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Protons of tens of keV can be resonantly scattered by electromagnetic ion cyclotron (EMIC) waves excited in the magnetosphere, resulting in proton precipitation down to the upper atmosphere. In this study, we report for the first time the ionospheric height-dependent ionization in response to EMIC-associated isolated proton aurora (IPA) using simultaneous space-borne and ground-based measurements. On 06 March 2019, the Polar Orbiting Environmental Satellites observed significant proton precipitation in the dusk sector (MLT ∼ 19), while ground-based magnetometers detected a clear signature of EMIC waves. Meanwhile, the conjugated all sky imager captured an IPA and the nearby Poker Flat incoherent scatter radar (PFISR) showed enhanced electron density in the E region, suggesting a potential consequence of the EMIC wave-driven proton precipitation. The Global Airglow model simulations confirmed the dominant impact of proton precipitation on the ionosphere and agreed well with PFISR observations. This study confirmed physical links from the magnetosphere to the ionosphere through EMIC-driven proton precipitation.

The characteristic impedance of a rock is defined as the product of the sonic velocity and the density of the rock. Based on previous studies, this article finds that: (1) For an intact rock, its characteristic impedance is a comprehensive physical property, since it is closely related with strengths, fracture toughness, Young’s modulus, and Poisson’s ratio. (2) For rock masses, their characteristic impedances either increase markedly or slightly with increasing depth. (3) The bursts of intact rocks in laboratory are dependent on their characteristic impedances to a great extent, and strong rock bursts happen mostly in the rocks with large characteristic impedance. (4) Rock burst occurrence in tunnel and mines has a close relation with the characteristic impedances of the rocks. (5) Laboratory experiments on different rock samples show that seismic velocity increases as applied stress rises, and field monitored results from coal mines indicate that in the areas where rock bursts happened, the seismic velocity was increasing markedly before or during the bursts. (7) Drillability of rock depends on the characteristic impedance of the rock and the rock with larger impedance has lower drillability or lower penetration rate. (8) The potential applications of characteristic impedance include evaluation and classification of rock masses, and prediction of rock burst proneness and drillability.

Aiming at the difficulties of the health status recognition of yellow feather broilers in large-scale broiler farms and the low recognition rate of current models, a novel method based on machine vision to achieve precise tracking of multiple broilers was proposed in this paper. Broilers’ behavior in the breeding environment can be tracked to analyze their behaviors and health status further. An improved YOLOv3 (You Only Look Once v3) algorithm was used as the detector of the Deep SORT (Simple Online and Realtime Tracking) algorithm to realize the multiple object tracking of yellow feather broilers in the flat breeding chamber, which replaced the backbone of YOLOv3 with MobileNetV2 to improve the inference speed of the detection module. The DRSN (Deep Residual Shrinkage Network) was integrated with MobileNetV2 to enhance the feature extraction capability of the network. Moreover, in view of the slight change in the individual size of the yellow feather broiler, the feature fusion network was also redesigned by combining it with the attention mechanism to enable the adaptive learning of the objects’ multi-scale features. Compared with traditional YOLOv3, improved YOLOv3 achieves 93.2% mAP (mean Average Precision) and 29 fps (frames per second), representing high-precision real-time detection performance. Furthermore, while the MOTA (Multiple Object Tracking Accuracy) increases from 51% to 54%, the IDSW (Identity Switch) decreases by 62.2% compared with traditional YOLOv3-based objective detectors. The proposed algorithm can provide a technical reference for analyzing the behavioral perception and health status of broilers in the flat breeding environment.

Autoimmune diseases are often treated by glucocorticoids and immunosuppressive drugs that could increase the risk for infection, which in turn deteriorate disease and cause mortality. Low-dose IL-2 (Ld-IL2) therapy emerges as a new treatment for a wide range of autoimmune diseases. To examine its influence on infection, we retrospectively studied 665 patients with systemic lupus erythematosus (SLE) including about one third receiving Ld-IL2 therapy, where Ld-IL2 therapy was found beneficial in reducing the incidence of infections. In line with this clinical observation, IL-2 treatment accelerated viral clearance in mice infected with influenza A virus or lymphocytic choriomeningitis virus (LCMV). Noticeably, despite enhancing anti-viral immunity in LCMV infection, IL-2 treatment exacerbated CD8+ T cell-mediated immunopathology. In summary, Ld-IL2 therapy reduced the risk of infections in SLE patients and enhanced the control of viral infection, but caution should be taken to avoid potential CD8+ T cell-mediated immunopathology.

