Real-Time Nitrate Ion Monitoring with Poly(3,4-ethylenedioxythiophene) (PEDOT) Materials.

Nitrate (NO3) pollution in groundwater, caused by various factors both natural and synthetic, contributes to the decline of human health and well-being. Current techniques used for nitrate detection include spectroscopic, electrochemical, chromatography, and capillary electrophoresis. It is highly desired to develop a simple cost-effective alternative to these complex methods for nitrate detection. Therefore, a real-time poly (3,4-ethylenedioxythiophene) (PEDOT)-based sensor for nitrate ion detection via electrical property change is introduced in this study. Vapor phase polymerization (VPP) is used to create a polymer thin film. Variations in specific parameters during the process are tested and compared to develop new insights into PEDOT sensitivity towards nitrate ions. Through this study, the optimal fabrication parameters that produce a sensor with the highest sensitivity toward nitrate ions are determined. With the optimized parameters, the electrical resistance response of the sensor to 1000 ppm nitrate solution is 41.79%. Furthermore, the sensors can detect nitrate ranging from 1 ppm to 1000 ppm. The proposed sensor demonstrates excellent potential to detect the overabundance of nitrate ions in aqueous solutions in real time.

Software Defined Radio-Based Wireless Sensing System.

In this paper, we investigate the application of using software-defined radio (SDR) and surface acoustic wave (SAW) device for wireless measurement of the response of in situ sensors. SDR uses software to realize different communication functions. After collecting the magnitude and phase of the response at discrete frequencies, we apply inverse Fourier transform to analyze the time domain responses which, in turn, allows for monitoring the changes of the response of the in situ sensor. We employ microwave signal flow graph concepts to improve the quality of the received signals. Comparing the normalized results obtained by SDR with those obtained from a commercial vector network analyzer (VNA), we demonstrate that the results are sufficiently close, and the SDR-based experiments can provide satisfactory measurement of the in-situ sensors. The objective is to eventually employ this wireless measurement system for soil nutrient sensing.

Gait Study of Parkinson's Disease Subjects Using Haptic Cues with A Motorized Walker.

Gait abnormalities are one of the distinguishing symptoms of patients with Parkinson's disease (PD) that contribute to fall risk. Our study compares the gait parameters of people with PD when they walk through a predefined course under different haptic speed cue conditions (1) without assistance, (2) pushing a conventional rolling walker, and (3) holding onto a self-navigating motorized walker under different speed cues. Six people with PD were recruited at the New York Institute of Technology College of Osteopathic Medicine to participate in this study. Spatial posture and gait data of the test subjects were collected via a VICON motion capture system. We developed a framework to process and extract gait features and applied statistical analysis on these features to examine the significance of the findings. The results showed that the motorized walker providing a robust haptic cue significantly improved gait symmetry of PD subjects. Specifically, the asymmetry index of the gait cycle time was reduced from 6.7% when walking without assistance to 0.56% and below when using a walker. Furthermore, the double support time of a gait cycle was reduced by 4.88% compared to walking without assistance.

Drinking Large Volume of Hot Water May Cause Increased 18 F-FDG Uptake in Esophagus.

ABSTRACT: We present 2 cases of diffuse FDG accumulation in the esophagus due to drinking hot water before an 18 F-FDG PET/CT scan. Drinking large volume of hot water immediately before the FDG PET/CT study may lead to challenges in the interpretation of the hypermetabolic esophagus.

FDG-Avid Periprosthetic Particle Disease Mimicking Osteosarcoma Recurrence.

ABSTRACT: A 24-year-old man with a history of osteosarcoma presented with swelling in his right thigh for more than 1 year. 18 F-FDG PET/CT demonstrated increased FDG uptake in multiple juxtacortical masses around the prosthesis, which highly suggested the possibility of osteosarcoma recurrence. A biopsy was performed, and the pathology confirmed the diagnosis of particle disease. The current case indicates that particle disease should be considered when interpreting the PET/CT images with high FDG uptake around the prosthesis.

Simple Pulmonary Eosinophilia Mimicking Lung Metastases on 18F-FDG PET/CT.

