Pengaruh Penyuluhan Obat Terhadap Peningkatan Perilaku Pengobatan Sendiri Di Kabupaten Banyumas

Self-medication is the mostly effort to coped health complaint, therefore to drug consume decrease unsuitable, it needed safety socialization to self-medication. The study was take to analyze the effect of drug counseling to self-medication increase in Banyumas regency. In addition to analyze the method effectiveness used in drug counseling to self-medication act. The instrument research used questionnaires in this study and purposive sampling used to took the sample. The respondents were 192 residents whom live in Banyumas regency. The type of research quasi-experimental with non-equivalent control group pretest and posttest research design. The data then analyzed by dependent-sampel t-test to find the effect of counseling to self-medication behavior in α = 0.05. While to find the effectiveness of between discussion group and lecture method by leaflet used independen-sampel t-test in α = 0.05. The results showed there significant different between before and after drug counseling by discussion goup and lecture method used leaflet media, able to self-medication attitude improved such as knowledge and attitude about self-medication (P= 0.000), also it can to know both of methods as effective as to self-medication attitude which showed P=0.05. It\u27s mean both of drug counseling methods used as effective as to self-medication attitude improvement. Key words: self medication attitude, counseling methods, housewife, Banyumas

Magnetostriction studies up to megagauss fields using fiber Bragg grating technique

We here report magnetostriction measurements under pulsed megagauss fields using a high-speed 100 MHz strain monitoring system devised using fiber Bragg grating (FBG) technique with optical filter method. The optical filter method is a detection scheme of the strain of FBG, where the changing Bragg wavelength of the FBG reflection is converted to the intensity of reflected light to enable the 100 MHz measurement. In order to show the usefulness and reliability of the method, we report the measurements for solid oxygen, spin-controlled crystal, and volborthite, a deformed Kagom\'{e} quantum spin lattice, using static magnetic fields up to 7 T and non-destructive millisecond pulse magnets up to 50 T. Then, we show the application of the method for the magnetostriction measurements of CaV$_{4}$O$_{9}$, a two-dimensional antiferromagnet with spin-halves, and LaCoO$_{3}$, an anomalous spin-crossover oxide, in the megagauss fields.Comment: 9pages, 6 figures, Conference proceedings for MegaGauss16 at Kashiwa, Japan in Sept. 201

Output Prediction Attacks on Block Ciphers using Deep Learning

Cryptanalysis of symmetric-key ciphers, e.g., linear/differential cryptanalysis, requires an adversary to know the internal structures of the target ciphers. On the other hand, deep learning-based cryptanalysis has attracted significant attention because the adversary is not assumed to have knowledge about the target ciphers with the exception of the algorithm interfaces. Such cryptanalysis in a blackbox setting is extremely strong; thus, we must design symmetric-key ciphers that are secure against deep learning-based cryptanalysis. However, almost previous attacks do not clarify what features or internal structures affect success probabilities. Although Benamira et al. (Eurocrypt 2021) and Chen et al. (ePrint 2021) analyzed Gohr’s results (CRYPTO 2019), they did not find any deep learning specific characteristic where it affects the success probabilities of deep learning-based attacks but does not affect those of linear/differential cryptanalysis. Therefore, it is difficult to employ the results of such cryptanalysis to design deep learning-resistant symmetric-key ciphers. In this paper, we propose deep learning-based output prediction attacks in a blackbox setting. As preliminary experiments, we first focus on two toy SPN block ciphers (small PRESENT-[4] and small AES-[4]) and one toy Feistel block cipher (small TWINE-[4]). Due to its small internal structures with a block size of 16 bits, we can construct deep learning models by employing the maximum number of plaintext/ciphertext pairs, and we can precisely calculate the rounds in which full diffusion occurs. Next, based on the preliminary experiments, we explore whether the evaluation results obtained by our attacks against three toy block ciphers can be applied to block ciphers with large block sizes, e.g., 32 and 64 bits. As a result, we demonstrate the following results, specifically for the SPN block ciphers: First, our attacks work against a similar number of rounds that the linear/differential attacks can be successful. Next, our attacks realize output predictions (precisely ciphertext prediction and plaintext recovery) that are much stronger than distinguishing attacks. Then, swapping or replacing the internal components of the target block ciphers affects the average success probabilities of the proposed attacks. It is particularly worth noting that this is a deep learning specific characteristic because swapping/replacing does not affect the average success probabilities of the linear/differential attacks. Finally, by analyzing the influence of the differences in the characteristics of three S-boxes (i.e., the original PRESENT S-box and two known weak S-boxes) on deep learning specific characteristics, we clarify that the resistance of the target ciphers to differential/linear attacks can affect the success probability of deep learning-based attacks. We also confirm whether the proposed attacks work on the Feistel block cipher. We expect that our results will be an important stepping stone in the design of deep learning-resistant symmetric-key ciphers

