron types and a novel neuron type MAAC (Fxyd7+/Atp1b1+) in PDPN. The novel neuron type originated from peptidergic neuron cluster and was characterized by highly expressing genes related to neurofilament and cytoskeleton. Based on the inferred gene regulatory networks, we found that activated transcription factors Hobx7 and Larp1 in MAAC could enhance Atp1b1 expression. Moreover, we constructed the cellular communication network of MAAC and revealed its receptor-ligand pairs for transmitting signals with other cells. Our molecular investigation at single-cell resolution advances the understanding of the dynamic peripheral neuron changes and underlying molecular mechanisms during the development of PDPN.
High Voltage SiC Power Module Optimized for Low Parasitics and Compatible System Interface

SiC power Metal-Oxide-Semiconductor Field-Effect Transistors (MOSFETs) are strong candidates to replace Si devices in high voltage applications. Their high breakdown voltage and high switching frequency characteristics enable a drastic enhancement in power density and a significant reduction in complexity of the power electric system. However, proper power module packaging is critical to meet the sufficient insulation distance while simultaneously minimizing parasitics, especially at the module-system interface. This paper addresses the criticality effect of terminal arrangement on 10 kV power module performance. Three kinds of typical module layouts are compared in terms of system interface and parasitics. Thus, a concept of arranging terminals into groups according to the electric potential is proposed to provide a compact module layout with sufficient insulation. Based on this concept, an optimized terminal layout with low commutation loop inductance and attractive module-system interface is recommended for high voltage power module design.
WAN Converter: A Family of Multicell PWM Converter with All-in-One Magnetics

This paper presents a family of PWM converters - the WAN Converter - with matrix coupled “all-in-one” mag-netics for wide operation range dc-dc applications. The WAN converter comprises multiple PWM converter cells driving a single magnetic component with matrix coupling. The matrix coupled multi-winding magnetics miniaturizes the dc inductive energy storage and significantly reduces the loss and volume of magnetic components. By applying multiphase interleaving, the inductor current ripple can be greatly decreased while maintaining fast transient speed. Topologies with matrix coupled magnetics achieve higher efficiency, higher power density, and faster dynamic response than with discrete magnetic components. To validate the WAN topology and matrix coupling concept, a 1 V-to-5 V input, 1 V-to-5 V output, four-phase SEPIC-based WAN prototype with a planar PCB matrix coupled inductor was designed and tested. PCB windings are optimized to reduce the ac resistance. The WAN prototype can support load current up to 185 A at 5 V-to-1 V voltage conversion with a maximum power density over 470 W/in3. Compared to discrete commercial inductors, the matrix coupled inductor has a 4x smaller size and 9x faster transient speed with similar current ripple and rating.
Improved Methodology for Estimating Switching Losses of Wide Band-Gap Semiconductors Using Gaussian Curve Fitting

The accurate assessment of switching losses is critical for evaluating the achievable performance of hard-switched applications implemented with wide band-gap semiconductors. The traditional method for evaluating the switching losses for a particular semiconductor device is to calculate the instantaneous switching power from the drain-source voltage and drain current waveforms, and then integrate the power waveform to compute switching loss. However, a potential problem arises due to the need to manually select limits of integration for the resulting instantaneous power waveform. To date, there is no widely recognized standard practice for selecting integration bounds during this process. The resulting variability in approach compromises the ability to fairly assess and reliably compare performance between devices. To address this issue, the present paper proposes a switching loss estimation method based on Gaussian curve fitting that does not rely on human judgment. The details of the proposed method are discussed, and the results using this method are compared to those from the traditional limit selection method. As is shown, this approach is simple and straightforward to implement, produces consistent results across a wide range of operating conditions, and is especially suitable for automated post-processing of switching waveforms.
On-Demand Q-Switching Regime in Optically Injected Dual-Section Quantum-Dot Laser

Pure Q-switching (self-pulsating) behaviour is shown for the first time in an optically injected two-section quantum-dot laser. Upon CW optical injection, it was possible to switch the operation regime from free-running mode-locking to locked Q-switching. Under this regime, the pulse repetition rate of around 1 GHz was tunable with injection power (by more than 100 MHz) and absorber reverse bias. Moreover, through injection-locking, the Q-switched output was spectrally tunable by around 7 nm, by tuning the master laser. The seamless switch between mode-locking and Q-switching with optical injection as well as the tunability and control afforded by injection-locking could open up a range of applications, such as in multi-modal imaging. On a more fundamental level, this investigation has also generated new insights into the dynamics of quantum-dot lasers and the optical injection process.
A Modular Single-Stage PV Step-up Converter With Integrated Power Balancing Feature Using Inter-Coupled Active Voltage Quadruplers

This paper presents a novel modular single-stage photovoltaic step-up converter with an integrated power balancing technique that features high frequency inter-connecting active voltage quadruplers (VQ). The input stage of each module consists of an integrated boost circuit with a CLL resonant circuit, allowing for both maximum power point tracking (MPPT) and soft-switching operation to be achieved. To achieve balanced output voltage for all the modules while providing MPPT, the output inductor of the resonant circuit in each module is coupled with the neighboring module with duty ratio control of the active VQ circuit is used to control the output voltage. The proposed technique allows the entire PV converter system to simultaneously achieve: (1) MPPT, (2) soft-switching operation for all modules, and (3) equal output voltage and power distribution without the use of additional circuitry. Descriptions of the proposed converter and the proposed power balancing technique are provided. Results on a 2kW, 3kV-output system is provided to highlight the features of the proposed converter configuration.