Background Three-dimensional (3D) chromatin organization provides a critical foundation to investigate gene expression regulation and cellular homeostasis. Results Here, we present the first 3D genome architecture maps in wild type and mutant allotetraploid peanut lines, which illustrate A/B compartments, topologically associated domains (TADs), and widespread chromatin interactions. Most peanut chromosomal arms (52.3%) have active regions (A compartments) with relatively high gene density and high transcriptional levels. About 2.0% of chromosomal regions switch from inactive to active (B-to-A) in the mutant line, harboring 58 differentially expressed genes enriched in flavonoid biosynthesis and circadian rhythm functions. The mutant peanut line shows a higher number of genome-wide cis-interactions than its wild-type. The present study reveals a new TAD in the mutant line that generates different chromatin loops and harbors a specific upstream AP2EREBP-binding motif which might upregulate the expression of the GA2ox gene and decrease active gibberellin (GA) content, presumably making the mutant plant dwarf. Conclusions Our findings will shed new light on the relationship between 3D chromatin architecture and transcriptional regulation in plants.

To investigate energy dissipation and particle size distribution of rock under dynamic loads, a series of dynamic compression tests of granite specimens were conducted using a conventional split-Hopkinson pressure bar (SHPB) device with a high-speed camera. The experimental results show that the dissipated energy increases linearly with an increasing incident energy, following two different inclined paths connected by a critical incident energy, and the linear energy dissipation law in the dynamic compression test has been confirmed. This critical incident energy was found to be 0.29–0.33 MJ/m³. As the incident energy was smaller than the critical incident energy, the rock specimens remained unruptured after the impact. When the incident energy was greater than the critical incident energy, the rock specimens were ruptured or fragmented after the impact. In addition, the experimental results indicate that the dissipated energy and energy consumption ratio of a rock specimen, either unruptured or fragmented, increase with an increasing strain rate. Furthermore, it was found that fragment sizes at each mesh decrease with an increasing incident energy; that is, fragmentation becomes finer as incident energy increases.

Aims: We investigated which serum amino-terminal pro-B-type-natriuretic peptide (NT-proBNP) levels inform heart failure (HF) risk in a community-based population at increased cardiovascular disease (CVD) risk. Methods and results: Inclusion criteria were age = 60 years with one or more of self-reported hypertension, diabetes, heart disease, abnormal heart rhythm, cerebrovascular disease, or renal impairment. Exclusion criteria were known HF, ejection fraction (EF) < 50%, or more than mild valve abnormality. NT-proBNP levels were measured in 3842 participants on enrolment. HF was diagnosed in 162 participants at a median of 4.5 (interquartile range 2.7–5.4) years after enrolment, 73 with HF with preserved EF (HFpEF), 53 with HF with reduced EF (HFrEF), and 36 with valvular HF (VHF). Areas under the receiver operating characteristic curve (AUC) for 5-year prediction of total HF were similar for NT-proBNP alone (0.79, 95% confidence interval 0.74–0.83) and a 7-parameter multivariable model (0.82, 0.77–0.86, P = 0.035). NT-proBNP cut-points of 11, 16, and 25 pmol/L for individuals aged 60–69, 70–79, and = 80 years, respectively, achieved sensitivities > 76% and specificities of 47–69% for 5-year prediction of total HF in men and women in all three age groups. Sensitivities were = 75% in most subgroups according to body mass index, estimated glomerular filtration rate, and the presence or absence of atrial fibrillation, pacemaker, or CVD, and for the prediction of HFpEF, HFrEF and VHF. Conclusion: Age-specific serum NT-proBNP levels inform prognosis, and hence therapeutic decisions, regarding HF risk in individuals at increased CVD risk.