A Case of Retroperitoneal Malignant Mesenchymoma

A rare case of malignant mesenchymoma of a retroperitoneal lesion, com-posed of liposarcoma and osteosarcoma, is reported. For complete resection of the tumor, two surgical operations were performed. The first operative material showed a mass measuring 20 x 20 x 10 cm, weighing 1607g, arising from the soft tissue of the left retroperitoneum and the tumor had a smooth surface and elastic-hard consistency. The secondary operative materials exhi-bited a mass measuring 10 x 5 x 3 cm, weighing 268g. The tumor was com-posed of soft gelatinous tissues and adhered to the tail of the pancreas but was separate from the spleen. More than 3 years after the secondary operation, no recurrence has been observed. Immunohistochemical examinations showed that S-100 protein and non-specific enolase were present in the liposarcoma-tous area and that vimentin was positive in the osteosarcomatous area

Improved long-term performance of pulsatile extracorporeal left ventricular assist device

SummaryBackground and purposeThe majority of heart transplant (HTx) candidates require left ventricular assist device (LVAD) support for more than 2 years before transplantation in Japan. However, the only currently available device is the extracorporeal pulsatile LVAD. The long-term management of extracorporeal LVAD support has improved remarkably over the years. To determine which post-operative management factors are related to the long-term survival of patients on such LVAD, we retrospectively compared the incidence of complications and their management strategies between the initial and recent eras of LVAD use, classified by the year of LVAD surgery.MethodsSixty-nine consecutive patients supported by extracorporeal pulsatile LVAD as a bridge to HTx between 1994 and 2007 were reviewed retrospectively. The patients were assigned according to the time of LVAD surgery to either group A (n=30; between 1994 and 2000) or group B (n=39; between 2001 and 2007).ResultsPatients in group B survived significantly longer on LVAD support than those in group A (674.6 vs. 369.3 days; p<0.001). The 1- and 2-year survival rates were significantly higher in group B than that in group A (82% vs. 48%, p<0.0001; 68% vs. 23%, p<0.0001, respectively). The proportion of deaths due to cerebrovascular accidents was lower (17% vs. 50%, p<0.001) in group B compared with group A. The incidences of systemic infection were similar in both groups, but the proportions of patients alive and achieving transplant surgery after systemic infection were higher in group B than those in group A (55% vs. 14%, p<0.01; 14% vs. 36%, p<0.05, respectively).ConclusionsThe long-term survival of patients even on “first-generation” extracorporeal LVAD has improved significantly in the recent era. Careful management of cerebrovascular accidents and systemic infection will play important roles in the long-term LVAD management

JASMINE: Near-infrared astrometry and time-series photometry science

The Japan Astrometry Satellite Mission for INfrared Exploration (JASMINE) is a planned M-class science space mission by the Institute of Space and Astronautical Science, the Japan Aerospace Exploration Agency. JASMINE has two main science goals. One is Galactic archaeology with a Galactic Center survey, which aims to reveal the Milky Way’s central core structure and formation history from Gaia-level (∼25 ${\mu}$as) astrometry in the near-infrared (NIR) Hw band (1.0–1.6 ${\mu}$m). The other is an exoplanet survey, which aims to discover transiting Earth-like exoplanets in the habitable zone from NIR time-series photometry of M dwarfs when the Galactic Center is not accessible. We introduce the mission, review many science objectives, and present the instrument concept. JASMINE will be the first dedicated NIR astrometry space mission and provide precise astrometric information on the stars in the Galactic Center, taking advantage of the significantly lower extinction in the NIR. The precise astrometry is obtained by taking many short-exposure images. Hence, the JASMINE Galactic Center survey data will be valuable for studies of exoplanet transits, asteroseismology, variable stars, and microlensing studies, including discovery of (intermediate-mass) black holes. We highlight a swath of such potential science, and also describe synergies with other missions