1,729,353 research outputs found
Khamis Siam
No full textDr. Khamis Siam is a professory and advisor within the Chemistry Department and has a research focus on computational chemisty. He has served as KNEA president twice, first from 1998 to 1998 and again from 2019 to 2023
Posttraumatic stress and worry as mediators and moderators between political stressors and emotional and behavioral disorders in Palestinian children
No full textThis study was designed to assess whether the symptoms of posttraumatic stress mediate or moderate the relationship between political stressors and emotional and behavioral disorders in Palestinian children. It was hypothesized that (a) posttraumatic stress and worry mediate the effect of political stressors on behavioral and emotional disorders and (b) the relationship between political stressors and behavioral and emotional disorders should be attenuated for children with low levels of worry and posttraumatic stress and strengthened for children with high levels of worry and posttraumatic stress. The total sample was 1267 school age children of both sexes with a mean age of 11.97 years. Interviews were conducted with children at school. As hypothesized, the results indicated that posttraumatic stress and worry mediated and moderated the relationship between political stressors and emotional and behavioral disorders in children. Cognitive-behavioral therapy may be used to reduce the incidence of posttraumatic stress and decrease self-reported worry, somatic symptoms, general anxiety, and depression among children exposed to political trauma. Cognitive-behavioral treatment that exclusively targets excessive worry can lead to clinical change in the other interacting subsystems at the cognitive, physiological, affective and behavioral levels. © 2012 Taylor and Francis Group, LLC.Aiken L., 1991, MULTIPLE REGRESSION; Almqvist K, 1999, J AM ACAD CHILD PSY, V38, P723, DOI 10.1097-00004583-199906000-00020; American Psychiatric Association, 1994, DIAGN STAT MAN MENT; BARON RM, 1986, J PERS SOC PSYCHOL, V51, P1173, DOI 10.1037-0022-3514.51.6.1173; Borkovec T. D., 1999, COMPREHENSIVE CLIN P, V4, P439; BORKOVEC TD, 1993, J CONSULT CLIN PSYCH, V61, P611, DOI 10.1037-0022-006X.61.4.611; Breslau N, 2000, BIOL PSYCHIAT, V48, P902, DOI 10.1016-S0006-3223(00)00933-1; Cloitre M, 2009, J TRAUMA STRESS, V22, P399, DOI 10.1002-jts.20444; Diefenbach GJ, 2001, DEPRESS ANXIETY, V14, P247, DOI 10.1002-da.1075; Dorahy MJ, 2009, J AFFECT DISORDERS, V112, P71, DOI 10.1016-j.jad.2008.04.003; Dugas MJ, 1997, COGNITIVE THER RES, V21, P593, DOI 10.1023-A:1021890322153; Elbedour S, 2007, CHILD ABUSE NEGLECT, V31, P719, DOI 10.1016-j.chiabu.2005.09.006; Garmezy N, 1985, CHILD ADOL PSYCH CL, P152; Gilbertson MW, 2001, J TRAUMA STRESS, V14, P413, DOI 10.1023-A:1011181305501; Goodman R, 1997, J CHILD PSYCHOL PSYC, V38, P581, DOI 10.1111-j.1469-7610.1997.tb01545.x; Grych JH, 2000, J CONSULT CLIN PSYCH, V68, P84, DOI 10.1037--0022-006X.68.1.84; Hoagwood KE, 2007, J AM ACAD CHILD PSY, V46, P773, DOI 10.1097-chi.0b013e3180413def; Hoagwood KE, 2007, J CLIN CHILD ADOLESC, V36, P581; Horowitz M. J., 1979, PSYCHOSOM MED, V41, P207; Johansson P, 2007, CLIN PSYCHOL PSYCHOT, V14, P1, DOI 10.1002-cpp.514; Khamis V, 2008, SOC SCI MED, V67, P1199, DOI 10.1016-j.socscimed.2008.06.013; KHAMIS V, 