Tenfold Reduction Research Articles

An Isodipeptide Building Block for Microwave-Assisted Solid-Phase Synthesis of Difficult Sequence-Containing Peptides.

Microwave technology, in conjunction with the isopeptide strategy including Fmoc-based solid-phase peptide synthesis (SPPS), was used to establish a methodology for time-efficient synthesis of peptides containing difficult sequences. A model difficult sequence-containing peptide (8QSer) was synthesized through this method in 1day, representing a tenfold reduction in synthesis time compared to the isopeptide method combined with classical SPPS.

Linewidth-narrowing of a continuous wave terahertz polariton laser using an intracavity etalon

An uncoated etalon was incorporated within an intracavity continuous wave terahertz polariton laser, leading to a tenfold reduction in linewidth, plus a factor of 2 increase in the THz output power. The increase in output power is explained in terms of phase matching considerations for the parametric downconversion process.

Effective Resistance of Two-Dimensional Truncated Infinite Mesh Structures

Determining the effective resistance of a mesh is a powerful tool for simplifying the analysis of complex electrical structures, ranging from transistors to power delivery systems. A common structure in science and engineering is a two-dimensional resistive grid. Applications of this structure include IR drop analysis and decoupling capacitor allocation in on-chip power and ground networks in VLSI systems, and the analysis of electrical and thermal conductive media, such as a semiconductor substrate. In the case where the effective resistance is evaluated far from the grid edges, an infinite resistive lattice can be used to simplify the analysis of a grid. If however the target nodes are located close to the grid edges, the assumption of infinite dimensions becomes invalid, producing inaccurate results. To bridge this gap, a resistive mesh truncated along a single or two dimensions is discussed here. Integral expressions for the effective resistance within a truncated infinite mesh structure are provided, as well as a closed-form approximation, which exhibits good agreement with the exact integral equation, exhibiting an average error of 0.27% and a maximum error of 4.77%. These expressions significantly improve the accuracy of the effective resistance estimation near the edges and corner of a resistive mesh, providing a tenfold reduction in error. In case studies, the expressions provide four to six orders of magnitude speedup in IR analysis of a $10^{4} \times 10^{4}$ grid, while providing accuracy comparable to nodal analysis.

Motion-corrected coronary calcium scores by a convolutional neural network: a robotic simulating study.

To classify motion-induced blurred images of calcified coronary plaques so as to correct coronary calcium scores on nontriggered chest CT, using a deep convolutional neural network (CNN) trained by images of motion artifacts. Three artificial coronary arteries containing nine calcified plaques of different densities (high, medium, and low) and sizes (large, medium, and small) were attached to a moving robotic arm. The artificial arteries moving at 0-90mm/s were scanned to generate nine categories (each from one calcified plaque) of images with motion artifacts. An inception v3 CNN was fine-tuned and validated. Agatston scores of the predicted classification by CNN were considered as corrected scores. Variation of Agatston scores on moving plaque and by CNN correction was calculated using the scores at rest as reference. The overall accuracy of CNN classification was 79.2 ± 6.1% for nine categories. The accuracy was 88.3 ± 4.9%, 75.9 ± 6.4%, and 73.5 ± 5.0% for the high-, medium-, and low-density plaques, respectively. Compared with the Agatston score at rest, the overall median score variation was 37.8% (1st and 3rd quartile, 10.5% and 68.8%) in moving plaques. CNN correction largely decreased the variation to 3.7% (1.9%, 9.1%) (p < 0.001, Mann-Whitney U test) and improved the sensitivity (percentage of non-zero scores among all the scores) from 65 to 85% for detection of coronary calcifications. In this experimental study, CNN showed the ability to classify motion-induced blurred images and correct calcium scores derived from nontriggered chest CT. CNN correction largely reduces the overall Agatston score variation and increases the sensitivity to detect calcifications. • A deep CNN architecture trained by CT images of motion artifacts showed the ability to correct coronary calcium scores from blurred images. • A correction algorithm based on deep CNN can be used for a tenfold reduction in Agatston score variations from 38 to 3.7% of moving coronary calcified plaques and to improve the sensitivity from 65 to 85% for the detection of calcifications. • This experimental study provides a method to improve its accuracy for coronary calcium scores that is a fundamental step towards a real clinical scenario.