ABSTRACT: A 72-year-old man with pancreatic tail cancer underwent distal pancreatectomy and splenectomy 1 year ago. Routine postoperative follow-up CT detected multiple pulmonary nodules. 18F-FDG PET/CT showed multiple FDG-avid nodules in the bilateral lungs, which highly suggested the possibility of lung metastases of pancreatic cancer. Finally, the bronchoalveolar lavage fluid and pathology confirmed the diagnosis of simple pulmonary eosinophilia.

A global blockchain for recording high rates of COVID-19 vaccinations.

Blockchain has been recently proposed to securely record vaccinations against COVID-19 and manage their verification. However, existing solutions may not fully meet the requirements of a global vaccination management system. These requirements include the scalability required to support a global vaccination campaign, like one against COVID-19, and the capability to facilitate the interoperation between the independent health administrations of different countries. Moreover, access to global statistics can help to control securing community health and provide continuity of care for individuals during a pandemic. In this paper, we propose GEOS, a blockchain-based vaccination management system designed to address the challenges faced by the global vaccination campaign against COVID-19. GEOS offers interoperability between vaccination information systems at both domestic and international levels, supporting high vaccination rates and extensive coverage for the global population. To provide those features, GEOS uses a two-layer blockchain architecture, a simplified byzantine-tolerant consensus algorithm, and the Boneh-Lynn-Shacham signature scheme. We analyze the scalability of GEOS by examining transaction rate and confirmation times, considering factors such as the number of validators, communication overhead, and block size within the blockchain network. Our findings demonstrate the effectiveness of GEOS in managing COVID-19 vaccination records and statistical data for 236 countries, encompassing crucial information such as daily vaccination rates for highly populous nations and the global vaccination demand, as identified by the World Health Organization.

Solitary Malignant Peripheral Nerve Sheath Tumor of Lumbar Vertebra Mimicking Metastatic Malignancy.

ABSTRACT: Malignant peripheral nerve sheath tumor involving solitary lumbar vertebra is extremely rare. A 72-year-old man had a chief complaint of growing lumbocrural pain for 2 months. The CT scan detected a solitary vertebral lesion, which highly supported the diagnosis of metastatic malignancy. 18 F-FDG PET/CT demonstrated that the vertebral lesion had heterogeneous intense FDG accumulation with an SUV max of 16.4. The pathological examination confirmed the diagnosis of malignant peripheral nerve sheath tumor. This case highlights that MPNST should be considered when there is solitary vertebra invasion with increased FDG uptake.

Solitary Scapular Metastasis as the First Presentation of Prostate Adenocarcinoma Identified on 99mTc-MDP SPECT/CT.

ABSTRACT: Metastases of prostate carcinoma in the skeleton are usually multiple. Solitary metastasis in appendicular skeleton is extremely rare. We present bone scan findings of solitary scapular metastasis from prostate adenocarcinoma as the initial presentation of his malignancy in a 62-year-old man. The 99mTc-MDP SPECT/CT demonstrated intense activity in the coracoid process of left scapula, whereas the tracer uptakes in other bones were not typical of metastases. The subsequent pathological results of the punctured left scapula confirmed as metastasis from prostate adenocarcinoma.

The value of FT4/TSH ratio in the differential diagnosis of Graves' disease and subacute thyroiditis.

Objective: To explore the value of the FT4/TSH ratio in the etiological diagnosis of newly diagnosed patients with thyrotoxicosis. Methods: The retrospective study was conducted on 287 patients with thyrotoxicosis (122 patients with subacute thyroiditis and 165 patients with Graves' disease) and 415 healthy people on their first visit to our hospital. All patients underwent thyroid function tests including the measurement of T3, T4, FT3, FT4, TSH, T3/TSH, and T4/TSH. The receiver operating characteristic (ROC) curve was employed to evaluate the value of FT4/TSH in the differential diagnosis of Graves' disease and subacute thyroiditis, and compared with other related indicators. Results: The area under the curve of FT4/TSH for diagnosing Graves' disease and thyroiditis was 0.846, which was significantly larger than the area under the curve of T3/T4 ratio (P< 0.05) and FT3/FT4 ratio (P< 0.05). When the cut-off value of the FT4/TSH ratio was 5731.286 pmol/mIU, the sensitivity was 71.52%, the specificity was 90.16%, the positive predictive value was 90.77% and the negative predictive value was 70.06%. The diagnostic accuracy was 79.44%. Conclusion: FT4/TSH ratio can be used as a new reference index for the differential diagnosis of thyrotoxicosis.