1993, BEHAV MED, V19, P93; KHAMIS V, 1993, J TRAUMA STRESS, V6, P555, DOI 10.1002-jts.2490060411; Khamis V, 2005, CHILD ABUSE NEGLECT, V29, P81, DOI 10.1016-j.chiabu.2004.06.013; Khamis V, 1998, SOC SCI MED, V46, P1033, DOI 10.1016-S0277-9536(97)10032-6; Khamis V., 2000, POLITICAL VIOLENCE P; Kivisto AJ, 2009, J TRAUMA STRESS, V22, P344, DOI 10.1002-jts.20425; Ladouceur R, 2000, J CONSULT CLIN PSYCH, V68, P957, DOI 10.1037-0022-006X.68.6.957; Litz BT, 2002, CLIN PSYCHOL-SCI PR, V9, P112, DOI 10.1093-clipsy-9.2.112; MALMQUIST CP, 1986, J AM ACAD CHILD PSY, V25, P320, DOI 10.1016-S0002-7138(09)60253-3; Masten AS, 2001, AM PSYCHOL, V56, P227, DOI 10.1037--0003-066X.56.3.227; MATHEWS A, 1990, BEHAV RES THER, V28, P455, DOI 10.1016-0005-7967(90)90132-3; McNally RJ, 2003, PSYCHOL SCI PUBLIC I, V4, P45, DOI [DOI 10.1111-1529-1006.01421, 10.1111-1529-1006.01421]; Meewisse M. L., 2005, J TRAUMA STRESS, V4, P299; MEYER TJ, 1990, BEHAV RES THER, V28, P487, DOI 10.1016-0005-7967(90)90135-6; Muris P, 2001, J BEHAV THER EXP PSY, V32, P63, DOI 10.1016-S0005-7916(01)00022-2; Sachinvala N, 2000, J NERV MENT DIS, V188, P818, DOI 10.1097-00005053-200012000-00005; Taft CT, 2007, J ABNORM PSYCHOL, V116, P498, DOI 10.1037-0021-843X.116.3.498; Thabet AAM, 2002, LANCET, V359, P1801, DOI 10.1016-S0140-6736(02)08709-3; Thabet AAM, 2004, J CHILD PSYCHOL PSYC, V45, P533, DOI 10.1111-j.1469-7610.2004.00243.x; Vasterling JJ, 2002, NEUROPSYCHOLOGY, V16, P5, DOI 10.1037--0894-4105.16.1.5; Wells A., 1994, ATTENTION EMOTION CL; Yates TM, 2003, DEV PSYCHOPATHOL, V15, P199, DOI 10.1017-S0954579403000117; Yilmaz E., 2008, CLIN PSYCHOL PSYCHOT, V15, P424; Yule W., 1994, INT HDB PHOBIC ANXIE, P223; ZILBERG NJ, 1982, J CONSULT CLIN PSYCH, V50, P407, DOI 10.1037-0022-006X.50.3.40712
Das SeBiLe-Curriculum – Anliegen, Module und Evaluation
No full textKapitel aus: Urban, M., Wienholz, S., & Khamis, C. (Eds.). (2022). Sexuelle Bildung für das Lehramt – Zur Notwendigkeit der Professionalisierung. Psychosozial-Verlag.https://www.psychosozial-verlag.de/catalog/product_info.php/cPath/20000/products_id/7825peerReviewedpublishedVersio
Radio program about Soad Hosny
No full textهذا التقرير عن حياة وانجازات الفنانة المصرية سعاد حسني. يتضمن التقرير مقتطفات من مقابلة مع سعاد حسني وهي تناقش اعمالها وبالأخص دورها في فيلم "الراعي والنساء". يتضمن أيضا التقرير كلمة للممثل عادل امام وهي يتحدث عن شخص سعاد حسني. التقرير من اعداد حسن شمس الدين.This report is about the life and work of Egyptian actress Soad Hosny. The report contains excerpts from an interview with Soad Hosny speaking about her work and her role in the film "The Shepherd and The Women". The report also contains excerpts from a word by Egyptian actor Adel Imam speaking about Hosny's character and achievements
TELE ECG Database: 250 telehealth ECG records (collected using dry metal electrodes) with annotated QRS and artifact masks, and MATLAB code for the UNSW artifact detection and UNSW QRS detection algorithms
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CITATION
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Please cite this data and code as:
H. Khamis, R. Weiss, Y. Xie, C-W. Chang, N. H. Lovell, S. J. Redmond, "QRS detection algorithm for telehealth electrocardiogram recordings," IEEE Transaction in Biomedical Engineering, vol. 63(7), p. 1377-1388, 2016.
