The “independent burning theory” is generally adopted in arson cases involving buildings, and the crime is considered complete when a part of the building has burned continuously. On the other hand, this is a theory within the field of jurisprudence and is not based on a scientific definition. In this study, we focused on flooring materials as burned building materials in arson cases, and conducted cone calorimeter tests on four types of wooden floorboards to investigate their ignition characteristics and burning rate. We also observed the interior of the floorboards burned by heat flux using an X-ray computed tomography (CT) system. When gasoline was spilled on the floor, the floorboards were ignited by the gasoline flame, and the maximum burning rate was found to be 1.25 to 3.26 mm per minute. From the results of cone calorimeter tests and gasoline burning experiments in a real-scale building, we predicted the maximum possible burn damage depth to floorboards caused by the thermal effects of a gasoline flame in an arson with gasoline. Based on the experimental results, we proposed a method to prove independent burning through the observation of floorboard burnout. Burn damages of the floorboards collected from locations where no continued burning after gasoline burnout was observed in the real-scale burning experiments were limited to the surface layer, below the maximum possible burn damage depth in all cases. On the other hand, the burn damage of some of floorboard sampled from locations where continued combustion was observed independent of the gasoline flame in the combustion experiments exceeded the depth. Therefore, it was validated that it is possible to determine whether the flooring burned independently of the gasoline flame by X-ray CT observation of the burn depth of the floorboard after the fire. The proposed method in this study can contribute to establishing independent combustion of a part of a building during arson using liquid fuel.

Like blood and semen, saliva is considered an important evidence in criminal investigations. Saliva identification has been performed by detecting α-amylase activity using the Blue Starch method or by detecting salivary α-amylase with the RSID^TM-Saliva. However, the Blue Starch method has low specificity, whereas the RSID^TM-Saliva test is costly. Therefore, there is a need for a new saliva identification method that solves these problems. Currently, an α-amylase isozyme kit “Determiner L P-AMY G2” is widely used as a diagnostic reagent and it can specifically detect non-salivary-type α-amylase activity. Since α-amylase activity in saliva is derived from salivary-type α-amylase, it was hypothesized that saliva could be identified by calculating the ratio of salivary-type α-amylase activity to total α-amylase activity (RS value). As a result, saliva and other body fluids (semen, vaginal fluid, urine, and blood) could be distinguished using an RS value of 0.950 as a reference. This method was able to detect saliva even when diluted 10,000-fold and could identify saliva in mixtures with seminal fluid or vaginal fluid. Therefore, this method detects salivary α-amylase with higher sensitivity than existing methods and is considered to be a potential novel saliva identification technique with practical applications.

We developed a data analysis method for non-target liquid chromatography–tandem mass spectrometry (LC-MS/MS) drug analysis by combining software and databases available online. Blood and urine samples from deceased persons were analyzed using LC-MS/MS in data-dependent acquisition mode. Full-scan data were extracted and output as a two-dimensional (2D) plot (x-axis: retention time; y-axis: m/z value) using the data analysis software MZmine3. Multiple 2D plots were overlaid using image processing software, and distinct peaks unique to the sample of interest were selected. The MS/MS spectra of these distinct peaks were matched against databases using the MS-DIAL software. The databases used for matching included publicly available resources, as well as a compilation of MS/MS spectra of substances relevant to forensic toxicology. The analysis led to the detection of unexpected drugs. To enhance the effectiveness of database matching, it will be crucial to improve the database by sharing MS/MS spectra among drug-testing institutions.

Recently, the importance of vehicle speed analysis from video images in traffic accidents and incidents has been increasing, and with the development of camera technology, there is an urgent need to improve image analysis technology. Among the influencing factors, the complexity of the frame rate due to digitization of video signals, and the time difference of imaging within the same frame due to the rolling shutter method of CMOS cameras are thought to influence the accuracy of vehicle speed analysis.

Therefore, we developed a software that can automatically read frame rates down to 1 ms by analyzing video images of a device (Time Counter) with a stopwatch function using LEDs. This software automatically read frame rates by cropping the frames, correcting lens distortion, generating orthogonal images through homographic transformation, and binarization of the images, then reading the coordinates of the lit LED points. Next, we developed a scanning time measurement device. This is a device that blinks an LED tape light at an arbitrary frequency. When this device is shot by a CMOS camera with rolling shutter method, the LED tape light is imaged in stripe pattern. The scanning speed can be measured by measuring the width of the stripe.

Moreover, we proposed a vehicle speed analysis method that takes scanning time into account, and conducted physical experiments to confirm its effectiveness．As a result, the proposed method achieved an error of ± 0.1 km/h, while the conventional method showed an error ranging from ‒1.48 km/h to +1.46 km/h. The proposed method improved the accuracy of vehicle speed analysis.