Accuracy improvement in OFDR-based distributed sensing system by image processing

The measurement repeatability and accuracy encounter rapid deterioration when the gauge length drops below several millimeters in optical frequency domain reflectometry (OFDR) based distributed sensing system. To improve the measurement accuracy when the gauge length is short, an approach based on the image processing is presented in this work. We have demonstrated the process of making the original 1D signal derived from the OFDR-based distributed sensing system be a 2D image. The image processing is then applied to denoise the image, which could make use of the 2D information from the measured data. The quality of each 1D cross-correlation profile is enhanced, and therefore the accuracy of the peak detection for the calculation of the spectrum deviation induced by the strain change could be improved. Three image processing methods are introduced, evaluated and compared in a thoughtful way. The strategy of overlapped window is introduced to reduce the deterioration effect on the spatial resolution due to image processing. The distributed strain with a gauge length of 0.4 mm is measured. Five- to tenfold reduction on the measurement standard deviation when the gauge length is less than 3 mm has been achieved. The results are helpful for high spatial resolution sensing applications. Furthermore, the non-local means algorithmic acceleration technique based on the summed square image scheme and fast Fourier Transform is illustrated and used to speed up the non-local means algorithm, making the processing speed over 30 times faster.

Improving the Time Stability of Superconducting Planar Resonators

ABSTRACTQuantum computers are close to become a practical technology. Solid-state implementations based, for example, on superconducting devices strongly rely on the quality of the constituent materials. In this work, we fabricate and characterize superconducting planar resonators in the microwave range, made from aluminum films on silicon substrates. We study two samples, one of which is unprocessed and the other cleaned with a hydrofluoric acid bath and by heating at 880 °C in high vacuum. We verify the efficacy of the cleaning treatment by means of scanning transmission electron microscope imaging of samples’ cross sections. From 3 h-long resonator measurements at ≈ 10 mK and with ≈ 10 photonic excitations, we estimate the frequency flicker noise level using the Allan deviation and find an approximately tenfold noise reduction between the two samples; the cleaned sample shows a flicker noise power coefficient for the fractional frequency of ≈ 0.23 × 10−15. Our preliminary results follow the generalized tunneling model for two-level state defects in amorphous dielectric materials and show that suitable cleaning treatments can help the operation of superconducting quantum computers.

A hybrid acceleration method to pin-by-pin calculations using the heterogeneous variational nodal method

As a continued research for our previous work, a hybrid method to accelerating pin-by-pin calculations based on the heterogeneous variational nodal method (VNM) is presented. Previously the coarse node acceleration method (CNA) was proposed for inner iterations. In this paper, the formulation of the generalized partitioned matrix method (GPM) to the heterogeneous VNM which accelerates outer iterations is elaborated. The hybrid utilization of the two methods is examined with the C5G7 problem and the small modular reactor problem. Numerical comparisons demonstrated that the hybrid acceleration method results in over ten-fold reduction in the total computational time.

The Impact of Temperature and Switching Rate on Dynamic Transients of High-Voltage Silicon and 4H-SiC NPN BJTs: A Technology Evaluation

This paper reports the application of silicon bipolar junction transistor (BJT) modeling techniques to the modeling of dynamic behavior of high-voltage 4H-SiC BJTs, and the experimental validation thereof. High-voltage silicon BJTs are impractical due to their low current gain that requires a bulky base driver. Emergence of high-voltage 4H-SiC vertical NPN BJTs with a tenfold higher gain enables the application of efficient drivers, with ratings close to those of IGBTs. This paper demonstrates the advantages offered by 4H-SiC BJTs by means of wide-scale measurements at 800 V and 10 A in a range of temperatures up to 175 °C and adjusted base driver switching rates. This paper shows that the turn- off storage delay in the SiC BJT is two orders of magnitude lower than that of the silicon device. It also shows that the turn- on switching transients of SiC device are by an order of magnitude and the turn- off transients are by two orders of magnitude faster than that of its silicon counterpart, resulting in a tenfold reduction of the switching energy. It also demonstrates the temperature dependence of switching transients of the silicon BJT, and the relative temperature-invariance of the SiC device's performance. This paper concludes with validation of the transient models for the 4H-SiC NPN BJT, showing that the model is sufficiently accurate for transient switching and loss calculations.