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DATABASE DESCRIPTION
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The following description of the TELE database is from Khamis et al (2016):
"In Redmond et al (2012), 300 ECG single lead-I signals recorded in a telehealth environment are described. The data was recorded using the TeleMedCare Health Monitor (TeleMedCare Pty. Ltd. Sydney, Australia). This ECG is sampled at a rate of 500 Hz using dry metal Ag/AgCl plate electrodes which the patient holds with each hand; a reference electrode plate is also positioned under the pad of the right hand. Of the 300 recordings, 250 were selected randomly from 120 patients, and the remaining 50 were manually selected from 168 patients to obtain a larger representation of poor quality data.
Three independent scorers annotated the data by identifying sections of artifact and QRS complexes. All scorers then annotated the signals as a group, to reconcile the individual annotations. Sections of the ECG signal which were less than 5 s in duration were considered to be part of the neighboring artifact sections and were subsequently masked. QRS annotations in the masked regions were discarded prior to the artifact mask and QRS locations being saved.
Of the 300 telehealth ECG records in Redmond et al. (2012), 50 records (including 29 of the 250 randomly selected records and 21 of the 50 manually selected records) were discarded as all annotated RR intervals within these records overlap with the annotated artifact mask and therefore, no heart rate can be calculated, which is required for measuring algorithm performance. The remaining 250 records will be referred to as the TELE database."
For all 250 recordings in the TELE database, the mains frequency was 50 Hz, the sampling frequency was 500 Hz and the top and bottom rail voltages were 5.556912223578890 and -5.554198887532222 mV respectively.
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DATA FILE DESCRIPTION
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Each record in the TELE database is stored as a X_Y.dat file where X indicates the index of the record in the TELE database (containing a total of 250 records) and Y indicates the index of the record in the original dataset containing 300 records (see Redmond et al. 2012).
The .dat file is a comma separated values file. Each line contains:
- the ECG sample value (mV)
- a boolean indicating the locations of the annotated qrs complexes
- a boolean indicating the visually determined mask
- a boolean indicating the software determined mask (see Khamis et al. 2016)
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CONVERTING DATA TO MATLAB STRUCTURE
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A matlab function (readFromCSV_TELE.m) has been provided to read the .dat files into a matlab structure:
%%
% [DB,fm,fs,rail_mv] = readFromCSV_TELE(DATA_PATH)
%
% Extracts the data for each of the 250 telehealth ECG records of the TELE database [1]
% and returns a structure containing all data, annotations and masks.
%
% IN: DATA_PATH - String. The path containing the .hdr and .dat files
%
% OUT: DB - 1xM Structure. Contains the extracted data from the M (250) data files.
% The structure has fields:
% * data_orig_ind - 1x1 double. The index of the data file in the original dataset of 300 records (see [1]) - for tracking purposes.
% * ecg_mv - 1xN double. The ecg samples (mV). N is the number of samples for the data file.
% * qrs_annotations - 1xN double. The qrs complexes - value of 1 where a qrs is located and 0 otherwise.
% * visual_mask - 1xN double. The visually determined artifact mask - value of 1 where the data is masked and 0 otherwise.
% * software_mask - 1xN double. The software artifact mask - value of 1 where the data is masked and 0 otherwise.