Background: The lack of effective therapies for heart failure with preserved ejection fraction (HFpEF) reflects an incomplete understanding of its pathogenesis. Design: We analysed baseline risk factors for incident HFpEF, heart failure with reduced ejection fraction (HFrEF) and valvular heart failure (VHF) in a community-based cohort. Methods: We recruited 2101 men and 1746 women =60 years of age with hypertension, diabetes, ischaemic heart disease (IHD), abnormal heart rhythm, cerebrovascular disease or renal impairment. Exclusion criteria were known heart failure, left ventricular ejection fraction <50% or valve abnormality >mild in severity. Median follow-up was 5.6 (IQR 4.6-6.3) years. Results: Median time to heart failure diagnosis in 162 participants was 4.5 (IQR 2.7-5.4) years, 73 with HFpEF, 53 with HFrEF and 36 with VHF. Baseline age and amino-terminal pro-B-type natriuretic peptide levels were associated with HFpEF, HFrEF and VHF. Pulse pressure, IHD, waist circumference, obstructive sleep apnoea and pacemaker were associated with HFpEF and HFrEF; atrial fibrillation (AF) and warfarin therapy were associated with HFpEF and VHF and peripheral vascular disease and low platelet count were associated with HFrEF and VHF. Additional risk factors for HFpEF were body mass index (BMI), hypertension, diabetes, renal dysfunction, low haemoglobin, white cell count and ß-blocker, statin, loop diuretic, non-steroidal anti-inflammatory and clopidogrel therapies, for HFrEF were male gender and cigarette smoking and for VHF were low diastolic blood pressure and alcohol intake. BMI, diabetes, low haemoglobin, white cell count and warfarin therapy were more strongly associated with HFpEF than HFrEF, whereas male gender and low platelet count were more strongly associated with HFrEF than HFpEF. Conclusions: Our data suggest a major role for BMI, hypertension, diabetes, renal dysfunction, and inflammation in HFpEF pathogenesis; strategies directed to prevention of these risk

Background: Effective management of cardiovascular and chronic kidney disease risk factors offers longer, healthier lives and savings in healthcare. Aim: To examine risk factor management in participants of the SCReening Evaluation of the Evolution of New Heart Failure study, a self-selected population at increased cardiovascular disease risk recruited from members of a health insurance fund in Melbourne and Shepparton, Australia. Methods: Inclusion criteria were age = 60 years with one or more self-reported ischaemic or other heart diseases, irregular or rapid heart rhythm, cerebrovascular disease, renal impairment or treatment for hypertension or diabetes for =2 years. Exclusion criteria were known heart failure or cardiac abnormality on echocardiography or other imaging. Medical history, clinical examination, full blood examination and biochemistry (without lipids and glycated haemoglobin (HbA1c)) were performed for 3847 participants on enrolment, and blood pressure, lipids and HbA1c were measured 1–2 years after enrolment for 3203 participants. Results: Despite 99% of 3294 participants with hypertension receiving antihypertensive medication, half had blood pressures >140/90 mmHg. Approximately 77% of participants were overweight or obese, with one third being obese. Additionally, 74% of participants at high cardiovascular disease risk had low-density lipoprotein cholesterol levels =2 mmol/L, one third of diabetic participants had HbA1c >7%, 22% had an estimated glomerular filtration rate < 60 mL/min/1.73m2, and substantial proportions had under-utilisation of antiplatelet therapy and anticoagulation for atrial fibrillation and were physically inactive. Conclusions: This population demonstrated substantial potential to reduce cardiovascular and renal morbidity and mortality and healthcare costs through more effective management of modifiable risk factors.

The undesired uncertainties in circuit performance can lead to analog/mixed-signal circuit failures and yield loss at nanoscale. As such, it has become extremely critical for high precision analog/RF circuits such as phase-locked loop (PLL) and custom/mixed-signal circuits such as SRAM arrays, which both have tight operating margin due to lower power supply and higher operating frequency. Many performance-domain techniques have become available in past few decades: the Monte Carlo (MC) method repeatedly draws samples, runs simulations, and evaluates the yield rate, which can be easily applied to high-dimensional problems. However, it is extremely time consuming. IS can reduce the number of samples required to achieve a desired accuracy, especially in the case where the failure region is small for rare failure events. However, it is always challenging to obtain an optimal sampling distribution or shift vector efficiently.

The undesired uncertainties in circuit performance can lead to analog/mixed-signal circuit failures and yield loss at nanoscale. As such, it has become extremely critical for high precision analog/RF circuits such as phase-locked loop (PLL) and custom/mixed-signal circuits such as SRAM arrays, which both have tight operating margin due to lower power supply and higher operating frequency. Many performance-domain techniques have become available in past few decades: the Monte Carlo (MC) method repeatedly draws samples, runs simulations, and evaluates the yield rate, which can be easily applied to high-dimensional problems. However, it is extremely time consuming. IS can reduce the number of samples required to achieve a desired accuracy, especially in the case where the failure region is small for rare failure events. However, it is always challenging to obtain an optimal sampling distribution or shift vector efficiently.