Critical process parameters in manufacturing of liposomal formulations of amphotericin B

Identifying the critical process parameters (CPPs) of a complex drug product manufacture and the associated impact on critical quality attributes (CQAs) is essential to the development and quality control of both new and generic drugs. AmBisome, a liposomal amphotericin B (AMB) macrolide antibiotic widely adopted as an important antifungal drug product, was used as a model complex drug product in the current study. This study investigated how multi-step production approaches and related manufacturing conditions may affect essential physico-chemical and toxicological properties of the final drug product. A key challenge in the manufacture and analysis of liposomal AMB was the drug substance’s propensity to aggregate, with associated poor solubility in water and organic solvents. This study identified three key CPPs in a four step manufacturing process: (i) proper acidification during formation of the drug-lipid complexes (Step 1), (ii) liposome heat curing following liposomal particle sizing (Step 3), and (iii) flash-freezing at the initial stages of the lyophilization cycle (Step 4). Over-acidification led to rapid degradation of the drug, whereas under-acidification hampered full solubilization and formation of the soluble drug-lipid complexes. Extended heat treatment of the formed liposomes at 65 °C, just above the lipid phase transition temperature, brought dramatic changes in the aggregated state and/or packing of the drug in the liposomal bilayer, as followed by the complex changes in the UV/Vis spectra. Such thermal conditioning resulted in a five- to ten-fold reduction in the in-vitro toxicity of the drug product, bringing it close to the values for AmBisome used as control and measured by the RBC assay. Finally, flash-freezing conditions during lyophilization was critical to prevent aggregation and maintaining the 80–120 nm liposome size when reconstituted. Our research found that changes in the amphotericin’s UV/Vis spectra were a sensitive CQA measure and provided a set of quantitative parameters for a facile non-destructive process monitoring in-situ, as well as for comparison of the quality of final formulations.

Fine road dust contamination in a mining area presents a likely air pollution hotspot and threat to human health

The road dust found in mining areas is composed of dust from multiple sources, including wind transported mineral dust from mines and tailings as well as uncovered trucks leakage. Collectively, these are then distributed via wind and traffic activity, becoming an important source of particulate matter (PM) and subsequently inhaled by pedestrians. A common practice in previous road dust risk assessments has regarded them as soil, which likely led to a significant underestimation of the actual inhaled amount. To more accurately understand the inhalation risk presented by road dust in mining areas, the study applied a detailed pollution analysis and dust dispersion model to assess the inhaled amount of road dust. Road dust samples located at different distances to the mine and tailings were collected and sieved to 10 μm (RD10). Enrichment factors (EFs) of Ce, As, Cd, and Mo exceeded 20 across most sampled sites, suggesting extreme pollution. Source analysis indicated that most of the collected RD10 had greater than half of its mass originating from the mine. To assess the risk presented by inhalation exposure to local populations, we built a method using Gaussian diffusion model and two exposure scenarios for both adults and children were considered. The level of simulated particle concentrations was comparable to that described in the literature; the inhalation of potential toxic elements (PTEs) in RD10 led to health risks for both adults and children (adult and child HI > 1, with adults CR in industrial areas >10−4). Results also indicated that a ten-fold reduction of silt load resulted in a >4-fold decrease in risk. Collectively, the results suggest that fine road dust is a potential hotspot for mineral exposure in populations living around a mine and its tailings; moreover, that effective prevention measures like road cleaning and truck regulation are urgently needed.

Thermal conductivity of single-layer MoS2(1−x)Se2x alloys from molecular dynamics simulations with a machine-learning-based interatomic potential

Single-layer transition metal dichalcogenides (TMDs) and their alloys have attracted intensive attention due to their potential in optoelectronics and energy conversion. Understanding the thermal transport in these two-dimensional materials is crucial for designing reliable devices where these materials are integrated. Molecular dynamics simulation is a commonly employed approach to investigate phonon transport and thermal conductivity in solids, but interatomic potentials that could satisfactorily characterize the phonon properties of multiple TMDs simultaneously are not available at present. In this paper, a machine-learning-driven interatomic potential for MoS2-MoSe2 system based on the spectral neighbor analysis approach is parameterized by learning from a large amount of data generated from first-principles. The phonon dispersion and mode-specific Gruneisen parameters of MoS2 and MoSe2, as well as the phonon dispersion of the MoS2-MoSe2 superlattice, obtained from first-principles are well reproduced by the potential parameterized. By performing equilibrium molecular dynamics simulations, the lattice thermal conductivity of MoS2(1−x)Se2x alloys are calculated and a ten-fold reduction compared with MoS2 is found when x = 50%. Moreover, the roles of mass disorder and force-field disorder on the low thermal conductivity is identified. The parameterized interatomic potential could be utilized to study phonon transport in other MoS2-MoSe2 nanostructures.