% fm - 1x1 double. The mains frequency (Hz)
% fs - 1x1 double. The sampling frequency (Hz)
% rail_mv - 1x2 double. The bottom and top rail voltages (mV)
%
% If you use this code or data, please cite as follows:
%
% [1] H. Khamis, R. Weiss, Y. Xie, C-W. Chang, N. H. Lovell, S. J. Redmond,
% "QRS detection algorithm for telehealth electrocardiogram recordings,"
% IEEE Transaction in Biomedical Engineering, vol. 63(7), p. 1377-1388,
% 2016.
%
% Last Modified: 05/09/2016
%
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CALCULATING ARTIFACT MASKS – UNSW Artifact Detection Algorithm
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A matlab function (UNSW_ArtifactMask.m) has been provided to compute the Rail Contact, High Frequency, Low Power, Baseline Shift and Final artifact masks described in Khamis et al 2016:
%%
% [rcmask,hfmask,lpmask,bsmask,finalmask] = UNSW_ArtifactMask(rawecg,railV,fm,fs)
%
% Determines the ECG artifact mask as described in [1]
%
% IN: rawecg - 1xN double. The ECG samples (mV). N is the number of samples.
% railV - 1x2 double. Bottom and top rail voltages (mV).
% fm - 1x1 double. The mains frequency (Hz)
% fs - 1x1 double. The sampling frequency (Hz)
%
% OUT: rcmask - 1xM1 double. M1 is the number of masked samples. Indices in rawecg of the rail contact mask - See RC Mask in [1].
% hfmask - 1xM2 double. M2 is the number of masked samples. Indices in rawecg of the high frequency mask - See HF Mask in [1].
% lpmask - 1xM3 double. M3 is the number of masked samples. Indices in rawecg of the low power mask - See LP Mask in [1].
% bsmask - 1xM4 double. M4 is the number of masked samples. Indices in rawecg of the baseline shift mask - See BS Mask in [1].
% finalmask - 1xM5 double. M5 is the number of masked samples. Indices in rawecg of the final mask - See Final Mask in [1].
%
%
% This function uses the files sortfilt1.m, medianfilter.mexw64 and
% minmaxfilter.mexw64 - Ensure that these files are on the MATLAB path.
%
% If the .mexw64 files are incompatible with you version of MATLAB, please
% rebuild the mex files from the corresponding .cpp and .h files provided.
%
% If you use this code or data, please cite as follows:
%
% [1] H. Khamis, R. Weiss, Y. Xie, C-W. Chang, N. H. Lovell, S. J. Redmond,
% "QRS detection algorithm for telehealth electrocardiogram recordings,"
% IEEE Transaction in Biomedical Engineering, vol. 63(7), p. 1377-1388,
% 2016.
%
% Last Modified: 05/09/2016
%
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DETECTING QRS LOCATIONS – UNSW QRS Detection Algorithm
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A matlab function (UNSW_QRSDetector.m) has been provided which is an implementation of the QRS detector algorithm described in Khamis et al 2016:
%%
% [qrs,RRlist,nRR,mRR,nSections] = UNSW_QRSDetector(rawecg,fs,mask,isplot)
%
% Determines the QRS locations in the raw ECG based on the UNSW QRS detection algorithm
%
% IN: rawecg - 1xN double. The ECG samples (mV). N is the number of samples.
% fs - 1x1 double. The sampling frequency (Hz)- A vector of ECG amplitude.
% mask - 1xM double. Indices of the artifact mask.
% isplot - 1x1 boolean. True for ploting intermediate signals. False for no plotting.
%
% OUT: qrs - 1xQ double. Indices of the qrs locations.
% RRlist - 1xR double. Indices of the RR-intervals in samples (not interupted by masking).
% nRR - 1x1 double. The number of RR-intervals (not interupted by masking).
% meanRR - 1x1 double. The mean RR interval in samples (not interupted by masking).
% nSections - 1x1 double. The number of unmasked sections of ECG.
%
%
% This function uses the files sortfilt1.m, medianfilter.mexw64 and
% minmaxfilter.mexw64 - Ensure that these files are on the MATLAB path.