Majority of practical multivariate statistical analysis and optimizations model interdependence among random variables in terms of the linear correlation. Though linear correlation is simple to use and evaluate, in several cases non-linear dependence between random variables may be too strong to ignore. In this paper, we propose polynomial correlation coefficients as simple measure of multi-variable non-linear dependence and show that the need for modeling non-linear dependence strongly depends on the end function that is to be evaluated from the random variables. Then, we calculate the errors in estimation resulting from assuming independence of components generated by linear de-correlation techniques, such as PCA and ICA. The experimental results show that the error predicted by our method is within 1% error compared to the real simulation of statistical timing and leakage analysis. In order to deal with non-linear dependence, we further develop a target-function-driven component analysis algorithm (FCA) to minimize the error caused by ignoring high order dependence. We apply FCA to statistical leakage power analysis and SRAM cell noise margin variation analysis. Experimental results show that the proposed FCA method is more accurate compared to the traditional PCA or ICA.

Majority of practical multivariate statistical analysis and optimizations model interdependence among random variables in terms of the linear correlation. Though linear correlation is simple to use and evaluate, in several cases non-linear dependence between random variables may be too strong to ignore. In this paper, we propose polynomial correlation coefficients as simple measure of multi-variable non-linear dependence and show that the need for modeling non-linear dependence strongly depends on the end function that is to be evaluated from the random variables. Then, we calculate the errors in estimation resulting from assuming independence of components generated by linear de-correlation techniques, such as PCA and ICA. The experimental results show that the error predicted by our method is within 1% error compared to the real simulation of statistical timing and leakage analysis. In order to deal with non-linear dependence, we further develop a target-function-driven component analysis algorithm (FCA) to minimize the error caused by ignoring high order dependence. We apply FCA to statistical leakage power analysis and SRAM cell noise margin variation analysis. Experimental results show that the proposed FCA method is more accurate compared to the traditional PCA or ICA. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Majority of practical multivariate statistical analysis and optimizations model interdependence among random variables in terms of the linear correlation. Though linear correlation is simple to use and evaluate, in several cases non-linear dependence between random variables may be too strong to ignore. In this paper, we propose polynomial correlation coefficients as simple measure of multi-variable non-linear dependence and show that the need for modeling non-linear dependence strongly depends on the end function that is to be evaluated from the random variables. Then, we calculate the errors in estimation resulting from assuming independence of components generated by linear de-correlation techniques, such as PCA and ICA. The experimental results show that the error predicted by our method is within 1% error compared to the real simulation of statistical timing and leakage analysis. In order to deal with non-linear dependence, we further develop a target-function-driven component analysis algorithm (FCA) to minimize the error caused by ignoring high order dependence. We apply FCA to statistical leakage power analysis and SRAM cell noise margin variation analysis. Experimental results show that the proposed FCA method is more accurate compared to the traditional PCA or ICA. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Majority of practical multivariate statistical analysis and optimizations model interdependence among random variables in terms of the linear correlation. Though linear correlation is simple to use and evaluate, in several cases non-linear dependence between random variables may be too strong to ignore. In this paper, we propose polynomial correlation coefficients as simple measure of multi-variable non-linear dependence and show that the need for modeling non-linear dependence strongly depends on the end function that is to be evaluated from the random variables. Then, we calculate the errors in estimation resulting from assuming independence of components generated by linear de-correlation techniques, such as PCA and ICA. The experimental results show that the error predicted by our method is within 1% error compared to the real simulation of statistical timing and leakage analysis. In order to deal with non-linear dependence, we further develop a target-function-driven component analysis algorithm (FCA) to minimize the error caused by ignoring high order dependence. We apply FCA to statistical leakage power analysis and SRAM cell noise margin variation analysis. Experimental results show that the proposed FCA method is more accurate compared to the traditional PCA or ICA.

Open joints have significantly different effects on stress wave propagation across them as compared to closed and filled joints. In the present study, a theoretical model is developed based on the analysis of interaction process between stress waves and a single open joint. The analytical solutions to the energy transmission coefficient are mathematically derived for stress waves across an open joint. Parametric studies are conducted to evaluate the effects of various parameters on the energy transmission coefficient. It is found that the energy transmission coefficient follows a similar trend for all types of stress waves, but stress waves with different waveforms have different values. The energy transmission coefficient increases with the increase in the wave amplitude and duration, but decreases with the gap width. It also increases at the outset, and then decreases gradually with the increase in the incident angle for rectangle, symmetric triangle and ascending triangle waves, but it decreases with the incident angle for sine and descending triangle waves. Furthermore, different-shaped stress waves have different critical gap widths for wave transmission. The optimal incident angle and the critical gap width increase as the wave duration increases, but the critical stress amplitude decreases.