Analysis of the pathogenic I326T variant of human tRNA nucleotidyltransferase reveals reduced catalytic activity and thermal stability in vitro linked to a conformational change

The I326T mutation in the TRNT1 gene encoding human tRNA nucleotidyltransferase (tRNA-NT) is linked to a relatively mild form of SIFD. Previous work indicated that the I326T variant was unable to incorporate AMP into tRNAs in vitro, however, expression of the mutant allele from a strong heterologous promoter supported in vivo CCA addition to both cytosolic and mitochondrial tRNAs in a yeast strain lacking tRNA-NT. To address this discrepancy, we determined the biochemical and biophysical characteristics of the I326T variant enzyme and the related variant, I326A. Our in vitro analysis revealed that the I326T substitution decreases the thermal stability of the enzyme and causes a ten-fold reduction in enzyme activity. We propose that the structural changes in the I326T variant that lead to these altered parameters result from a rearrangement of helices within the body domain of the protein which can be probed by the inability of the monomeric enzyme to form a covalent dimer in vitro mediated by C373. In addition, we confirm that the effects of the I326T or I326A substitutions are relatively mild in vivo by demonstrating that the mutant alleles support both mitochondrial and cytosolic CCA-addition in yeast.

Impacts of aerosol nuclei on amine emissions

Amine emissions are an environmental and economic concern for CO2 capture by amine scrubbing. Aerosol nuclei, including hydrolyzed SO3 and fly ash, can lead to amine aerosol emissions. Aerosol grows by collecting water and amine while passing through the absorber column; current mitigation techniques are ineffective at capturing the aerosol prior to atmospheric release. This work measures the varying impacts of aerosol nuclei on amine emissions at multiple pilot plants. Aerosol emissions were quantified by the use of Fourier Transform Infrared Spectrometry (FTIR). MEA emissions were measured in the Slipstream Solvent Test Unit (SSTU) at the National Carbon Capture Center (NCCC). The effect of baghouse pretreatment of the inlet flue gas on the aerosol emissions was observed by FTIR and Phase Doppler Interferometry (PDI); these tests were performed before and after the installation of a pulsed-jet baghouse designed for flue gas mercury control. The baghouse resulted in a ten-fold reduction of amine aerosol emissions, due to the collection of SO3 aerosol nuclei, probably on injected Ca(OH)2. This emissions reduction was due to a decrease in the inlet SO3 content from a max of 9 ppm to 0.5 ppm. FTIR sampling was used to quantify this emissions reduction. PDI analysis confirmed the absence of aerosol at diameters greater than 0.1 μm. Aerosol generation was performed through the injection of sulfur trioxide into the process inlet at the University of Texas Separations Research Program (UT-SRP) Pilot Plant. SO3 was generated by the oxidation of sulfur dioxide in air over a heated vanadium pentoxide catalyst bed. The 8% SO2/Air mix was fed at flow rates up to 6 liters per minute, and resulted in up to 110 ppm of SO3 at the absorber inlet. The generator converted an average of 94 % SO2 into SO3, with production rates up to 1.7 grams per minute of SO3. The injected aerosol was allowed to grow within the absorber and water wash. SO3 was found to increase PZ emissions by up to 7.6 mol PZ per mol SO3. Increasing inlet SO3 correlated with increasing PZ emissions.

A sandwich duplex immuno PCR for rapid and sensitive identification of Clostridium perfringens alpha and enterotoxin

