Quantifying the Impact of Ultraviolet Subtype C in Reducing Airborne Pathogen Transmission and Improving Energy Efficiency in Healthy Buildings: A Kahn–Mariita Equivalent Ventilation Model

There is growing evidence that viruses responsible for pandemics, such as Middle East respiratory syndrome and severe acute respiratory syndrome, are mainly spread through aerosols. Recommendations have been introduced to reduce the transmission risks of virulent airborne viral particles by increasing ventilation rates, expressed in air changes per hour (ACHs), effectively improving the dilution of pathogens via mechanical ventilation. However, infrastructural and operational costs associated with upgrades of building heating, ventilation, and air conditioning systems make these solutions expensive. It is well documented that Ultraviolet Subtype C (UVC) disinfection can help lower exposure risks by inactivating viruses and the performance of such solutions can translate into equivalent ventilation. Here, we present the first framework to extract the optimal UVC requirements to improve facility management yet ensuring compliance with ventilation guidelines at lower energy costs. The Kahn–Mariita (KM) model considers the air quality of shared enclosed spaces over time by supplementing the existing mechanical ventilation with localized UVC air treatment and includes variables such as room size, occupancy, existing ventilation, and target equivalent ACH. For example, the model applied to a conference room shows that a UVC chamber with recirculation rates of 160 m3/h increases ventilation from an ACH 3 to 7.9 and reduces the room’s reset time from 46 to <10 min with as little as 1 W. Recirculation rates of 30 m3/h however offer no benefits beyond 200 mW, with an eACH of 3.9 and reset time of 31 min. The first finding is that single-pass disinfection is not an appropriate metric of performance, i.e., low recirculation rates increase single-pass disinfection, and, however, only treats a portion of the space volume within a given time, limiting the overall performance. Conversely, higher recirculation rates decrease single-pass disinfection but treat larger portions of air, potentially multiple times, and are therefore expected to lower the transmission risk faster. The second result is that for fixed amounts of recirculating air flow, increasing UVC power helps with diminishing return, while for a fixed UVC power, increasing the recirculating air flow will always help. This dynamic is particularly important toward optimizing solutions, given the constraints system engineers must work with, and particularly to design for end-user benefits such as increased occupancy, in-dwelling time, or reduction of shared-space reset time.

Using Machine Learning for Predicting the Best Outcomes With Electrical Muscle Stimulation for Tremors in Parkinson’s Disease

Recent studies have identified that peripheral stimulation in Parkinson’s disease (PD) is effective in tremor reduction, indicating that a peripheral feedback loop plays an important role in the tremor reset mechanism. This was an open-label, quasi-experimental, pre- and post-test design, single-blind, single-group study involving 20 tremor-dominant PD patients. The objective of this study is to explore the effect of electrical muscle stimulation (EMS) as an adjunctive treatment for resting tremor during “on” period and to identify the best machine learning model to predict the suitable stimulation level that will yield the longest period of tremor reduction or tremor reset time. In this study, we used a Parkinson’s glove to evaluate, stimulate, and quantify the tremors of PD patients. This adjustable glove incorporates a 3-axis gyroscope to measure tremor signals and an EMS to provide an on-demand muscle stimulation to suppress tremors. Machine learning models were applied to identify the suitable pulse amplitude (stimulation level) in five classes that led to the longest tremor reset time. The study was registered at the www.clinicaltrials.gov under the name “The Study of Rest Tremor Suppression by Using Electrical Muscle Stimulation” (NCT02370108). Twenty tremor-dominant PD patients were recruited. After applying an average pulse amplitude of 6.25 (SD 2.84) mA and stimulation period of 440.7 (SD 560.82) seconds, the total time of tremor reduction, or tremor reset time, was 329.90 (SD 340.91) seconds. A significant reduction in tremor parameters during stimulation was demonstrated by a reduction of Unified Parkinson’s Disease Rating Scale (UPDRS) scores, and objectively, with a reduction of gyroscopic data (p < 0.05, each). None of the subjects reported any serious adverse events. We also compared gyroscopic data with five machine learning techniques: Logistic Regression, Random Forest, Support Vector Machine (SVM), Neural Network (NN), and Long-Short-Term-Memory (LSTM). The machine learning model that gave the highest accuracy was LSTM, which obtained: accuracy = 0.865 and macro-F1 = 0.736. This study confirms the efficacy of EMS in the reduction of resting tremors in PD. LSTM was identified as the most effective model for predicting pulse amplitude that would elicit the longest tremor reset time. Our study provides further insight on the tremor reset mechanism in PD.