The Thirteenth East Asia-Pacific Conference on Structural Engineering and Construction (EASEC-13), September 11-13, 2013, Sapporo, Japan.

The vacuolar H(+)-ATPase (V-ATPase) is a major contributor to luminal acidification in epithelia of Wolffian duct origin. In both kidney-intercalated cells and epididymal clear cells, cAMP induces V-ATPase apical membrane accumulation, which is linked to proton secretion. We have shown previously that the A subunit in the cytoplasmic V(1) sector of the V-ATPase is phosphorylated by protein kinase A (PKA). Here we have identified by mass spectrometry and mutagenesis that Ser-175 is the major PKA phosphorylation site in the A subunit. Overexpression in HEK-293T cells of either a wild-type (WT) or phosphomimic Ser-175 to Asp (S175D) A subunit mutant caused increased acidification of HCO(3)(-)-containing culture medium compared with cells expressing vector alone or a PKA phosphorylation-deficient Ser-175 to Ala (S175A) mutant. Moreover, localization of the S175A A subunit mutant expressed in HEK-293T cells was more diffusely cytosolic than that of WT or S175D A subunit. Acute V-ATPase-mediated, bafilomycin-sensitive H(+) secretion was up-regulated by a specific PKA activator in HEK-293T cells expressing WT A subunit in HCO(3)(-)-free buffer. In cells expressing the S175D mutant, V-ATPase activity at the membrane was constitutively up-regulated and unresponsive to PKA activators, whereas cells expressing the S175A mutant had decreased V-ATPase activity that was unresponsive to PKA activation. Finally, Ser-175 was necessary for PKA-stimulated apical accumulation of the V-ATPase in a polarized rabbit cell line of collecting duct A-type intercalated cell characteristics (Clone C). In summary, these results indicate a novel mechanism for the regulation of V-ATPase localization and activity in kidney cells via direct PKA-dependent phosphorylation of the A subunit at Ser-175.

Substantial concentrations of trace gases and aerosols are lofted and carried from Asia over the Pacific producing an inter-hemispheric impact on atmospheric chemistry and climate. The meteorological mechanism leading to this large-scale transport of dust and pollutants remains a major uncertainty in quantifying the global effects of emissions from the developing world. Models and downwind measurements have identified isentropic advection associated with wave cyclones (warm conveyor belt circulation) as an important mechanism. We present data from a case study conducted over Shenyang in NE China as part of EAST-AIRE in April 2005 in which upstream convection, rather than WCB lofting appears to dominate. Observations from instrumented aircraft flights, back trajectories, and satellite images of clouds (GOES) and aerosols (MODIS) are analyzed. In this heavily industrialized and populated region, the warm-sector PBL air ahead of a cold front was highly polluted. In the free troposphere, between ~1000 and 4000 m altitude, concentrations of trace gases and aerosols were lower, but well above background; we measured ~70 ppb O3, ~300 ppb CO, ~2 ppb SO2, and ~ 8x10-5 m-1 aerosol scattering. These observations show that dry (non-precipitating) convection can be an important mechanism for converting local air pollution problems into regional or global atmospheric chemistry problems. Climatological data indicate that spring (MAM) precipitation over NE China is low, about 90 mm compared to 290 mm over the NE US. Cloud cover, however, is similar with cumulus clouds reported about 7% of the time over NE China and about 9% of the time over the NE US suggesting that lofting in dry convective events may be common over NE Asia. Evaluation of models’ convective schemes and further observations near the source regions are called for.

Measures relating word frequencies and expectations have been constantly of interest in Bioinformatics studies. With sequence data becoming massively available, exhaustive enumeration of such measures have become conceivable, and yet pose significant computational burden even when limited to words of bounded maximum length. In addition, the display of the huge tables possibly resulting from these counts poses practical problems of visualization and inference. VERBUMCULUS is a suite of software tools for the efficient and fast detection of over- or under-represented words in nucleotide sequences. The inner core of VERBUMCULUS rests on subtly interwoven properties of statistics, pattern matching and combinatorics on words, that enable one to limit drastically and a priori the set of over- or under-represented candidate words of all lengths in a given sequence, thereby rendering it more feasible both to detect and visualize such words in a fast and practically useful way. This paper is devoted to the description of the facility at the outset and to report experimental results, ranging from simulations on synthetic data to the discovery of regulatory elements on the upstream regions of a set of genes of the yeast.