The prevalence and lethality associated with C. perfringens alpha (CPA) and enterotoxin (CPE) toxaemia necessitate the need for rapid and definitive detection systems to initiate management measures. In the present study, a sandwich duplex immuno-capture PCR (SD-IPCR) was developed by employing IgY antibodies against a bivalent protein r-Cpae derived from CPA and CPE for antigen capture and reporter antibodies against truncated CPA or CPE conjugated to oligomers of distinguishable size for antigen revealing and signal amplification. The avian immunoglobulin's (IgY) were devoid of reactivity with S. aureus protein A (SpA), a commensal that often co-exists with C. perfringens. The assay was specific, had a detection limit (LOD) of 1 pg/ml for both CPA and CPE in PBS and improved the LOD by 104 folds compared to an analogous sandwich ELISA with same set of antibodies. In spiking studies, a ten-fold reduction in LOD was observed in case of intestinal tissue samples (10 pg/ml) however, no change in LOD was observed when SD-IPCR was applied on to faecal, serum or muscle tissue samples. Of the 136 natural samples examined, the SD-IPCR could detect CPA and CPE in 29.4% and 35.3% samples, while the sandwich ELISAs could detect the same in 25.7% and 25% samples respectively owing to the relatively lesser sensitivity. The LOD and specificity of the SD-IPCR demonstrates its applicability as an efficient and rapid platform for direct detection CPA and CPE from diverse samples matrices in clinical microbiological and meat testing laboratories.

New direction for NPD

New direction for NPD

Automated localization and quality control of the aorta in cine CMR can significantly accelerate processing of the UK Biobank population data.

IntroductionAortic distensibility can be calculated using semi-automated methods to segment the aortic lumen on cine CMR (Cardiovascular Magnetic Resonance) images. However, these methods require visual quality control and manual localization of the region of interest (ROI) of ascending (AA) and proximal descending (PDA) aorta, which limit the analysis in large-scale population-based studies. Using 5100 scans from UK Biobank, this study sought to develop and validate a fully automated method to 1) detect and locate the ROIs of AA and PDA, and 2) provide a quality control mechanism.MethodsThe automated AA and PDA detection-localization algorithm followed these steps: 1) foreground segmentation; 2) detection of candidate ROIs by Circular Hough Transform (CHT); 3) spatial, histogram and shape feature extraction for candidate ROIs; 4) AA and PDA detection using Random Forest (RF); 5) quality control based on RF detection probability. To provide the ground truth, overall image quality (IQ = 0–3 from poor to good) and aortic locations were visually assessed by 13 observers. The automated algorithm was trained on 1200 scans and Dice Similarity Coefficient (DSC) was used to calculate the agreement between ground truth and automatically detected ROIs.ResultsThe automated algorithm was tested on 3900 scans. Detection accuracy was 99.4% for AA and 99.8% for PDA. Aorta localization showed excellent agreement with the ground truth, with DSC ≥ 0.9 in 94.8% of AA (DSC = 0.97 ± 0.04) and 99.5% of PDA cases (DSC = 0.98 ± 0.03). AA×PDA detection probabilities could discriminate scans with IQ ≥ 1 from those severely corrupted by artefacts (AUC = 90.6%). If scans with detection probability < 0.75 were excluded (350 scans), the algorithm was able to correctly detect and localize AA and PDA in all the remaining 3550 scans (100% accuracy).ConclusionThe proposed method for automated AA and PDA localization was extremely accurate and the automatically derived detection probabilities provided a robust mechanism to detect low quality scans for further human review. Applying the proposed localization and quality control techniques promises at least a ten-fold reduction in human involvement without sacrificing any accuracy.

Investigation of a KcsA Cytoplasmic pH Gate in Lipoprotein Nanodiscs.

The bacterial potassium channel KcsA is gated by pH, opening for conduction under acidic conditions. Molecular determinants responsible for this effect have been identified at the extracellular selectivity filter, at the membrane-cytoplasm interface (TM2 gate), and in the cytoplasmic C-terminal domain (CTD), an amphiphilic four-helix bundle mediated by hydrophobic and electrostatic interactions. Here we have employed NMR and EPR to provide a structural view of the pH-induced open-to-closed CTD transition. KcsA was embedded in lipoprotein nanodiscs (LPNs), selectively methyl-protonated at Leu/Val residues to allow observation of both states by NMR, and spin-labeled for the purposes of EPR studies. We observed a pHinduced structural change between an associated structured CTD at neutral pH and a dissociated flexible CTD at acidic pH, with a transition in the 5.0-5.5 range, consistent with a stabilization of the CTD by channel architecture. A double mutant constitutively open at the TM2 gate exhibited reduced stability of associated CTD, as indicated by weaker spin-spin interactions, a shift to higher transition pH values, and a tenfold reduction in the population of the associated "closed" channels. We extended these findings for isolated CTD-derived peptides to full-length KcsA and have established a contribution of the CTD to KcsA pH-controlled gating, which exhibits a strong correlation with the state of the proximal TM2 gate.