%
% If the .mexw64 files are incompatible with you version of MATLAB, please
% rebuild the mex files from the corresponding .cpp and .h files provided.
%
% If you use this code or data, please cite as follows:
%
% [1] H. Khamis, R. Weiss, Y. Xie, C-W. Chang, N. H. Lovell, S. J. Redmond,
% "QRS detection algorithm for telehealth electrocardiogram recordings,"
% IEEE Transaction in Biomedical Engineering, vol. 63(7), p. 1377-1388,
% 2016.
%
% Last Modified: 05/09/2016
%
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REFERENCES
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H. Khamis, R. Weiss, Y. Xie, C-W. Chang, N. H. Lovell, S. J. Redmond, "QRS detection algorithm for telehealth electrocardiogram recordings," IEEE Transaction in Biomedical Engineering, vol. 63(7), p. 1377-1388, 2016.
S. J. Redmond, Y. Xie, D. Chang, J. Basilakis, and N. H. Lovell, "Electrocardiogram signal quality measures for unsupervised telehealth environments," Physiological Measurement, vol. 33, p. 1517, 2012.<br
Eltern als bedeutsame AkteurInnen der Prävention von sexualisierter Gewalt
No full textKapitel aus: Urban, M., Wienholz, S., & Khamis, C. (Eds.). (2022). Sexuelle Bildung für das Lehramt – Zur Notwendigkeit der Professionalisierung. Psychosozial-Verlag.https://www.psychosozial-verlag.de/catalog/product_info.php/cPath/20000/products_id/7825peerReviewedpublishedVersio
Stressors, family environment and coping styles as predictors of educational and psychosocial adjustment in Palestinian children
No full textThis study investigated the contributions of child and parents' sociodemographics, daily stressors, family environment, and coping strategies, to academic achievement, cognitive functioning and aggression in a sample of 600 children at the intermediate grade levels from Gaza Strip. Each of the predictor variables exhibited a different pattern of relations with the outcome domains. Although the study highlights the negative consequences of stress on children's development, certain daily stressors had a positive effect. Optimal family relationships predicted better developmental outcomes. More emphasis on personal growth, control and organisation in the family predicted less optimal child development except for personal growth and achievement. More reliance on positive coping and less reliance on negative coping is associated with better academic achievement. The clinical and research implications of the findings are discussed. © 2013 Taylor and Francis.Achenbach TM, 2001, MANUAL ASEBA SCH AGE; Barrera M. A., 1981, SOCIAL NETWORKS SOCI, P69; BOGENSCHNEIDER K, 1994, SOCIOL EDUC, V67, P60, DOI 10.2307-2112750; Bongers IL, 2003, J ABNORM PSYCHOL, V112, P179, DOI 10.1037-0021-843X.112.2.179; Bradley RH, 2005, DEV PSYCHOL, V41, P89, DOI 10.1037-0012-1649.41.1.89; Bronfenbrenner U., 1979, ECOLOGY HUMAN DEV EX; Cairns E., 2001, INT ENCY SOCIAL BEHA, P16360; Causey D., 1993, PREVENTION SCH TRANS, P59; Compas BE, 2001, PSYCHOL BULL, V127, P87, DOI 10.1037--0033-2909.127.1.87; Cummings M., 2009, CLIN CHILD FAM PSYCH, V12, P16; Eisenberg N, 2005, CHILD DEV, V76, P1055, DOI 10.1111-j.1467-8624.2005.00897.x; Evans GW, 2002, CHILD DEV, V73, P1238, DOI 10.1111-1467-8624.00469; Folkman S, 1997, SOC SCI MED, V45, P1207, DOI 10.1016-S0277-9536(97)00040-3; Gelhaar T, 2007, EUR J DEV PSYCHOL, V4, P129, DOI 10.1080-17405620600831564; Hinkle D. E., 2003, APPL STAT BEHAV SCI; Khamis V, 2012, SOC SCI