Measures relating word frequencies and expectations have been constantly of interest in Bioinformatics studies. With sequence data becoming massively available, exhaustive enumeration of such measures have become conceivable, and yet pose significant computational burden even when limited to words of bounded maximum length. In addition, the display of the huge tables possibly resulting from these counts poses practical problems of visualization and inference. VERBUMCULUS is a suite of software tools for the efficient and fast detection of over- or under-represented words in nucleotide sequences. The inner core of VERBUMCULUS rests on subtly interwoven properties of statistics, pattern matching and combinatorics on words, that enable one to limit drastically and a priori the set of over- or under-represented candidate words of all lengths in a given sequence, thereby rendering it more feasible both to detect and visualize such words in a fast and practically useful way. This paper is devoted to the description of the facility at the outset and to report experimental results, ranging from simulations on synthetic data to the discovery of regulatory elements on the upstream regions of a set of genes of the yeast.

Mannose-binding lectin (MBL) is an important complement-activating protein of the human immune system. As a result of one of three structural gene mutations in exon 1 (variants B, C and D) and/or the presence of a low-efficiency promoter polymorphism, MBL deficiency may be associated with increased susceptibility to infectious diseases and to autoimmune disorders, including systemic lupus erythematosus (SLE). Using a combined approach of heteroduplex generator and polymerase chain reaction, a systematic search for mutations in exon 1 and the promoter region of the MBL gene was performed in a Chinese study population comprising 41 SLE patients and 111 healthy controls. Two alleles, a wild-type allele A and a variant allele B (a previously reported mutation of GGC to GAC at codon 54), were identified in MBL exon 1. The frequency of the B allele (0.15) was higher in the SLE patients than in the healthy controls (0.09), but the difference did not attain statistical significance (P > 0.05). However, for two polymorphisms at positions -550 and -221 in the promoter region, the frequency of the low-MBL-producing haplotype (LX) in the patients (0.2073) was significantly higher than that in the controls (0.0855) (P = 0.003, relative risk = 2.79). Our results suggest that the LX haplotype represents a strong risk factor among Chinese SLE patients. Although of lesser importance, the MBL B allele also may be a risk component in the developing process of SLE in Chinese patients.

A study of disc cutting was carried out for seven selected rocks occurring in Japan, Korea and China using a circular rock cutting testing rig. The aim of the study programme was to establish: the optimal conditions for disc cutting, to find the relationship between the peak tool force and the mean tool force and to estimate the effect of the radius of the cutting track on the lateral component of the tool force. The main conclusions of the study are: the optimal ratio of tool space to disc penetration that allows the specific energy of rock excavation to be minimised depends on the fracture toughness and the uniaxial compressive strength of rock; the specific energy at the optimal cutting condition correlates linearly with the uniaxial compressive strength of the rock; all the components of tool force vary around their mean values, resulting in stochastic process - the lateral force fluctuates more than the rolling force, although their mean values are comparable to each other; the peak tool force is in proportion to the mean tool force - the magnification of peak to mean is 1.33, 1.60 and 1.63 for the thrust, the rolling force and the lateral force respectively, regardless of different types of rocks; and the magnitude of lateral force does not depend on the radius of the cutting track when rocks between neighbouring tracks are cut off completely - lateral force is always directed towards the adjacent cutting track., A study of disc cutting was carried out for seven selected rocks occurring in Japan, Korea and China using a circular rock cutting testing rig. The aim of the study programme was to establish: the optimal conditions for disc cutting, to find the relationship between the peak tool force and the mean tool force and to estimate the effect of the radius of the cutting track on the lateral component of the tool force. The main conclusions of the study are: the optimal ratio of tool space to disc penetration that allows the specific energy of rock excavation to be minimised depends on the fracture toughness and the uniaxial compressive strength of rock; the specific energy at the optimal cutting condition correlates linearly with the uniaxial compressive strength of the rock; all the components of tool force vary around their mean values, resulting in stochastic process - the lateral force fluctuates more than the rolling force, although their mean values are comparable to each other; the peak tool force is in proportion to the mean tool force - the magnification of peak to mean is 1.33, 1.60 and 1.63 for the thrust, the rolling force and the lateral force respectively, regardless of different types of rocks; and the magnitude of lateral force does not depend on the radius of the cutting track when rocks between neighbouring tracks are cut off completely - lateral force is always directed towards the adjacent cutting track.