Enhanced removal of Mn (II) from solution by thermally activated Bayer precipitates

This study assessed the ability of thermally activated Bayer precipitates (Bppt) for manganese remediation from acidic solutions, focusing on their application in acid mine drainage water. The Bayer precipitates were formed from the addition of seawater to Bayer liquor residues, and were primarily composed of hydrotalcite and calcium carbonate. Thermal activation of these materials at 320, 380 and 440 °C showed a reduction in Bayer hydrotalcite crystallinity and increased surface area due to the decarbonation and dehydroxylation of the mixed metal hydroxide layers in Bayer hydrotalcite. At higher thermal activation temperatures (380 and 440 °C), partial decarbonation of calcium carbonate were suspected of forming calcium oxide, which aided the neutralisation process. The removal capacities for manganese were found to increase with thermal activation temperature, which corresponded with increased maximum pH (pH > 10 for 380 and 440 °C heated sample). Treatment of acidic solutions with Bayer precipitates simultaneously removed manganese and aluminium, which is not achievable in lime neutralisation technologies currently used in acid mine drainage treatment. The optimum thermal activation temperature was found to be 380 °C, showing high manganese removal performance and a ten-fold reduction in material mass required when compared to Bayer precipitate. Removal mechanisms of manganese were found to be a combination of hydrotalcite reformation (determined by X-ray photoelectron spectroscopy, X-ray diffraction and infrared spectroscopy), surface precipitation and surface complexation, as well as the formation of hausmannite and rhodochrosite.

Highly-porous diatom biosilica stationary phase for thin-layer chromatography

This study showed that a nanostructured, highly-porous stationary phase composed of randomly-deposited biosilica frustules isolated from living cells of diatom Pinnularia sp. significantly improved the conventional thin-layer chromatography (TLC) based separation of the triphenylmethane dyes malachite green and fast green relative to silica gel by two mobile phases (9:1:1 v/v 1-butanol:ethanol:water, 5:1:2 v/v 1-butanol:acetic acid:water). Although both stationary phases were composed of amorphous silica rich in silanol groups with particle size of 10–12 μm, diatom biosilica frustules were highly porous, hollow shells with surface structure dominated by 200 nm pore arrays. Diatom biosilica significantly improved the mobility of both malachite green and fast green, enabling the resolution of these analytes. The diatom biosilica layer had a high void fraction of 96% but reduced the flow velocity and permeability constant by a factor of two relative to silica gel. TLC performance was enhanced, as evidenced by ten-fold reduction in theoretical plate height for both analytes using the 1-butanol:acetic acid:water mobile phase, and an increased difference in retention time between malachite green and fast green (ΔRf = 0.26) using the 1-butanol:ethanol:water mobile phase. Analysis of plate height vs. solvent front position by the modified van Deemter equation suggested that dispersive mass transfer was reduced, leading to improved analyte resolution, and that surface of the frustule decreased boundary layer resistance, leading to increased analyte flux. Overall, the basis for improved chromatographic performance is believed to be the unique nano- and microstructure of the diatom biosilica frustule.

Automated Region Extraction from Thermal Images for Peripheral Vascular Disease Monitoring.

This work develops a method for automatically extracting temperature data from prespecified anatomical regions of interest from thermal images of human hands, feet, and shins for the monitoring of peripheral arterial disease in diabetic patients. Binarisation, morphological operations, and geometric transformations are applied in cascade to automatically extract the required data from 44 predefined regions of interest. The implemented algorithms for region extraction were tested on data from 395 participants. A correct extraction in around 90% of the images was achieved. The process of automatically extracting 44 regions of interest was performed in a total computation time of approximately 1 minute, a substantial improvement over 10 minutes it took for a corresponding manual extraction of the regions by a trained individual. Interrater reliability tests showed that the automatically extracted ROIs are similar to those extracted by humans with minimal temperature difference. This set of algorithms provides a sufficiently accurate and reliable method for temperature extraction from thermal images at par with human raters with a tenfold reduction in time requirement. The automated process may replace the manual human extraction, leading to a faster process, making it feasible to carry out large-scale studies and to increase the regions of interest with minimal cost. The code for the developed algorithms, to extract the 44 ROIs from thermal images of hands, feet, and shins, has been made available online in the form of MATLAB functions and can be accessed from http://www.um.edu.mt/cbc/tipmid.