Comparative Analysis of Energy Use and Greenhouse Gas Emission of Diesel and Electric Trucks for Food Distribution in Gowanus District of New York City.

New York City's food distribution system is among the largest in the United States. Food is transported by trucks from twelve major distribution centers to the city's point-of-sale locations. Trucks consume large amounts of energy and contribute to large amounts of greenhouse gas emissions. Therefore, there is interest to increase the efficiency of New York City's food distribution system. The Gowanus district in New York City is undergoing rezoning from an industrial zone to a mix residential and industrial zone. It serves as a living lab to test new initiatives, policies, and new infrastructure for electric vehicles. We analyze the impact of electrification of food-distribution trucks on greenhouse gas emissions and electricity demand in this paper. However, such analysis faces the challenges of accessing available and granular data, modeling of demands and deliveries that incorporate logistics and inventory management of different types of food retail stores, delivery route selection, and delivery schedule to optimize food distribution. We propose a framework to estimate truck routes for food delivery at a district level. We model the schedule of food delivery from a distribution center to retail stores as a vehicle routing problem using an optimization solver. Our case study shows that diesel trucks consume 300% more energy than electric trucks and generate 40% more greenhouse gases than diesel trucks for food distribution in the Gowanus district.

Correlation of subway turnstile entries and COVID-19 incidence and deaths in New York City.

In this paper, we show a strong correlation between turnstile entries data of the New York City (NYC) subway provided by NYC Metropolitan Transport Authority and COVID-19 deaths and cases reported by the NYC Department of Health from March to May 2020. This correlation is obtained through linear regression and confirmed by the prediction of the number of deaths by a Long Short-Term Memory neural network. The correlation is more significant after considering incubation and symptomatic phases of this disease as experienced by people who died from it. We extend the analysis to each individual NYC borough. We also estimate the dates when the number of COVID-19 deaths and cases would approach zero by using the Auto-Regressive Integrated Moving Average model on the reported deaths and cases. We also backward forecast the dates when the first cases and deaths might have occurred.

Survey of Saliva Components and Virus Sensors for Prevention of COVID-19 and Infectious Diseases.

The United States Centers for Disease Control and Prevention considers saliva contact the lead transmission means of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes the coronavirus disease 2019 (COVID-19). Saliva droplets or aerosols expelled by heavy breathing, talking, sneezing, and coughing may carry this virus. People in close distance may be exposed directly or indirectly to these droplets, especially those droplets that fall on surrounding surfaces and people may end up contracting COVID-19 after touching the mucosa tissue on their faces. It is of great interest to quickly and effectively detect the presence of SARS-CoV-2 in an environment, but the existing methods only work in laboratory settings, to the best of our knowledge. However, it may be possible to detect the presence of saliva in the environment and proceed with prevention measures. However, detecting saliva itself has not been documented in the literature. On the other hand, many sensors that detect different organic components in saliva to monitor a person's health and diagnose different diseases that range from diabetes to dental health have been proposed and they may be used to detect the presence of saliva. This paper surveys sensors that detect organic and inorganic components of human saliva. Humidity sensors are also considered in the detection of saliva because a large portion of saliva is water. Moreover, sensors that detect infectious viruses are also included as they may also be embedded into saliva sensors for a confirmation of the virus' presence. A classification of sensors by their working principle and the substance they detect is presented. This comparison lists their specifications, sample size, and sensitivity. Indications of which sensors are portable and suitable for field application are presented. This paper also discusses future research and challenges that must be resolved to realize practical saliva sensors. Such sensors may help minimize the spread of not only COVID-19 but also other infectious diseases.