Using Adaptive Psychophysics to Identify the Neural Network Reset Time in Sub-second Interval Timing

State dependent network models of sub-second interval timing propose that duration is encoded in states of neuronal populations that need to reset prior to a novel timing operation in order to maintain optimal timing performance. Previous research has shown that the approximate boundary of this reset interval can be inferred by varying the interstimulus interval between two to-be-timed intervals. However, the estimated boundary of this reset interval is broad (250-500ms) and remains underspecified with implications for the characteristics of state dependent network dynamics subserving interval timing. Here we probed the interval specificity of this reset boundary by manipulating the interstimulus interval between standard and comparison intervals in two sub-second auditory duration discrimination tasks (100 and 200ms) and a control (pitch) discrimination task using adaptive psychophysics. We found that discrimination thresholds improved with the introduction of a 333ms interstimulus interval relative to a 250ms interstimulus interval in both duration discrimination tasks, but not in the control task. This effect corroborates previous findings of a breakpoint in the discrimination performance for sub-second stimulus interval pairs as a function of an incremental interstimulus delay but more precisely localizes the minimal interstimulus delay range. These results suggest that state dependent networks subserving sub-second timing require approximately 250-333ms for the network to reset in order to maintain optimal interval timing.New & NoteworthyThe state-dependent-network model considers interval timing as an intrinsic ability of neuronal populations to track the temporal evolution of their collective state. However, the time-dependent nature of neuronal properties imposes constraints on a maximum encodable interval and on the processing of intervals that are presented before the network resets to its baseline state. Investigating temporal discrimination thresholds as a function of variable inter-stimulus-intervals, we showed that the network reset time is between 250 and 333ms.

Proroguing Canada parliament gives Trudeau reset time

Headline CANADA: Proroguing parliament gives Trudeau reset time

Optimal PID Controller Tuning using Simulated Annealing based Internal Model Control

In this paper, simulated annealing (SA), a heuristic algorithm is used to tune PID based Internal Model Control (IMC) for large and small / systems. PID tuning is effected with SA optimizer. The IMC technique requires tuning of a single parameter, filter constant which in turn is used to find the PID controller parameters: proportional gain, reset time and derivative time. The proposed method uses SA for tuning the filter constant. The proposed method is verified in systems with different / ratio.

Hubungan Perubahan Tata Guna Lahan dengan Debit Air Limpasan pada Kawasan Hunian Pantai Indah Kapuk 2

<p>The construction of the residential and commercial area of Pantai Indah Kapuk (PIK) 2 Cluster “D” is located in the part of two sub-district, which is Sub-district of Kosambi and Sub-district of Teluknaga. PIK 2 Cluster “D” has an area of 508,59 Ha. With the construction of PIK 2 Cluster “D”, there will be a change of land use and an enchancement of run off water. The relationship between the change of land use and the enhancement of run off water can be seen from run off peak deviation for reset time T year (Q_r) on existing condition with planning condition after the change of land use. The method used is the rational method which is estimating run off peak. There is an enhancement off run off coefficient value (C) on existing condition about 0,46 and 0,81 on planning condition which causing an enhancement off run off peak in planning area as the effect of the change of land use as Q = 87,59 m³/second. The enhancement of run off coefficient value as the effect of the change of land use is directly proportional with the enhancement of run off peak in case study residential and commercial area of PIK 2 Cluster “D”.</p>

ANALYSIS OF POWER CONSUMPTION SAR-ADC DYNAMIC COMPARATOR

Due to the high demand of ultra-low power in digital application, the needs of energy efficient analog-to-digital converter (ADC) are really essential. The comparator being an important part of successive approximation register (SAR)-ADC needs to have optimum performance under low power condition. This paper presents the comparison on power consumption together with the output performance flow power SAR-ADC dynamic comparators from three different design proposed by previous researchers. The three circuits is simulated and compared in terms of power consumption, regeneration time, reset time and output transient. The simulation is using Cadence Spectre and setup with 0.18µm CMOS technology, VDD at 0.8V and clock speed 2 at MHz. The analysis results obtained provides the lowest voltage input different (ΔVin) possible for double tail dynamic comparator using 0.18µm CMOS technology while adhering to the 45 corner process requirement. The results can be used as references for further design of ultra-low power dynamic comparator.