Assessing Honors Internationalization: A Case Study of Lloyd International Honors College at UNC Greensboro

Lloyd International Honors College (LIHC) of the University of North Carolina at Greensboro (UNC Greensboro) is a useful example of the reimagining of a traditional honors program into an honors college with an international focus.1 The process of becoming an internationally focused honors college, which began in 2006, was part of the university’s strategic goal of internationalizing its curriculum, student body, faculty, and culture. It has involved an extended process of program development; campus-wide partnership building, specifically in conjunction with the university’s International Programs Center (IPC) and Global Engagement Quality Enhancement Plan (QEP); and iterative assessment. This chapter outlines the internationalization of the honors college as it is embedded in an iterative assessment process. In doing so, it highlights the implementation of international programs and structures at the university and in the honors college, defines the assessment framework the university and honors used to guide their internationalization efforts, discusses specific assessment measures and outcomes, and considers future directions

Design and Implementation of Automated Predictive Magnetic Abrasive Finishing Machine

Magnetic abrasive finishing (MAF) is one of the non-traditional methods, that produce high quality condition of surface roughness (Ra) and is primarily controlled by magnetic field. This process can remove materials depending on magnetic energy.The aims of this research have been made to design and implement MA automated predictive machine, which plays an important role to the values of parameters (voltage of electromagnetic, magnetic pole velocity, working gap, and working time) to obtain the desired values for Ra.The microcontroller (Arduino Mega) was used for controlling the four parameters, and can predict the working time from regression model using optimum values parameters.  The automated machine can be programmed to control the electromagnetic voltage, the poles rotation, working gap, turn on and off the rotation of workpiece, and working time.The results indicated that the optimum parameters for the surface roughness are calculated according to Taguchi method and the S/N ratio, and the optimum values before automated the machine are voltage (7V), the working time (7min), poles speed (30r.p.m) and the working gap (1mm) for Ra. The results also indicated that the predict values for Ra is  nearly equal to the values from the automated machine about 95% for  Ra, that mean the automated predictive MA machine are very efficient. Keywords: Automated Machine, MAF Method, Arduino, Surface Roughness

Channel, Phase Noise, and Frequency Offset in OFDM Systems: Joint Estimation, Data Detection, and Hybrid Cramer-Rao Lower Bound

Oscillator phase noise (PHN) and carrier frequency offset (CFO) can adversely impact the performance of orthogonal frequency division multiplexing (OFDM) systems, since they can result in inter carrier interference and rotation of the signal constellation. In this paper, we propose an expectation conditional maximization (ECM) based algorithm for joint estimation of channel, PHN, and CFO in OFDM systems. We present the signal model for the estimation problem and derive the hybrid Cramer-Rao lower bound (HCRB) for the joint estimation problem. Next, we propose an iterative receiver based on an extended Kalman filter for joint data detection and PHN tracking. Numerical results show that, compared to existing algorithms, the performance of the proposed ECM-based estimator is closer to the derived HCRB and outperforms the existing estimation algorithms at moderate-to-high signal-to-noise ratio (SNR). In addition, the combined estimation algorithm and iterative receiver are more computationally efficient than existing algorithms and result in improved average uncoded and coded bit error rate (BER) performance

Co-Production of Cellulase and Xylanase Enzymes By Thermophilic Bacillus subtilis 276NS

Co-production of thermostable extracellular cellulase and xylanase was investigated using bacterial soil isolate. To evaluate the effect of culture conditions on the c-oproduction of both enzymes by Bacillus subtilis 276NS (GenBank accession number JF801740), a Plackett-Burman fractional factorial design was applied. Among the tested variables, yeast extract, sucrose and incubation time were the most significant variables increased cellulase and xylanase productions. Both of xylan and CMC (Carboxymethyl Cellulose) induced the xylanse enzyme production. A near-optimum medium formulation was obtained which increased the cellulase and xylanase enzymes 5.7- and 1.08 –fold higher than the yield obtained with the basal medium, respectively. Thereafter, the response surface methodology was adopted to acquire the best process conditions among the selected variables (xylan, CMC and Yeast Extract (YE)) required for improving xylanase yield. The optimal combinations of the major medium constituents for xylanase production evaluated using non-linear optimization algorithm of EXCEL-solver, was as follows (g/L): D-sucrose, 10; xylan, 10.367, CMC, 10.535; (NH4)2SO4, 1.0; YE, 1.71; Tween-80, 0.4 and FeSO4, 0.25 mg/L, at pH 8.0, temperature 35◦C and incubation time 24h under shaking. The predicted optimum thermostable xylanase activity was 360 U/ml, which was around 4-times the activity with the basal medium

Multi-Relay Communications in the Presence of Phase Noise and Carrier Frequency Offsets