MED, V74, P2005, DOI 10.1016-j.socscimed.2012.02.025; Khamis V., 2000, POLITICAL VIOLENCE P; Kiser L. J., 2010, TRAUMATOLOGY, V16, P33, DOI [10.1177-1534765609358466, DOI 10.1177-1534765609358466]; KURDEK LA, 1988, J EDUC PSYCHOL, V80, P90, DOI 10.1037-0022-0663.80.1.90; La Greca A. M., 2001, ANXIETY DISORDERS CH, P159; Lazarus R. S., 1984, STRESS APPRAISAL COP; Li H, 2008, DEMOGRAPHY, V45, P223, DOI 10.1353-dem.2008.0006; Lugo-Gil J, 2008, CHILD DEV, V79, P1065, DOI 10.1111-j.1467-8624.2008.01176.x; McLoyd VC, 1998, AM PSYCHOL, V53, P185, DOI 10.1037-0003-066X.53.2.185; Merton R. K., 1957, SOCIAL THEORY SOCIAL; Moos B., 2002, FAMILY ENV SCALE; Morales JR, 2006, CHILD DEV, V77, P907, DOI 10.1111-j.1467-8624.2006.00910.x; Palestinian Centre for Human Rights (PCHR), 2008, POV GAZ STRIP; Pearlin L., 1993, HDB STRESS THEORETIC, P303; Poulin M, 2008, PSYCHOL AGING, V23, P13, DOI 10.1037-0882-7974.23.1.13; Punamaki RL, 2001, J COMMUNITY PSYCHOL, V29, P281, DOI 10.1002-jcop.1018; Rogers KN, 2003, J EARLY ADOLESCENCE, V23, P349, DOI 10.1177-0272431603258344; Schroeder VM, 2009, J CHILD FAM STUD, V18, P227, DOI 10.1007-s10826-008-9223-0; Seery MD, 2010, J PERS SOC PSYCHOL, V99, P1025, DOI 10.1037-a0021344; SPIRITO A, 1988, J PEDIATR PSYCHOL, V13, P555, DOI 10.1093-jpepsy-13.4.555; Wadsworth M. E., 2005, J CHILD FAM STUD, V14, P283, DOI DOI 10.1007-S10826-005-5056-211
Predicting Adult Stature Without Using Skeletal Age: The Khamis-Roche Method
No full textStudy objective. To obtain reliable and accurate predictions of adult stature in white American children who are free of disease without using skeletal age. Design. Apply a modification of the Roche-Wainer-Thissen stature prediction model to a sample of white American children. Setting. Longitudinal data (every 6 months) from participants in the Fels Longitudinal Study were used for the development of the stature prediction model. Participants. Residents of Southwest Ohio, 223 white males and 210 white females, at the time of their enrollment into the Fels Longitudinal Study. Measurements and results. The errors of the proposed method, which does not use skeletal age as a predictor variable, are only slightly larger than those for the Roche-Wainer-Thissen method which uses skeletal age as a predictor variable. Conclusions. Adult stature predictions are needed commonly but the current methods are difficult to apply because they require a skeletal age assessed by a modern method. The Khamis-Roche method predicts adult stature in the absence of skeletal age with only a slight deterioration in accuracy and reliability. The applicability of the Khamis-Roche method is limited to white American children without pathologic conditions that alter the potential for growth in stature, but it should be useful for white children who are unusual in stature or in levels of maturity for age
Interview with Abdullah bin Khamis
No full textمقابلة مع الشاعر السعودي ومدير كليتي الشريعة واللغة بالرياض وعضوا ببيت الحكمة، عبد الله بن خميس، يناقش فيها الحركة الأدبية والشعرية في السعودية . قام بالمقابلة حسن شمس الدين.An interview with Saudi poet and director of the College of Sharia (Islamic Law) and Language in Riyadh and a member of the House of Wisdom, Abdullah Al-Khamis (Abdullah bin Khamis), in which he discusses the literary and poetic movement in Saudi Arabia. The interview was conducted by Hassan Shams Al-Din
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