Impairments like time varying phase noise (PHN) and carrier frequency offset (CFO) result in loss of synchronization and poor performance of multi-relay communication systems. Joint estimation of these impairments is necessary in order to correctly decode the received signal at the destination. In this paper, we address spectrally-efficient multi-relay transmission scenarios where all the relays simultaneously communicate with the destination. We propose an iterative pilot-aided algorithm based on the expectation conditional maximization (ECM) for joint estimation of multipath channels, Wiener PHNs, and CFOs in decode-and-forward (DF) based multi-relay orthogonal frequency division multiplexing (OFDM) systems. Next, a new expression of the hybrid Cramér-Rao lower bound (HCRB) for the multi-parameter estimation problem is derived. Finally, an iterative receiver based on an extended Kalman filter (EKF) for joint data detection and PHN tracking is employed. Numerical results show that the proposed estimator outperforms existing algorithms and its mean square error performance is close to the derived HCRB at differnt signal-to-noise ratios (SNRs) for different PHN variances. In addition, the combined estimation algorithm and iterative receiver can significantly improve average bit-error rate (BER) performance compared to existing algorithms. In addition, the BER performance of the proposed system is close to the ideal case of perfect channel impulse responses (CIRs), PHNs and CFOs estimation

A rare case report of ectopic tooth in submandibular salivary gland's duct

This case report highlights mandibular tooth in an ectopic position in the floor of the mouth, associated with submandibular salivary gland, which was completely obliterating the Wharton duct. Very few such cases have been reported in the literatures. Since ectopic tooth may lead to pain, discomfort sensation upon mastication, and even infection (sialadenitis), its diagnosis and treatment is essentia

Selection Algorithm for the CALIPSO Lidar Aerosol Extinction-to-Backscatter Ratio

The extinction-to-backscatter ratio (S(sub a)) is an important parameter used in the determination of the aerosol extinction and subsequently the optical depth from lidar backscatter measurements. We outline the algorithm used to determine Sa for the Cloud and Aerosol Lidar and Infrared Pathfinder Spaceborne Observations (CALIPSO) lidar. S(sub a) for the CALIPSO lidar will either be selected from a look-up table or calculated using the lidar measurements depending on the characteristics of aerosol layer. Whenever suitable lofted layers are encountered, S(sub a) is computed directly from the integrated backscatter and transmittance. In all other cases, the CALIPSO observables: the depolarization ratio, delta, the layer integrated attenuated backscatter, beta, and the mean layer total attenuated color ratio, gamma, together with the surface type, are used to aid in aerosol typing. Once the type is identified, a look-up-table developed primarily from worldwide observations, is used to determine the S(sub a) value. The CALIPSO aerosol models include desert dust, biomass burning, background, polluted continental, polluted dust, and marine aerosols

Neurotropic Manifestations as a Potential Risk Factor for Schizophrenia Following in utero Exposure to SARS-CoV-2

Background: COVID-19 infection is associated with neurologic and psychiatric morbidity that suggests a direct effect of the virus or secondary effect of an inflammatory process. These neuropsychiatric consequences may increase the likelihood of schizophrenia in the offspring of women who become infected with COVID-19 during their pregnancy. Methods: We performed a directed narrative review of the literature focusing on the proposed pathophysiological processes that lead to schizophrenia and known pathological consequences of COVID-19 infection. Results: Schizophrenia in adult offspring has been associated with maternal infections during pregnancy by a wide range of respiratory and neurotropic pathogens. Spikes in the incidence of schizophrenia approximately 20 years after several influenza pandemics have been documented. There are multiple lines of evidence suggesting that a similar pattern may be seen due to the recent COVID-19 pandemic. These include the nonspecific consequences of acute illness and hyperpyrexia, as well as more specific derangements of brain development related to direct effects of the virus or secondary effects of the inflammatory response on the developing brain. There is the potential to prospectively test this hypothesis by following the offspring of women who are known to have developed COVID-19 during their pregnancy. Conclusion: The COVID-19 pandemic is likely associated with a range of future neuropsychiatric consequences in people whose mothers suffered the infection during their fetal development. It is important to try to follow these offspring to determine the full range of consequences of COVID-19 infection

CaO impregnated highly porous honeycomb activated carbon from agriculture waste: symmetrical supercapacitor study

This study presents the electrochemical studies of activated carbon prepared from palm kernel shell (ACPKS), with CaO impregnation. The CaO is obtained from chicken eggshell waste to produce CaO/ACPKS, which shows highly porous honeycomb structure with homogeneous distribution of CaO nanoparticles (30–50 nm in size). The prepared materials are evaluated as supercapacitor electrodes by testing their electrochemical characteristics. A high specific capacitance value of 222 F g−1 at 0.025 A g−1 is obtained for CaO/ACPKS, which is around three times higher than that for ACPKS (76 F g−1). In addition, electrochemical impedance data show lower impedance for CaO/ACPKS. Lastly, a practical symmetrical supercapacitor is fabricated by CaO/ACPKS and its performance is discussed